Curving beams are a promising new method for bypassing obstacles in future millimeter-wave to sub-terahertz (sub-THz) networks but lack a general predictive model for their reflections from arbitrary surfaces. We show that, unfortunately, attempting to "mirror" the incident beam trajectory across the normal of the reflector, as in ray optics, fails in general. Thus, we introduce the first geometric framework capable of modeling the reflections of arbitrary convex sub-THz curving beams from general reflectors with experimental verification. Rather than "mirroring" the trajectory, we decompose the beam into a family of tangents and demonstrate that this process is equivalent to the Legendre transform. This approach allows us to accurately account for reflectors of any shape, size, and position while preserving the underlying physics of wave propagation. Our model is validated through finite element method simulations and over-the-air experiments, demonstrating millimeter-scale accuracy in predicting reflections. Our model provides a foundation for future curving beam communication and sensing systems, enabling the design of reflected curved links and curving radar paths.

Metasurfaces enable controllable manipulation of electromagnetic waves and have been shown to be valuable for wireless communications in many diverse ways. In this paper, we explore the notion that these useful components could also provide opportunities for a malicious agent. In particular, we define and experimentally demonstrate for the first time a “MetaSurface-in-the-Middle” (MSITM) attack. In this attack, the adversary Eve places a metasurface in the path of a directive transmission between Alice and Bob and targets to re-direct a portion of the signal towards herself, without being detected. Specifically, we show how Eve can design a metasurface that induces abrupt phase changes at the interface of the metasurface to controllably diffract directional links and establish furtive eavesdropping links. We explore the theoretical foundations of the MSITM attack and demonstrate that an effective metasurface can be prototyped in under 5 min at a minimal cost. We experimentally demonstrate the attack in a THz time-domain system and perform a set of over-the-air experiments. Our results indicate that the MSITM attack yields an acute vulnerability that can significantly reduce empirical secrecy capacity while leaving a minimal energy footprint, making the attack challenging to detect.

In theory, sub-terahertz (sub-THz) communication offers the potential for near-field beam focusing, that can far surpass conventional far-field beam steering by directing energy to a specific point in space rather than a broad angular direction. In this paper, we introduce TeraFocus, the first adaptive beam focusing system for sub-THz wideband communication. Moreover, we present the first experimental demonstration of a wideband focusing link, in contrast to prior experiments with monochromatic sources. With TeraFocus, we demonstrate how metasurfaces with thousands of radiating elements (81 by 81 for a total of 6,561), can create the non-linear phase gradient required for precise beam focusing, achieving a 60 GHz 3-dB bandwidth. Moreover, TeraFocus maximizes link capacity by addressing the inherent spectral asymmetry in metasurface responses. Finally, for mobile clients, TeraFocus dynamically compensates for misalignment by leveraging the frequency-dependent focal length characteristic, allowing it to adapt to radial mobility without relying on traditional localization algorithms, which can be time-consuming, computationally expensive, and error-prone. Instead, TeraFocus re-localizes the client by analyzing the received spectral signature of a misaligned focusing beam, achieving a maximum error of less than 0.2 cm.

Wireless eavesdropping on phone conversations has become a major security and safety concern, especially with advancements toward 5G and beyond featuring higher frequencies and higher sensing resolution. As demonstrated recently, attackers can remotely detect even micron-scale acoustic vibrations emanating from a smartphone's earpiece via off-the-shelf millimeter-wave radar for audio information eavesdropping, all without the victim ever noticing. Here, we present a new architecture, MiSINFO, that not only thwarts such attacks but also enables the victim to counter-attack by spoofing of eavesdroppers with audio misinformation. With emerging attacks targeting the physical medium, i.e., acoustic signals, which cannot be protected by digital encryption and are the weakest segment of the communication chain, MiSINFO aims to systematically modify the eavesdroppers' fundamental sensing observations, concealing native signals while encoding alternate synthetic data. MiSINFO incorporates a low-profile, reconfigurable metasurface and double-inference principles to dynamically generate artificial audio-vibration signatures, injecting deceptive misinformation. We design, implement, and experimentally evaluate MiSINFO. Our results reveal that eavesdroppers detect none of the original words emitted by the speaker, while the injected misinformation is reconstructed with a low average word error rate of 2.29%. Our work represents the first such eavesdropping countermeasure which not only prevents attackers from accurately decoding the true signal but also uses a false signal to fool them into believing that they have succeeded. This approach transforms defensive measures from merely reactive to proactively deceptive, giving the defender an advantage and the capability to delude attackers into trusting false information.

Wireless eavesdropping on phone conversations has become a major security concern as attackers repurpose advanced wireless capabilities in 5G and beyond featuring higher frequencies and higher sensing resolution. Recent studies have demonstrated that attackers can exploit off-the-shelf millimeter-wave radars to covertly detect even micron-scale vibrations of smartphones caused by the earpiece during the phone conversation, eavesdropping on audio information without the victim ever noticing. In our IEEE S&P'25 paper, we present a new architecture that not only thwarts such attacks but also injects false signatures to fool eavesdroppers into believing they have succeeded. Here, we demonstrate the eavesdropping countermeasure technique that enables the user to hide his private acoustic signals and simultaneously inject an alternative signal via a low-profile, reconfigurable metasurface. We present a metasurface-based audio encoding method that generates artificial audio-vibration signatures to send deceptive audio information to eavesdroppers. We showcase experimental audio samples from both the attack and the proposed countermeasure, which transforms defensive strategies from merely reactive to proactively deceptive.

Today, Wi-Fi is over 25 years old. Yet, despite sharing the same branding name, today’s Wi-Fi boasts entirely new capabilities that were not even on the roadmap 25 years ago. This article aims to provide a holistic and comprehensive technical and historical tutorial on Wi-Fi, beginning with Institute of Electrical and Electronics Engineers 802.11b (Wi-Fi 1) and looking forward to IEEE 802.11bn (Wi-Fi 8). This is the first tutorial article to span these eight generations. Rather than a generation-by-generation exposition, we describe the key mechanisms that have advanced Wi-Fi. We begin by discussing spectrum allocation and coexistence, and detailing the IEEE 802.11 standardization cycle. Second, we provide an overview of the physical layer (PHY) and describe key elements that have enabled data rates to increase by over 1000×. Third, we describe how Wi-Fi medium access control (MAC) has been enhanced from the original distributed coordination function (DCF) to now include capabilities spanning from frame aggregation to wideband spectrum access. Fourth, we describe how Wi-Fi 5 first broke the one-user-at-a-time paradigm and introduced multi-user (MU) access. Fifth, given the increasing use of mobile, battery-powered devices, we describe Wi-Fi’s energy-saving mechanisms over the generations. Sixth, we discuss how Wi-Fi was enhanced to seamlessly aggregate spectrum across 2.4-, 5-, and 6-GHz bands to improve throughput, reliability, and latency. Finally, we describe how Wi-Fi enables nearby access points (APs) to coordinate in order to improve performance and efficiency. In the Appendix, we further discuss Wi-Fi developments beyond 802.11bn, including integrated millimeter-wave (IMMW) operations, sensing, security and privacy extensions, and the adoption of artificial intelligence (AI)/machine learning (ML).

THz communication can realize the next order of magnitude in data rate and user densities due to the availability of wide THz-scale spectral bands. Wide bandwidth links can exhibit angular dispersion, i.e., frequency-dependent radiation direction. While angular dispersion has enabled path discovery and dynamic beam steering via frequency tuning, multi-user communication in THz links remains an unaddressed challenge. This paper presents the first study and performance evaluation of multi-user THz WLANs with angularly dispersive links. We employ a single parallel-plate Leaky-Wave Antenna (LWA) for THz directional transmission and present a multi-user communication strategy that exploits angular dispersion and angular separation of users and provides all-spectrum access to users located in different directions with the objective of aggregate rate maximization. With analytical model-driven evaluations and over-the-air experiments that inform our trace-driven emulation of multi-user conditions, we show how the multi-user performance of an angularly dispersive LWA link fundamentally depends on frequency, angle, and bandwidth utilized by users through non-linear mechanisms. As increasing bandwidth yields a larger signal footprint in LWA links, we demonstrate that as compared to the model prediction, not only is the aggregate data rate maximized with wider beams, but the experimental link is far better even for practical irregular beams with side lobes and asymmetry. Our experimental findings reveal the potential of leveraging angular dispersion and users’ angular separation to establish a scalable THz wireless link that offers contention-free or medium access control-free access. Our results demonstrate the feasibility of accommodating up to 11 simultaneous users, making it a promising candidate solution for densely populated user environments.

In this paper, we propose FloatSense, a novel balloon-based UAV network system for efficient and robust air pollution monitoring. Unlike prior related work commonly leveraging rotary-wing drones, FloatSense UAVs mainly exploit helium balloons to maintain elevation and use small lightweight normally-off fans as a propulsion mechanism. The proposed design enables as a result extended environmental sensing missions by staying afloat for weeks. However, the wind-dependent mobility nature of balloon systems involves multiple challenges in terms of system design and pollution mapping. We address in this paper the aforementioned challenges as we design and experimentally evaluate FloatSense in order to identify the benefits of the helium-powered flight mechanism on the accuracy of air pollution mapping compared to traditional rotatory-wing drones. We reveal that although balloon-based UAVs are prone to drifting off due to external forces like wind, FloatSense outperforms traditional drones even in the presence of considerable wind speeds. Moreover, we show that the wind-dependent balloon mobility nature also contributes to the performance improvement of FloatSense in air pollution monitoring missions.

The next generation of wireless networks will utilize highly directional beams to overcome the path loss at high frequencies, requiring angle inference during link establishment. Furthermore, the integration of location-based services into the wireless infrastructure is rapidly increasing, bringing in a significant demand for an integrated fast localization scheme. In this work, we present a first-of-its-kind one-shot angular localization method that is carried out with a re-configurable architecture that unlocks ISAC functionality. Specifically, we use an electrically tunable metasurface with broadband response to generate wavefronts that are randomized across the angular space with diverse wideband amplitude and phase observations, corresponding to a collection of angle-unique one-shot beacons. Our results show down to 0.26° mean absolute error at 20 dB SNR, an order of magnitude improvement over the recently proposed one-shot solutions based on leaky-wave antennas (LWAs), in addition to having wider area coverage and less stringent bandwidth requirements.

Wireless backhaul links, already ubiquitous and expanding further with 5G and beyond, are employed for many critical functions, such as financial trading on Wall Street. In this work, we demonstrate for the first time that such links are acutely vulnerable to a new class of aerial metasurface attacks. In particular, we show how an adversary Eve designs and employs MetaFly to covertly manipulate the electromagnetic wavefront of the signals and remotely eavesdrop on highly directional backhaul links. Exploring the foundation of the attack, we demonstrate Eve’s strategy for generating eavesdropping diffraction beams by inducing pre-defined phase profiles at the aerial metasurface interface. We also show how Eve’s flight navigation approach can dynamically shape radiation patterns based on drone mobility via a wavefront-tailored flight refinement principle. We prototype MetaFly and demonstrate Eve’s lightweight, low-cost, transmissive, and power-free aerial metasurface. We implement the attack and perform a suite of over-the-air experiments in both a large indoor atrium and outdoor rooftops in a large metropolitan area. The results reveal that armed with MetaFly, Eve can intercept backhaul transmissions with nearly zero bit error rate while maintaining minimal impact on legitimate communication.

To accommodate extremely high data rates, provide high reliability, improve coverage, and meet traffic demands in future wireless communication networks, novel technologies have emerged that exploit electromagnetic waves, large multiple-antenna systems, intelligent reflective surfaces, hardware innovations, new network architectures, and higher frequency bands. Considering advances in information theory and devices, fundamental questions arise for system designers on how to develop synergies between theory and practice. Current design and analysis methods are predominantly based on scalar-quantity, far-field, planar-wavefront, monochromatic, and other non-physically consistent assumptions, which can lead to significant mismatches with systems designed based on realistic propagation models.

In this article, we investigate the real-world capability of the multi-link operation (MLO) framework—one of the key MAC-layer features included in the IEEE 802.11be amendment—by using a large dataset containing 5 GHz spectrum occupancy measurements on multiple channels. Our results show that when both available links are often busy, as is the case in ultra-dense and crowded scenarios, MLO attains the highest throughput gains over single-link operation (SLO) since it is able to leverage multiple intermittent transmission opportunities. As for latency, if the two links exhibit statistically the same level of occupancy, MLO can outperform SLO by one order of magnitude. In contrast, in asymmetrically occupied links, MLO can sometimes be detrimental and even increase latency. We study this somewhat unexpected phenomenon, and find its origins to be packets suboptimally mapped to either link before carrying out the backoff, with the latter likely to be interrupted on the busier link. We cross validate our study with real-time traffic generated by a cloud gaming application and quantify MLO’s benefits for latency-sensitive applications.

This paper presents the first security study of THz networks employing antennas with the angle-frequency coupling property. Using Leaky Wave Antennas (LWAs) as a representative, we explore the unique security properties due to the frequency-dependent radiation. We show via both analytical models and over-the-air experiments that LWA links exhibit non-uniform secrecy capacity across sub-channels, yielding advantages to an eavesdropper at edge frequencies. Yet, because different frequencies emit towards different angles, the eavesdropper is thwarted from easily intercepting an entire wideband transmission. The experiments diverge from the analytical model in that the model underpredicts the eavesdropper’s advantage at angles smaller than the target user and subsequent asymmetric performance across angles. Nonetheless, both the model and measurements show that increasingly wide bandwidth and correspondingly wide beams have only a modest marginal security penalty. Further, we find the LWA link secrecy not only depends on the target user angle (due to nonlinearity of LWA’s frequency-angle coupling), but also the beamwidth of the frequency components that constitute the collective LWA transmission.

Uplink Multi-User (MU) MIMO transmissions allow clients to simultaneously transmit independent data streams to the Access Point (AP), effectively multiplying the capacity of the wireless channel for uplink access. Due to inherent limitations of the distributed wireless networks, extra coordination is required for effective implementation of uplink MU-MIMO. Triggered uplink access (TUA) is the only mechanism that can initiate an uplink MU-MIMO transmission in Wi-Fi: it enables an access point (AP) to start simultaneous uplink multi-user (MU) transmissions. To trigger a MU uplink transmission, the AP must first contend for the channel using the enhanced distributed channel access (EDCA) and win channel access to broadcast the trigger frame in the downlink direction. At the same time, clients that have traffic buffered for uplink transmission also contend for channel access using the same EDCA method. However, the aforementioned mechanism introduces a fundamental conflict in the network. There are potentially two network entities competing for the channel for the same packet, namely, the AP contends for the channel to broadcast the trigger frame, while the clients that have traffic buffered for uplink transmission also contend for single-user (SU) channel access. Yet, while TUA MU transmission is preferable to SU uplink, one cannot disable the latter entirely. In this paper, we introduce Client-side Access Manipulation (CAM) as a mechanism to enable clients to dynamically adapt their channel access priority in order to realize an efficient uplink MU-MIMO WLAN. Through experiments in an end-to-end testbed with the TUA mechanism, an 11ax compliant network, and traffic from bursty closed-loop applications we show that CAM achieves gains in throughput and up to 65% reduction in average latency. Moreover, we show that, on the same scenarios, the aggregate throughput decreases and the average latency increases sharply with the use of the standard's defined access adaptation mechanism.

Wireless channels are vulnerable to eavesdroppers due to their broadcast nature. One approach to thwart an eavesdropper (Eve) is to decrease her SNR, e.g., by reducing the signal in her direction. Unfortunately, such methods are vulnerable to (1) a highly directional Eve that can increase her received signal strength and (2) Eve that is close to the receiver, Bob, or close to the transmitter, Alice. In this paper, we design and experimentally evaluate Multipath Multicarrier Misinformation to Adversaries (M3A), a system for Alice to send data to Bob while simultaneously sending misinformation to Eve. Our approach does not require knowledge of Eve's channel or location and, with multipath channels, randomly transforms Eve's symbols even if Eve is located one wavelength-scale distance from Bob (approximately 10 cm) or if Eve is located between Alice and Bob in their direct path (Eve is approximately 1/3 closer to Alice). In particular, our approach is to move each of Eve's received symbols (over time and across subcarriers), to an independently random transformation as compared to Bob, without Alice or Bob knowing Eve's location or channel. We realize this by modulating Alice's per-subcarrier beamforming weights with an i.i.d. random binary sequence, as if Alice had a separate antenna array for each subcarrier, and could randomly turn antennas in each array on and off. We implement M3A on a real-time Massive MIMO testbed and show that M3A can increase Eve's bit error rate more than two hundredfold compared to beamforming, even if she is positioned approximately a wavelength away, whether above, below, or beside Bob. Finally, to ensure reliability at Bob, we show that with M3A, Bob's bit error rate is approximately an order of magnitude lower than achieved with prior work.

With the large bandwidths available in the terahertz regime, directional transmissions can exhibit angular dispersion, i.e., frequency-dependent radiation direction. Unfortunately, angular dispersion introduces new security threats as increased bandwidth necessarily yields a larger signal footprint in the spatial domain and potentially benefits an eavesdropper. This paper is the first study of secure transmission strategies on angularly dispersive links. Based on information theoretic foundations, we propose a transmission strategy that channelizes the wideband transmission in frequency, and performs secure coding across frequency channels. With model-driven evaluations and over-the-air experiments, we show that the proposed method exploits the properties of angular dispersion to realize secure wideband transmissions, despite the increased signal footprint and even for practical irregular beams with side lobes and asymmetry. In contrast, without the proposed cross-channel coding strategy, angularly dispersive links can suffer from significant security degradation when bandwidth increases. In addition, we find that the security degradation due to bandwidth increment for angularly dispersive links is secondary compared to other factors including the selected secrecy rate or the directivity of the link. Nonetheless, we find that a higher angular dispersion level, i.e., a larger angular spread with the same bandwidth, results in a higher security degradation as bandwidth increases.

Today’s mmWave WLANs can realize simultaneous multi-user multi-stream transmission solely on the downlink. In this paper, we present Uplink Multi-user Beamforming on single RF chain AP (UMBRA), a novel framework for supporting multi-stream multi-user uplink transmissions via a single RF chain. We design multi-user overlayed constellations and multi-user receiver mechanisms to enable concurrent time-triggered uplink multi-user transmissions received on a single RF chain AP. We devise exemplary beam selection policies to jointly adapt beams at users and the AP for targeting aggregate rate maximization without increasing training requirements compared to single-user systems. We implement the key components of UMBRA using a programmable WLAN testbed using software-defined radios and commercial 60-GHz transceivers and collect over-the-air measurements using phased-array antennas and horn antennas with varying beamwidth. We find that in comparison to single-user transmissions, UMBRA achieves more than$1.45 \times $improvement in aggregate rate regardless of the choice of the user group, geometric separation, receiver beamwidth, and also under LOS blockage.

Will Multi-Link Operation (MLO) be able to improve the latency of Wi-Fi networks? MLO is one of the most disruptive MAC-layer techniques included in the IEEE 802.11be amendment. It allows a device to use multiple radios simultaneously and in a coordinated way, providing a new framework to improve the WLAN throughput and latency. In this paper, we investigate the potential latency benefits of MLO by using a large dataset containing 5 GHz spectrum occupancy measurements. Experimental results show that when the channels are symmetrically occupied, MLO can improve latency by one order of magnitude. In contrast, in asymmetrically occupied channels, MLO can sometimes be detrimental and increase latency. This is a result of packets being assigned to an interface before carrying out the backoff, which is more likely to be interrupted on the busier link. We overcome this issue by allowing multiple backoffs to run in parallel, assigning the packet to the particular interface where the backoff expires first, which also achieves lower latency overall.

The 802.11ax amendment introduced Triggered Uplink Access (TUA) to Wi-Fi to support uplink Multi-User (MU) MIMO. TUA coordinates simultaneous transmission of uplink users via an AP-transmitted trigger that gives an AP-selected group of users permission to transmit simultaneously for an AP-selected duration of time. Thus, TUA promises performance gains by enabling multi-user transmission and reducing contention overhead for access. In this paper, for the first time, we experimentally study the role of real application traffic on the performance of TUA. In particular, while TUA gains for fully backlogged traffic are well established, we show that bursty closed-loop traffic radically transforms performance. Using a real-time emulator, we experimentally evaluate the empirical limits of triggered uplink multi-user access with traffic from a real file transfer application and different uplink triggering strategies. Our results show that TUA significantly reduces file transfer latency compared to legacy single-user uplink, but unfortunately the standardized method for low-overhead backlog reporting leaves substantial benefits unrealized. Moreover, we show that unlike a single-user uplink, TUA has non-monotonic performance with respect to the frame aggregation limit.

The spectrum above 100 GHz has the potential to enable accurate 3D wireless localization due to the large swath of available spectrum. Yet, existing wide-band localization systems utilize the time of arrival measurements requiring strict time synchronization. In this paper, we present 123-LOC, a novel non-coherent system for one-shot dual-polarized 3D localization above 100 GHz. Our key idea is to create unique asymmetric THz fingerprints in 3D so that a wireless node can jointly infer its angular position and distance by taking hints from the measured power-spectrum profile. We introduce a dual-polarized dual-slit waveguide structure that emits out signals into free-space with a key feature that the beam pattern depends on the frequency of the signal and the geometry of the slit. To distinguish the emissions from the two slits, we use polarization diversity and manipulate the aperture geometry of the two slits so that they transmit slightly different angular-spectral signatures. Our over-the-air experiments demonstrate that 123-LOC achieves an average angle estimation error of 1° together with millimeter-scale ranging resolution, solely through non-coherent power measurements.

THz communication can realize the next order of magnitude in data rate and user densities due to the availability of wide THz-scale spectral bands. Wide bandwidth links can exhibit angular dispersion, i.e., frequency-dependent radiation direction. While angular dispersion has enabled path discovery and dynamic beam steering via frequency tuning, multi-user communication in THz links remains an unaddressed challenge. This paper presents the first study and performance evaluation of multi-user THz WLANs with angularly dispersive links. We employ a single parallel-plate Leaky-Wave Antenna (LWA) for THz directional transmission and present a multi-user communication strategy that exploits angular dispersion and angular separation of users and provides all-spectrum access to users located in different directions with the objective of aggregate rate maximization. With analytical model-driven evaluations and over-the-air experiments, we show how the multi-user performance of an angularly dispersive LWA link fundamentally depends on frequency, angle, and bandwidth utilized by users, through non-linear mechanisms. As increasing bandwidth yields a larger signal footprint in LWA links, we demonstrate that as compared to the model prediction, not only is aggregate data rate maximized with wider beams, but that the experimental link is far better even for practical irregular beams with side lobes and asymmetry. Our experiments demonstrate that by exploiting angular dispersion and users' angular separation, we can transmit without contention or medium access control up to 11 simultaneous users.

Metasurfaces enable controllable manipulation of electromagnetic waves and have been shown to improve wireless communications in many diverse ways. In this paper, we define and experimentally demonstrate for the first time a "MetaSurface-in-the-Middle'' (MSITM) attack. In this attack, the adversary Eve places a metasurface in the path of a directive transmission between Alice and Bob and targets to re-direct a portion of the signal towards herself, without being detected. In particular, we show how Eve can design a metasurface that induces abrupt phase changes at the interface of the metasurface to controllably diffract directional links and establish furtive eavesdropping links. We explore the theoretical foundations of the MSITM attack and demonstrate that an effective metasurface can be prototyped in under 5 min at the cost of several cents. We experimentally demonstrate the attack in a THz time-domain system and perform a set of over-the-air experiments. Our results indicate that the MSITM attack yields an acute vulnerability that can significantly reduce empirical secrecy capacity while leaving a minimal energy footprint, making the attack challenging to detect.

Metasurfaces enable controllable manipulation of electromagnetic waves and have been shown to improve wireless communications in many diverse ways. Investigating adversarial metasurfaces, we define and experimentally demonstrate for the first time a "MetaSurface-in-the-Middle'' (MSITM) attack in our paper \citeshaikhanov2022MSITM. In the attack, the adversary Eve places a metasurface in the path of a directive transmission between Alice and Bob and targets to re-direct a portion of the signal towards herself, without being detected. Here, we demonstrate the rapid fabrication of the MSITM employing only standard office supplies such as a printer, paper, foil, and laminator. We show that an effective metasurface can be prototyped in under $5$ min at the cost of several cents. We also demo the attack implementation in the THz network, presenting a video of the MSITM attacker establishing a diffractive eavesdropping link while maintaining the legitimate Alice-Bob link. Our results indicate that the attack yields an acute eavesdropping vulnerability while leaving a minimal energy footprint, making the attack challenging to detect.

With the large bandwidths available in the terahertz regime, directional transmissions can exhibit angular dispersion, i.e., frequency-dependent radiation direction. Unfortunately, angular dispersion introduces new security threats as increased bandwidth necessarily yields a larger signal footprint in the spatial domain and potentially benefits an eavesdropper. This paper is the first study of secure transmission strategies on angularly dispersive links. Based on information theoretic foundations, we propose to channelize the wideband transmission in frequency, and perform secure coding across frequency channels. With over-the-air experiments, we show that the proposed method exploits the properties of angular dispersion to realize secure wideband transmissions, despite the increased signal footprint and even for practical irregular beams with side lobes and asymmetry. In contrast, without the proposed cross-channel coding strategy, angularly dispersive links can suffer from significant security degradation when bandwidth increases.

We present FALCON, a novel autonomous drone network system for sensing, localizing, and approaching RF targets/sources such as smartphone devices. Potential applications of our system include disaster relief missions in which networked drones sense the Wi-Fi signal emitted from a victim’s smartphone and dynamically navigate to accurately localize and quickly approach the victim, for instance, to deliver the time-critical first-aid kits. For that we exploit Wi-Fi’s recent fine time measurement (FTM) protocol to realize the first on-drone FTM sensor network that enables accurate and dynamic ranging of targets in a mission. We propose a flight planning strategy that adapts the trajectory of the drones to concurrently favor localizing and approaching the target. Namely, our approach jointly optimizes the drones’ diversity of observations and the target approaching process, while flexibly trading off the intensities of the potentially conflicting objectives. We implement FALCON via a custom-designed multidrone platform and demonstrate up to$2\times $localization accuracy compared to a baseline flocking approach, while spending 30% less time localizing targets.

Multi-user transmission in 60 GHz Wi-Fi can achieve data rates up to 100 Gbps by multiplexing multiple user data streams. However, a fundamental limit in the approach is that each RF chain is limited to supporting one stream or one user. In this paper, we scale multi-user 60 GHz WLAN data rate by overcoming this limit and propose SIngle RF chain Multi-user BeAmforming (SIMBA), a novel framework for multi-stream multi-user downlink transmission via a single RF chain. We build on single beamformed transmission via overlayed constellations to multiplex multiple users’ modulated symbols such that grouped users at different locations can share the same transmit beam from the AP. For this, we introduce user grouping and beam selection policies that span tradeoffs in data rate, training, and computation overhead. We implement a programmable WLAN testbed using software-defined radios and commercial 60 GHz transceivers and collect over-the-air measurements for different indoor WLAN deployments using a 12-element phased antenna array as well as horn antennas with varying beamwidth. We show that in comparison to single-user transmissions, SIMBA achieves$2\times $improvement in aggregate rate and two-fold delay reduction for simultaneous transmission to four users.

Today's mmWave WLANs can realize simultaneous multi-user multi-stream transmission solely on the downlink. In this paper, we present Uplink Multi-user Beamforming on single RF chain AP (UMBRA), a novel framework for supporting multi-stream multi-user uplink transmissions via a single RF chain. We design multi-user overlayed constellations and multi-user receiver mechanisms to enable concurrent time-triggered uplink multi-user transmissions received on a single RF chain AP. We devise exemplary beam selection policies to jointly adapt beams at users and the AP for targeting aggregate rate maximization without increasing training requirements compared to single-user systems. We implement the key components of UMBRA using a programmable WLAN testbed using software-defined radios and commercial 60-GHz transceivers and collect over-the-air measurements using phased-array antennas and horn antennas with varying beamwidth. We find that in comparison to single-user transmissions, UMBRA achieves more than 1.45× improvement in aggregate rate regardless of the choice of the user group, geometric separation, and receiver beamwidth.

This paper presents uScope, an AP-side framework for validation of delay-based SLAs. Specifically, uScope enables in the estimation of WLAN uplink latency for any of the associated STAs and decomposition into its constituent components. uScope does not require any form of active probing, no special purpose software installations on the STAs, nor any additional infrastructure to collect more information, and makes estimations solely based on passive AP-side observations. We implement uScope on a commodity hardware platform and conduct extensive field trials on a university campus and in a residential apartment complex. In over 1 million tests, uScope demonstrates a high estimation accuracy with mean estimation errors under 10% for all the estimated parameters.

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.

We present the design, implementation, and experimental evaluation of ASTRO, a modular end-to-end system for distributed sensing missions with autonomous networked drones. We introduce the fundamental system architecture features that enable agnostic sensing missions on top of the ASTRO drones. We demonstrate the key principles of ASTRO by using on-board software-defined radios to find and track a mobile radio target. We show how simple distributed on-board machine learning methods can be used to find and track a mobile target, even if all drones lose contact with a ground control. Also, we show that ASTRO is able to find the target even if it is hiding under a three-ton concrete slab, representing a highly irregular propagation environment. Our findings reveal that, despite no prior training and noisy sensory measurements, ASTRO drones are able to learn the propagation environment in the scale of seconds and localize a target with a mean accuracy of 8 m. Moreover, ASTRO drones are able to track the target with relatively constant error over time, even as it moves at a speed close to the maximum drone speed.

In this paper, we present WACA, the first system to simultaneously measure all 24 Wi-Fi channels that allow channel bonding at 5 GHz with microsecond scale granularity. With WACA, we perform a first-of-its-kind measurement study in areas including urban hotspots, residential neighborhoods, universities, and even a game in Futbol Club Barcelona’s Camp Nou, a sold-out stadium with 98,000 fans and 12,000 simultaneous Wi-Fi connections. We study channel bonding in this environment, and our experimental findings reveal the underpinning factors controlling throughput gain, including channel bonding policy and spectrum occupancy statistics. We then show the significance of the gathered dataset for finding insights, which would not be possible otherwise, given that simple channel occupancy models severely underestimate the available gains. Likewise, we characterize the risks of channel bonding due to other BSS’s, including their missed transmission opportunities and potential collisions due to imperfect sensing of bonded transmissions. We explore 802.11ax which imposes constraints on bonded channels to avoid fragmentation and defines different modes that can trade implementation complexity for throughput. Lastly, we show that the stadium, while seemingly too highly occupied for channel bonding gains, has transient gaps yielding impressive gains.

Massive multiple-input and multiple-output (massive MIMO) has the potential to thwart passive eavesdropping as the signals transmitted by large antenna arrays become highly focused. Indeed, the impact of passive eavesdropping has been shown to be negligible when the base station (BS) antenna size approaches infinity for Rayleigh channels. In this paper, we experimentally explore eavesdropping in massive MIMO incorporating real-world factors including a limited BS antenna array size, potential correlation in over-the-air channels, and adaptation of modulating and coding schemes (MCS) over a discrete and finite set. Using a 96-antenna ArgosV2 BS, we first explore scaling the array size and identify eavesdropper (Eve) advantages due to channel correlation. We next identify the “MCS saturation regime” as a vulnerability even with high SNR due to limited MCS levels, and thereby demonstrating the need for power control as a counter-strategy, especially considering Eve’s advantages in the over-the-air channels. We further demonstrate Eve’s gain in optimizing her position, not only via being nomadic and searching for the most favorable position, but also via exploiting predictable line-of-sight (LoS) positional vulnerabilities. Specifically, we demonstrate Eve’s advantage by simply sharing the elevation angle with Bob in the LoS scenario. Finally, we examine how Eve’s advantage due to channel correlation scales with more eavesdropping antennas.

Multi-user transmission in 60 GHz Wi-Fi can achieve data rates up to 100 Gbps by multiplexing multiple user data streams. However, a fundamental limit in the approach is that each RF chain is limited to supporting one stream or one user. To overcome this limit, we propose SIngle RF chain Multiuser BeAmforming (SIMBA), a novel framework for multi-stream multi-user downlink transmission via a single RF chain. We build on single beamformed transmission via overlayed constellations to multiplex multiple users' modulated symbols such that grouped users at different locations can share the same transmit beam from the AP. For this, we introduce user grouping and beam selection policies that span tradeoffs in data rate, training and computation overhead. We implement a programmable WLAN testbed using software-defined radios and commercial 60-GHz transceivers and collect over-the-air measurements using phased array antennas and horn antennas with varying beamwidth. We find that in comparison to single user transmissions, SIMBA achieves 2× improvement in aggregate rate and two-fold delay reduction for simultaneous transmission to four users.

THz communication has the potential to realize an order of magnitude increase in data rates due to the availability of wide THz-scale spectral bands. Unfortunately, establishing and managing highly directional beams in THz networks is challenging as links lack the "pseudo-omni" reception capability of lower bands and the product of AP-client beam resolution is high due to narrow beams of only a few degrees. In this paper, we present One-shot Path discovEry with a THz RAinbow (OPERA), a novel system that identifies dominant paths between the AP and all clients in order to efficiently steer directional beams. The key idea is to embed path direction into the inherent characteristics of signals traveling along each path. To do so, we exploit a single leaky wave antenna and create a THz Rainbow. A THz Rainbow transmission consists of distinct signals with unique spectral characteristics across the angular domain. Leveraging the spatial-spectral signatures in the THz Rainbow, all receivers can correlate the measured signal with the known transmission signatures to discover the sender's path directions in one-shot. Our experiments demonstrate that OPERA achieves average direction estimates within 2° of ground truth for LOS and reflected paths.

Radio frequency signals have the potential to convey rich information about a node's motion and surroundings. Unfortunately, extracting such information is challenging, previously requiring accurate phase measurement, large antenna array structures, or extensive training. In this paper, we present LeakyTrack, a novel system that enables non-coherent and training-free motion sensing with a single antenna. The key idea is to create unique spectrally coded signals at different spatial directions so that geometric properties of the receiving node, as well as any potential objects in the environment, leave spectral footprints on the collected signal. To do so, we exploit a THz leaky-wave antenna and realize a color-coded scan in which signals with distinct spectral characteristics simultaneously emit across the angular domain. LeakyTrack infers nodal and environmental motion by analyzing the received spectral profile. We evaluate the performance of LeakyTrack via extensive over-the-air experiments.

Contention-based uplink radio access might lead to significant degradation in airtime efficiency and energy efficiency as the time spent “awake” by the radio is dependent on the network traffic conditions. In this paper, we design and evaluate LiSCAN, a visible light uni-directional control channel for contention-free uplink radio access. LiSCAN enables a virtual full-duplex operation by broadcasting polling frames (light-polls) across distributed LED luminaires concurrently with data reception over radio. In LiSCAN, each client consists of an additional low-power light sensor, which upon hearing a light-poll directed to it by Access Point (AP), wakes up the radio module only if there is backlogged traffic. To maximize the airtime efficiency, LiSCAN transmits light-polls successively until it detects an uplink radio transmission. LiSCAN's pipelined polling enables clients to detect failure in uplink packet reception and accordingly abort their transmissions to eliminate collisions at the AP. We simulate LiSCAN and alternate strategies in ns3 network simulator to analyze LiSCAN's performance under varying traffic conditions. Our results show that LiSCAN can provide significant improvements in the radio airtime efficiency, the sessions delivered with pre-defined service quality requirements and energy savings.

This paper presents the first security study of THz networks with Leaky Wave Antennas (LWAs). We employ a mix of analytical models and over-the-air experiments to explore the unique security properties of LWA links. We show via both models and experiments that the LWA's angle-frequency coupling leads to non-uniform secrecy capacity across sub-channels yielding advantages to an eavesdropper at edge frequencies. Yet, because different frequencies emit energy at different angles, the eavesdropper is thwarted from easily intercepting an entire wideband transmission. The experiments diverge from the analytical model in that the model underpredicts the eavesdropper's advantage at angles smaller than the target user and subsequent asymmetric performance across angles. Nonetheless, both the model and measurements show that increasingly wide bandwidth and correspondingly wide beams have only a modest marginal security penalty.

Internet speed tests assess end-to-end network performance by measuring throughput for 10s of MB of TCP uploads and downloads. While such tests provide valuable insights into network health, they are of little use to network administrators since (1) the results are only available on the client that performs the test and (2) the tests can saturate the network, increasing load and worsening performance for other clients. In this paper, we present virtual speed test, a measurement based framework that enables an AP to estimate speed test results for any of its associated clients without any special-purpose probing, with zero end-user co-operation and purely based on passively observable parameters at the AP. We implemented virtual speed test using commodity hardware, deployed it in office and residential environments, and conducted measurements spanning multiple days having different network loads and channel conditions. Overall, virtual speed test has mean estimation error less than 6% compared to ground truth speed tests, yet with zero overhead, and outcomes available at the AP.

Multi-stream 60 GHz communication can potentially achieve data rates up to 100 Gbps via multiplexing multiple data streams. Unfortunately, establishing multi-stream directional links is a high overhead procedure as the search space increases with the number of spatial streams and the product of AP-client beam resolution. In this paper, we present MUlti-stream beam-Training for mm-wavE networks (MUTE) a novel system that leverages channel sparsity, GHz-scale sampling rate, and the knowledge of mm-Wave RF codebook beam patterns to construct a set of candidate beams for efficient multi-stream beam steering. MUTE repurposes the mandatory periodic beam sweeps in 60 GHz WLANs to discover the dominant paths of the mmWave channel between the AP and any client with zero additional overhead. Coupling path estimates with beam pattern knowledge, MUTE selects a set of candidate beams that capture diverse or ideally orthogonal paths to obtain maximum stream separability. Our over-the-air experiments demonstrate that MUTE achieves 90% of the maximum achievable aggregate PHY rate while incurring only 1.2% of exhaustive search's training overhead.

In this paper, we present the first cross-layer analysis of wireless LANs operating under downlink multi-user multi-in multi-out (MU-MIMO), considering the fundamental role played by the closed-loop (TCP) traffic. In particular, we consider a scenario in which the access point transmits on the downlink via MU-MIMO, whereas stations must employ single-user transmissions on the uplink, as is the case in IEEE 802.11ac. With the help of analytical models built for different regimes that can occur in the considered system, we identify and explain crucial performance anomalies that can result in very low throughput in some scenarios, completely offsetting the theoretical gains achievable by MU-MIMO. We discuss solutions to mitigate the risk of this performance degradation and alternative uplink strategies allowing WLANs to approach their maximum theoretical capacity under MU-MIMO.

Channel state information (CSI) has been proposed to enhance physical layer security by functioning as a shared secret between a transmitter and a receiver, because it decorrelates over half wavelength distances and cannot be predicted based on locations of the transmitter and receiver in rich scattering environments. Consequently, CSI was employed to generate passwords, to authenticate the source of packets, and to inject artificial noise to thwart eavesdroppers. However, in this paper, we present CSIsnoop, and show that an attacker can infer CSI in a multi-user MIMO WLAN, even when both channel sounding sequences from the access point and CSI measurement feedback from the clients are encrypted during downlink (explicit) channel sounding, or when uplink (implicit) channel sounding is employed. The insights of CSIsnoop are that the CSI of clients can be computed based on transmit beamforming weights at the access point, and that the transmit beamforming weights can be estimated from downlink beamforming transmission. In other words, we reveal the fundamental conflict between using CSI to optimize PHY design by beamforming and ensuring the confidentiality of CSI. We implement CSIsnoop on a software defined radio and conduct experiments in various indoor environments. Our results show that on average CSIsnoop can infer CSI of the target client with an absolute normalized correlation of over 0.99, thereby urging reconsideration of the use of CSI as a tool to enhance physical layer security in multi-user MIMO WLANs.

Multi-stream 60 GHz communication has the potential to achieve data rates up to $100$ Gbps via multiplexing multiple data streams. Unfortunately, establishing multi-stream directional links can be a high overhead procedure as the search space increases with the number of spatial streams and the product of AP-client beam resolution. In this paper, we present MUlti-stream beam-Training for mm-wavE networks (MUTE) a novel system that leverages channel sparsity, GHz-scale sampling rate, and the knowledge of mm-Wave RF codebook beam patterns to construct a set of candidate beams for multi-stream beam steering. In 60 GHz WLANs, the AP establishes and maintains a directional link with every client through periodic beam training. MUTE repurposes these beam acquisition sweeps to estimate the Power Delay Profile (PDP) of each beam with zero additional overhead. Coupling PDP estimates with beam pattern knowledge, MUTE selects a set of candidate beams that capture diverse or ideally orthogonal paths to obtain maximum stream separability. Our experiments demonstrate that MUTE achieves 90% of the maximum achievable aggregate rate while incurring only 0.04% of exhaustive search's training overhead.

We present LiSteer, a novel system that steers mmWave beams at mobile devices by repurposing indicator LEDs on wireless Access Points (APs) to passively acquire direction estimates using off-the-shelf light sensors. We demonstrate that LiSteer maintains beam alignment at the narrowest beamwidth level even in case of device mobility, without incurring any training overhead at mobile devices. Our extensive evaluation on a custom dual-band hardware platform comprising highly directional horn antennas as well as practical phased antenna arrays with electronic beam steering shows that LiSteer achieves direction estimates within 2.5 degrees of ground truth on average. Moreover, it achieves beam steering accuracy of more than 97% while in tracking mode, without incurring any client beam training or feedback overhead.

We present SearchLight, a system that enables adaptive steering of highly directional 60 GHz beams via passive sensing of visible light from existing illumination sources. The key idea is to simultaneously track a mobile device's position and orientation using intensity measurements from lighting infrastructure, and to adapt client and AP beams to maintain beam alignment, without training overhead or outages in the 60 GHz band. Our implementation on custom dual-band hardware with 2 GHz wide channels and 24-element, electronically steerable phased array antennas shows that SearchLight successfully tracks client mobility and achieves up to 3× throughput gains compared to an in-band training strategy, and eliminates millisecond-scale in-band training epochs.

Accurate channel state information (CSI) is a key requirement for massive multiple-input multiple-output to achieve multi-fold increases in throughput and secrecy rate. Consequently, an adversary targeting the channel sounding process has the potential to significantly degrade performance. In this paper, we first present and model the pilot distortion attack, a simple but devastating jamming strategy in which the adversary distorts the access point's (AP's) CSI measurement of even a single client leading to denial of service for all clients associated with the AP. We then propose multiple-antenna carrier frequency offset estimate (MACE) as a countermeasure that exploits the AP's antenna array to detect jamming with zero startup cost and zero additional network overhead. Our key insight is that with multiple antennas, the AP's variance estimator of client carrier frequency offset significantly increases when there are jamming signals present. We build a test bed with a 72-antenna AP and collect over 3 000 000 over-the-air transmissions. Our results show that a single-antenna adversary jamming no more than 1/60 of the time and having no more transmit power than any client can cause over 23% reduction of achievable rate of all clients. Moreover, by setting a single detection threshold, MACE can achieve 0.97 true positive at 0.01 false positive for various client/adversary locations and for a wide range of signal-to-noise ratio (SNR) (5 ~35 dB) and signal-to-interference ratio (SIR) (-5 ~35 dB) with SNR - SIR ≥ dB.

In this paper we present the first cross-layer analysis of wireless LANs operating under downlink multi-user MIMO (MU-MIMO), considering the fundamental role played by closed-loop (TCP) traffic. In particular, we consider an 802.11ac scenario in which the access point transmits on the downlink via MU-MIMO, whereas stations must employ single-user transmissions on the uplink. With the help of analytical models built for the different regimes that can occur in the considered system, we identify and explain crucial performance anomalies that can result in very low throughput in some scenarios, completely offsetting the theoretical gains achievable by MU-MIMO. We discuss solutions to mitigate the risk of this performance degradation and alternative uplink strategies allowing WLANs to approach their maximum theoretical capacity under MU-MIMO.

We introduce X60, the first SDR-based testbed for 60 GHz WLANs, featuring fully programmable MAC/PHY/Network layers, multi-Gbps rates, and a user-configurable 12-element phased antenna array. These features provide us with an unprecedented opportunity to revisit the most important aspects of 60 GHz signal propagation and obtain new insights on performance expected from practical 60 GHz systems. X60's unique capabilities make it an ideal platform for experimentation and prototyping across layers.

Multi-user transmission at 60 GHz promises to increase the throughput of next generation WLANs via both analog and digital beamforming. To maximize capacity, analog beams need to be jointly configured with user selection and digital weights; however, joint maximization requires prohibitively large training and feedback overhead. In this paper, we scale multi-user 60 GHz WLAN throughput via design of a low-complexity structure for decoupling beam steering and user selection such that analog beam training precedes user selection. We introduce a two-class framework comprising (i) single shot selection of users by minimizing overlap of their idealized beam patterns obtained from analog training and (ii) interference-aware incremental addition of users via sequential training to better predict inter-user interference. We implement a programmable testbed using software defined radios and commercial 60 GHz transceivers and conduct over-the-air measurements to collect channel traces for different indoor WLAN deployments. Using trace based emulations and high resolution 60 GHz channel models, we show that our decoupling structure experiences less than 5% performance loss compared to maximum achievable rates via joint user-beam selection.

Channel State Information (CSI) has been proposed to enhance physical layer security between a transmitter and a receiver because it decorrelates over half wavelength distances in rich scattering environments. Consequently, CSI was employed to generate passwords, to authenticate the source of packets, and to inject artificial noise to thwart eavesdroppers. However, in this paper, we present CSIsnoop, and show that an attacker can infer CSI in a multi-user WLAN, even if both channel sounding sequences from the access point and CSI measurement feedback from the clients are encrypted. The insights of CSIsnoop are that the CSI of clients can be computed based on transmit beamforming weights at the access point, and that the transmit beamforming weights can be estimated from downlink multi-user transmission. We implement CSIsnoop on a software defined radio and conduct experiments in various indoor environments. Our results show that on average CSIsnoop can infer CSI of the target client with an absolute normalized correlation of over 0.99, thereby urging reconsideration of the use of CSI as a tool to enhance physical layer security in multi-user WLANs.

Visible Light Communication (VLC) can dual purpose energy efficient LED-based lighting infrastructure for both illumination and data communication. Unfortunately, this dual-purposing is only inherent in the downlink direction, from infrastructure illumination sources to mobile devices. In this paper, we design, analyze, and implement LiRa, a Light-Radio WLAN that fuses light and radio capabilities in an integrated system design without requiring mobile devices to emit light or infrared. We design an uplink control channel for LiRa that is Wi-Fi compliant, has a controllable impact on airtime taken from legacy Wi-Fi clients, and efficiently scales with increasing VLC user population. We implement LiRa's key components and perform extensive over-the-air experiments. While LiRa inherits uplink coverage from Wi-Fi, we demonstrate that a commercial infrared uplink is subject to deep rotational fades and outages. Finally, we show that in typical WLAN scenarios, LiRa reduces response delay up to a factor of 15 and reduces throughput degradation of legacy Wi-Fi from an excessive value of 74% to less than 3% compared to transmission of VLC feedback via 802.11 without LiRa.

While radio-based indoor localization schemes achieve decimeter-scale accuracy, they typically require precise reference measurements, multiple infrastructure nodes, or a multi-RF-chain anchor. In this paper, we propose Pseudo LATeration (PLAT), an indoor localization protocol that requires only a single RF chain infrastructure anchor and does not require prior knowledge of the environment. PLAT leverages the directionality and propagation characteristics of millimeter-wave transmissions to relax the requirement of multiple infrastructure anchors and RF chains by constructing pseudo anchors from reflected signal paths. By combining these pseudo anchors with time-of-flight measurements for distance estimation, PLAT can localize a user's device in indoors. Our evaluation reveals centimeter scale location accuracy for typical office environments. In testbed measurements and simulations, localization errors are centimeter scale for distances up to 1.5 m and beamwidths at or below 8.6 degrees. Although accuracy decreases to decimeter scale with additional propagation distance, we show that multiple reflection paths can mitigate this effect.

The 60-GHz bands target multi-gigabit rate applications, such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate scalable directional multicast (SDM) as a technique to 1) train the access point with per-beam per-client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. 2) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over-the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8 times throughput gains over exhaustive-search training and grouping.

In this paper we present the design of CHRoME, a downlink multi-user beamforming (MUBF) protocol that addresses the inherent sensitivity of multi-stream systems to mobility, inter-stream interference, and imperfect channel state information. Our contributions are: (i) a technique for accurately selecting the downlink bit rate in the presence of inter-stream interference via a custom multi-user probe and feedback signal, immediately preceding data transmission, and (ii) a fast retransmission scheme that exploits liberated antenna resources to increase the expected per-user signal-to-interference-plus-noise ratio (SINR) and retransmit without having to re-sound the channel. We implement each mechanism and evaluate via a combination of indoor over-the-air experiments and trace-driven emulation. We demonstrate that CHRoME increases the resilience of MUBF systems to inter-stream interference and achieves multi-fold throughput gains compared to IEEE 802.11ac.

High directivity of 60 GHz links introduces new link training and adaptation challenges due to both client and environmental mobility. In this paper, we design, implement and evaluate MOCA, a protocol for Mobility resilience and Overhead Constrained Adaptation for directional 60 GHz links. Since mobility-induced link blockage and misalignment cannot be countered with data rate adaptation alone, we introduce Beam Sounding as a mechanism invoked before each data transmission to estimate the link quality for selected beams, and identify and adapt to link impairments. We devise proactive techniques to restore broken directional links with low overhead and design a mechanism to jointly adapt beamwidth and data rate, targeting throughput maximization that incorporates data rate, overhead for beam alignment, and mobility resilience. We implement a programmable node and testbed using software defined radios with commercial 60 GHz transceivers, and conduct an extensive over-the-air measurement study to collect channel traces for various environments. Based on trace based emulations and the IEEE 802.11ad channel model, we evaluate MOCA under a variety of propagation environments and mobility scenarios. Our experiments show that MOCA achieves up to 2x throughput gains compared to a baseline WLAN scheme in a diverse set of operational conditions.

60 GHz bands target multi-gigabit rate applications such as high definition video streaming. Unfortunately, to provide multicast service, the strong directionality required at 60 GHz precludes serving all clients in a multicast group with a single transmission. Instead, a multicast transmission is comprised of a sequence of beam-formed transmissions (a beam group) that together cover all multicast group members. In this paper, we design, implement, and experimentally evaluate Scalable Directional Multicast (SDM) as a technique to (i) train the access point with per-beam per client RSSI measurements via partially traversing a codebook tree. The training balances the objectives of limiting overhead with collecting sufficient data to form efficient beam groups. (ii) Using the available training information, we design a scalable beam grouping algorithm that approximates the minimum multicast group data transmission time. We implement the key components of SDM and evaluate with a combination of over the-air experiments and trace-driven simulations. Our results show that the gains provided by SDM increase with group size and provide near-optimal group selection with significantly reduced training time, yielding up to 1.8x throughput gains over exhaustive-search training and grouping.

This paper proposes a new protocol called Optimal DCF (O-DCF). O-DCF modifies the rule of adapting CSMA parameters, such as backoff time and transmission length, based on a function of the demand-supply differential of link capacity captured by the local queue length. O-DCF is fully compatible with 802.11 hardware, so that it can be easily implemented only with a simple device driver update. O-DCF is inspired by the recent analytical studies proven to be optimal under assumptions, which often generates a big gap between theory and practice. O-DCF effectively bridges such a gap, which is implemented in off-the-shelf 802.11 chipset. Through extensive simulations and real experiments with a 16-node wireless network testbed, we evaluate the performance of O-DCF and show that it achieves near-optimality in terms of throughput and fairness and outperforms other competitive ones, such as 802.11 DCF, optimal CSMA, and DiffQ for various scenarios. Also, we consider the coexistence of O-DCF and 802.11 DCF and show that O-DCF fairly shares the medium with 802.11 via its parameter control.

A Multi-User MIMO (MU-MIMO) Access Point (AP) can obtain a capacity gain by simultaneously transmitting to multiple clients. This technique requires Channel State Information (CSI) at the transmitting AP to set antenna gains and phases to enable simultaneous reception through beamforming. The AP must also select both the mode (number of transmit and collective receive antennas) and the user set prior to transmission. While the ideal mode and user selection is a function of CSI, CSI must be estimated with an overhead intensive channel sounding process. We design, implement, and evaluate Pre-sounding User and Mode selection Algorithm (PUMA), a method for mode and user selection prior to channel sounding. We show that even without CSI, PUMA (i) exploits theoretical properties of MU-MIMO system scaling with respect to mode, (ii) characterizes the relative cost of each potential mode, and (iii) estimates per-stream transmission rate and aggregate throughput in each mode for a potential user set, all without CSI. Once PUMA has selected the appropriate mode and user group, the chosen protocol's channel sounding method is used on the intended user subset to carry out the transmission. We show that, on average, PUMA selects the mode and group that achieves an aggregate rate within 3% of the saturation throughput of what would have been achieved by sounding all users (which would require significant additional overhead). Moreover, we show that PUMA obtains 30% higher aggregate throughput compared to the best fixed-mode policy that uses the maximum number of available transmit and receive antennas.

Millimeter-wave communication achieves multi-Gbps data rates via highly directional beamforming to overcome pathloss and provide the desired SNR. Unfortunately, establishing communication with sufficiently narrow beamwidth to obtain the necessary link budget is a high overhead procedure in which the search space scales with device mobility and the product of the sender-receiver beam resolution. In this paper, we design, implement, and experimentally evaluate Blind Beam Steering (BBS) a novel architecture and algorithm that removes in-band overhead for directional mm-Wave link establishment. Our system architecture couples mm-Wave and legacy 2.4/5 GHz bands using out-of-band direction inference to establish (overhead-free) multi-Gbps mm-Wave communication. Further, BBS evaluates direction estimates retrieved from passively overheard 2.4/5 GHz frames to assure highest mm-Wave link quality on unobstructed direct paths. By removing in-band overhead, we leverage mm-Wave's very high throughput capabilities, beam-width scalability and provide robustness to mobility. We demonstrate that BBS achieves 97.8% accuracy estimating direction between pairing nodes using at least 5 detection band antennas. Further, BBS successfully detects unobstructed direct path conditions with an accuracy of 96.5% and reduces the IEEE 802.11ad beamforming training overhead by 81%.

Today's "white space" model of spectrum sharing applied in the UHF TV band allows channels that are not being used regionally by a TV broadcaster to be re-purposed for unlicensed-style secondary access in 24 hour increments. Unfortunately, populated areas have few unused channels for white space usage. Nonetheless, from the UHF TV viewer's perspective, Nielsen data show severe under-utilization of this spectrum, with vast regions that are in range of TV transmitters having no active TV receivers on multiple channels even at peak TV viewing times. In this paper, we present the design, implementation, and experimental evaluation of WATCH (WiFi in Active TV CHannels), the first system to enable secondary WiFi transmission even in the presence of kilowatt-scale TV transmitters, while simultaneously protecting TV receivers when they are active. To protect active TV receivers, WATCH includes a smartphone-based TV remote or an Internet-connected TV to inform the WATCH controller of TV receivers' spatial-spectral requirements. To enable WiFi transmission in UHF bands, we design WATCH-IC (Interference Cancellation) and CAT (Constructive Addition Transmission) to (i) exploit the unique environment of asynchronous WiFi transmission in the presence of a strong streaming interferer, and (ii) require no coordination with legacy TV transmitters. With FCC permission to test our implementation, we show that WATCH can provide at least 6 times the total achievable rate to 4 watt secondary devices compared to current TV white space systems, while limiting the increase in TV channel switching time to less than 5%.

Downlink Multi-User MIMO (MU-MIMO) enables the simultaneous spatial sharing of the channel by multiple users to achieve a capacity gain over Single-Input Single-Output (SISO) systems. Unfortunately, the overhead required to enable multi-user MIMO is much higher than the overhead required for single-stream systems. Namely, for K users, collection of channel state information requires K transmission exchanges (i.e., O(K)) between the AP and users. Likewise, the MU-MIMO acknowledgement process also requires the same amount of exchanges, thus reducing the performance gains attained via simultaneous downlink transmission. In this paper, we design, implement, and experimentally evaluate Concurrent Uplink Control Messages (CUiC) to scale the MU-MIMO control information exchange process and improve the efficiency of 802.11ac-based MU-MIMO networks. Our key technique is the design of new channel sounding and acknowledgement mechanisms that enable multiple users to transmit their reverse-direction control messages (i.e., beamforming reports and acknowledgments) concurrently to the AP, in O(1) transmission slots. We implement CUiC and perform an extensive set of experiments and demonstrate throughput gains of more than 100% compared to 802.11ac.

It has recently been shown that distributed queue-based adaptation of CSMA's contention aggressiveness can provably optimize network utility. However, such an approach is fragile, in that it suffers high performance degradation under conditions of asymmetric channels, heterogeneous traffic, and packet collisions. In this work, we address the main sources of performance degradation in optimal CSMA to design a distributed system for proportional-fair throughput that delivers high performance in a wide-range of network conditions. First, we generalize prior optimal CSMA models to incorporate individual per-link modulation and coding rates. With such a model, we derive adaptive principles that maximize utility under arbitrary channel capacities. Second, we propose a novel structure that can be used in the place of queues to provide optimal CSMA adaptation. As such a structure does not use traffic backlog to operate, the resulting adaptation is optimal for the set of backlogged flows under general traffic arrival patterns. Third, we propose a robustness function that reduces access attempts in high contention scenarios to avoid high performance degradation due to collisions. By evaluating our approach in combined scenarios that incorporate the three main sources of performance degradation, we observe vast performance gains, with an average 68% higher logarithmic utility compared to prior solutions.

In this paper, we propose "Virtual Duplex," a wireless architecture which, like Frequency Division Duplex (FDD), divides spectrum resources into two sub-bands. However, in contrast to FDD, both bands in Virtual Duplex are physically bidirectional, and transmissions are allocated to the bands according to whether they correspond to download or upload traffic. The "download data channel" carries data originating from the AP and that data's associated reversed-direction acknowledgements, and vice-versa for the "upload data channel." Thus, Virtual Duplex separates upload and download traffic at the link layer so that MAC layer Data-ACK handshakes are allocated into one of the two (physical) independent and asynchronous bi-directional channels. The spectrum division can be equal (as is typical with FDD) or weighted with a configurable bandwidth allocated to each channel to guarantee a spectrum share independent of client density. We show that the logical division and spectrum isolation between upload and download Data-ACK handshakes increases spectral efficiency, eliminates contention asymmetry and provides scalability to traffic asymmetry. Experimental and simulation results demonstrate that Virtual Duplex matches download vs. Upload throughput to demand ratio within 1% under any client density and traffic load. This matching capability offers unbounded download gains as congestion increases, minimizing and in some cases eliminating retransmissions and contention time.

While the UHF band exhibits superior propagation characteristics compared to other frequency bands used for broadband communications, limited spectral availability in time and space necessitates high spectral efficiency techniques such as Multi-user MIMO (MU-MIMO). In this paper we design and implement the first open MU-MIMO Software-Defined Radio (SDR) platform that operates on an order of magnitude frequency range, from 300 MHz to 5.8 GHz. We perform a comprehensive set of over-the-air experiments to evaluate the potential of UHF-band MU-MIMO in comparison to 2.4 and 5.8 GHz WiFi bands encompassing a range of operating environments. We evaluate MU-MIMO performance in both outdoor, indoor, line-of-sight (LOS), and non-line-of-sight (NLOS) environments, and demonstrate that while the temporal correlation of the measured UHF environment is increased, it does not come at the cost of increased spatial correlation as measured by the Demmel condition number, thus proving highly attractive for MU-MIMO. This evaluation demonstrates the effectiveness of MU-MIMO transmission techniques in UHF bands for high spectral efficiency and low-overhead wireless access.

We present a real-time software-defined radio (SDR) platform for prototyping and measuring the performance of broadband UHF radio networks operating over long distances with point-to-multipoint (PTMP) non-line-of-sight (NLOS) networks. Enabled by the Wideband UHF Radio Card (WURC), a custom high-power and frequency-flexible radio transceiver daughter-card for FPGA-based digital basebands, the 802.11 DCF-like MAC and PHY implementation is completely open source. We demonstrate a long-range PTMP NLOS network bonding several of the white space television channels available in Maui, Hawaii. Off-the-shelf client devices can use this network via 802.11a/g links implemented with the same SDR framework. The multi-carrier channel estimates and real-time MAC statistics of connected nodes in UHF and 2.4 GHz are recorded and displayed in real-time, demonstrating an unprecedented amount of flexibility in unlicensed frequency bands, enabling real-time TV-band cognitive networks and small-cell research deployments.

In this paper, we present the design, implementation, and evaluation of the novel downlink Multi-User MIMO sounding protocol called MUTE. Our protocol decouples the sounding set selection used to collect Channel State Information (CSI), from the transmission set selection in order to minimize or even eliminate the overhead associated with sounding, while maximizing user selection performance. To this end, MUTE exploits channel statistics to all the different users to predict whether a particular user's channel will remain sufficiently stable, thereby allowing the access point to preclude channel sounding before a MU-MIMO transmission. We show that in indoor WLANs, MUTE can reduce sounding overhead by close to 73% under certain conditions while minimizing rate performance losses due to inaccurate channel estimation.

In this paper, we design, implement, and evaluate 802.11ec (Encoded Control), an 802.11-based protocol without control messages: Instead, 802.11ec employs correlatable symbol sequences that, together with the timing the codes are transmitted, encode all control information and change the fundamental design properties of the MAC. The use of correlatable symbol sequences provides two key advantages: 1) efficiency, as it permits a near order of magnitude reduction of the control time; 2) robustness, because codes are short and easily detectable even at low signal-to-interference-plus-noise ratio (SINR) and even while a neighbor is transmitting data. We implement 802.11ec on a field programmable gate array (FPGA)-based software defined radio. We perform a large number of experiments and show that, compared to 802.11 (with and without RTS/CTS), 802.11ec achieves a vast efficiency gain in conveying control information and resolves key throughput and fairness problems in the presence of hidden terminals, asymmetric topologies, and general multihop topologies.

Virtual Multiple-Input Single-Output (vMISO) systems distribute multi-antenna diversity capabilities between a sending and a cooperating node. vMISO has the potential to vastly improve wireless link reliability and bit error rates by exploiting spatial diversity. In this paper, we present the first design and experimental evaluation of vMISO triggers (when to invoke vMISO rather than traditional transmission) in Wi-Fi networking environments. We consider the joint effect of gains obtained at the physical layer with MAC and network-scale factors and show that 802.11 MAC mechanisms represent a major bottleneck to realizing gains that can be attained by a vMISO PHY. In contrast, we show how vMISO alters node interconnectivity and coordination and therefore can vastly transform the network throughput distribution in beneficial ways that are not described merely by vMISO link gains. Moreover, we show how to avoid triggering vMISO when the increased spatial footprint of the new cooperator would excessively hinder other flows' performance. In this paper, we build the first multi-flow vMISO testbed and explore the trigger criteria that are essential to attain substantial gains in a fully integrated vMISO system. We find that the largest gains are achieved by a largely isolated flow (gains of 110%) whereas cooperator interference and contention effects are pronounced in larger topologies, limiting typical gains to 14%.

Wireless networks increasingly utilize diverse spectral bands that exhibit vast differences in both transmission range and usage. In this work, we present MAWS (Mobile Access of Wide-Spectrum Networks), the first scheme designed for mobile clients to evaluate and select both APs and spectral bands in wide-spectrum networks. Because of the potentially vast number of spectrum and AP options, scanning may be prohibitive. Consequently, our key technique is for clients to infer channel quality and spectral usage for their current location and bands using limited measurements collected in other bands and at other locations. We experimentally evaluate MAWS via a widespectrum network that we deploy, a testbed providing access to four bands at 700 MHz, 900 MHz, 2.4 GHz and 5 GHz. To the best of our knowledge, the spectrum of these bands is the widest to be spanned to date by a single operational access network. A key finding of our evaluation is that under a diverse set of operating conditions, mobile clients can accurately predict their performance without a direct measurement at their current location and spectral bands.

We present the design and implementation of ADAM, the first adaptive beamforming-based multicast system and experimental framework for indoor wireless environments. ADAM addresses the joint problem of adaptive beamformer design at the PHY layer and client scheduling at the MAC layer by proposing efficient algorithms that are amenable to practical implementation. ADAM is implemented on a field programmable gate array (FPGA) platform, and its performance is compared against that of omnidirectional and switched beamforming based multicast. Our experimental results reveal that: 1) switched multicast beamforming has limited gains in indoor multipath environments, whose deficiencies can be effectively overcome by ADAM to yield an average gain of threefold; 2) the higher the dynamic range of the discrete transmission rates employed by the MAC hardware, the higher the gains in ADAM's performance, yielding up to ninefold improvement over omni with the 802.11 rate table; and 3) finally, ADAM's performance is susceptible to channel variations due to user mobility and infrequent channel information feedback. However, we show that training ADAM's signal-to-noise ratio (SNR)-rate mapping to incorporate feedback rate and coherence time significantly increases its robustness to channel dynamics.

A class of carrier sense multiple access (CSMA) protocols used in a broad range of wireless applications uses synchronized contention where nodes periodically contend at intervals of fixed duration. While several models exist for asynchronous CSMA contention used in protocols like IEEE 802.11 MAC, no model exists for synchronized CSMA contention that also incorporates realistic factors like clock drifts. In this paper, we introduce a model that quantifies the interplay of clock drifts with contention window size, control packet size, and carrier sense regulated by usage of guard time. Using a field programmable gate array (FPGA)-based MAC protocol implementation and controlled experiments on a wireless testbed, we evaluate the model predictions on the isolated and combined impact of these key performance factors to per-flow throughput and fairness properties in both single-hop and multihop networks. Our model and experimental evaluation reveal conditions on protocol parameters under which the throughput of certain flows can exponentially decrease; while at the same time, it enables solutions that can offset such problems in a predictable manner.

We present the design and experimental evaluation of Simultaneous TRansmission with Orthogonally Blinded Eavesdroppers (STROBE). STROBE is a cross-layer approach that exploits the multi-stream capabilities of existing technologies such as 802.11n and the upcoming 802.11ac standard where multi-antenna APs can construct simultaneous data streams using Zero-Forcing Beamforming (ZFBF). Instead of using this technique for simultaneous data stream generation, STROBE utilizes ZFBF by allowing an AP to use one stream to communicate with an intended user and the remaining streams to orthogonally “blind” (actively interfere with) any potential eavesdropper thereby preventing eavesdroppers from decoding nearby transmissions. Through extensive experimental evaluation, we show that STROBE consistently outperforms Omnidirectional, Single-User Beamforming (SUBF), and directional antenna based transmission methods by keeping the transmitted signal at the intended receiver and shielded from eavesdroppers. In an indoor Wireless LAN environment, STROBE consistently serves an intended user with an SINR 15 dB greater than an eavesdropper.

We present the design and implementation of ADAM, the first adaptive beamforming based multicast system and experimental framework for indoor wireless environments. ADAM addresses the joint problem of adaptive beamformer design at the PHY layer and client scheduling at the MAC layer by proposing efficient algorithms that are amenable to practical implementation. ADAM is implemented on an FPGA platform and its performance is compared against that of omni-directional and switched beamforming based multicast. Our experimental results reveal that (i) switched multicast beamforming has limited gains in indoor multi-path environments, whose deficiencies can be effectively overcome by ADAM to yield an average gain of three-fold; (ii) the higher the dynamic range of the discrete transmission rates employed by the MAC hardware, the higher the gains in ADAM's performance, yielding upto nine-fold improvement over omni with the 802.11 rate table; and (iii) finally, ADAM's performance is susceptible to channel variations due to user mobility and infrequent channel information feedback. However, we show that training ADAM's SNR-rate mapping to incorporate feedback rate and coherence time significantly increases its robustness to channel dynamics.

We present a novel modeling approach to derive closed-form throughput expressions for CSMA networks with hidden terminals. The key modeling principle is to break the interdependence of events in a wireless network using conditional expressions that capture the effect of a specific factor each, yet preserve the required dependences when combined together. Different from existing models that use numerical aggregation techniques, our approach is the first to jointly characterize the three main critical factors affecting flow throughput (referred to as hidden terminals, information asymmetry and flow-in-the-middle) within a single analytical expression. We have developed a symbolic implementation of the model, that we use for validation against realistic simulations and experiments with real wireless hardware, observing high model accuracy in the evaluated scenarios. The derived closed-form expressions enable new analytical studies of capacity and protocol performance that would not be possible with prior models. We illustrate this through an application of network utility maximization in complex networks with collisions, hidden terminals, asymmetric interference and flow-in-the-middle instances. Despite that such problematic scenarios make utility maximization a challenging problem, the model-based optimization yields vast fairness gains and an average per-flow throughput gain higher than 500% with respect to 802.11 in the evaluated networks.

In this paper, we design, implement and evaluate 802.11ec (Encoded Control), an 802.11-based protocol without control messages: instead, 802.11ec employs correlatable symbol sequences, which together with the timing the codes are transmitted, encode all control information and change the fundamental design properties of the MAC. The use of correlatable symbol sequences provides two key advantages: (i) efficiency, as it permits a near order of magnitude reduction of the control time; (ii) robustness, because codes are short and easily detectable even at low SINR and even while a neighbor is transmitting data. We implement 802.11ec on an FPGA-based software defined radio. We perform a large number of experiments and show that, compared to 802.11 (with and without RTS/CTS), 802.11ec achieves a vast efficiency gain in conveying control information and resolves key throughput and fairness problems in the presence of hidden terminals, asymmetric topologies, and general multi-hop topologies.

The FCC ruled in September 2010 that unused UHF TV channels could be repurposed for unlicensed wireless Internet, a capability often termed "Super WiFi" because UHF bands have much greater range compared to today's GHz WiFi. Yet with so many channels used for TV in populated areas, few and sometimes none are left over in urban areas, severely hindering the capacity and market possibilities of Super WiFi in U.S. cities. Moreover, with a limited urban market hindering the cost savings of mass production, rural deployments are likewise hindered. Nonetheless, many urban areas world-wide have far greater unlicensed spectrum availability across many sub-GHz bands. In this talk, I will describe the global possibilities for UHF-band wireless networks, including specific deployment scenarios. Moreover, I will describe research, standardization, and policy challenges that must be overcome to realize urban-scale wireless networks in sub-GHz bands.

Contending flows in multihop 802.11 wireless networks compete with two fundamental asymmetries: 1) channel asymmetry, in which one flow has a stronger signal, potentially yielding physical layer capture; and 2) topological asymmetry, in which one flow has increased channel state information, potentially yielding an advantage in winning access to the channel. Prior work has considered these asymmetries independently with a highly simplified view of the other. However, in this paper, we perform thousands of measurements on coupled flows in urban environments and build a simple yet accurate model that jointly considers information and channel asymmetries. We show that if these two asymmetries are not considered jointly, throughput predictions of even two coupled flows are vastly distorted from reality when traffic characteristics are only slightly altered (e.g., changes to modulation rate, packet size, or access mechanism). These performance modes are sensitive not only to small changes in system properties, but also small-scale link fluctuations that are common in an urban mesh network. We analyze all possible capture relationships for two-flow subtopologies and show that capture of the reverse traffic can allow a previously starving flow to compete fairly. Finally, we show how to extend and apply the model in domains such as modulation rate adaptation and understanding the interaction of control and data traffic.

In 802.11 managed wireless networks, the manager can address underserved links by rate-limiting the conflicting nodes. In order to determine to what extent each conflicting node is responsible for the poor performance, the manager needs to understand the coordination among conflicting nodes' transmissions. In this paper, we present a management framework called Management, Inference, and Diagnostics using Activity Share (MIDAS). We introduce the concept of Activity Share, which characterizes the coordination among any set of network nodes in terms of the time they spend transmitting simultaneously. Unfortunately, the Activity Share cannot be locally measured by the nodes. Thus, MIDAS comprises an inference tool that, based on a combined physical, protocol, and statistical approach, infers the Activity Share by using a small set of passively collected, time-aggregate local channel measurements reported by the nodes. MIDAS uses the estimated Activity Share as the input of a simple model that predicts how limiting the transmission rate of any conflicting node would benefit the throughput of the underserved link. The model is based on the current network conditions, thus representing the first throughput model using online measurements. We implemented our tool on real hardware and deployed it on an indoor testbed. Our extensive validation combines testbed experiments and simulations. The results show that MIDAS infers the Activity Share with a mean relative error as low as 4% in testbed experiments.

By `optimal CSMA' we denote a promising approach to maximize throughput-based utility in wireless networks without message passing or synchronization among nodes. Despite the theoretical guarantees on the performance of these protocols, their evaluation in real networking scenarios has been preliminary. In this paper, we propose a methodical approach for the first comprehensive evaluation of optimal CSMA, via experimentation with a custom implementation. Example findings include; 1) hidden terminals with symmetric channels can drive the protocol to a state of extreme contention aggressiveness due to the low service received by flows. Since increasing aggressiveness does not mitigate collisions but actually aggravates them, optimal CSMA enters a positive-feedback loop eventually reaching a deadlock state of total flow starvation; 2) however, the use of RTS/CTS in such scenarios can reduce collisions to lower levels, restoring throughput and preventing an excessive contention aggressiveness by optimal CSMA flows; 3) in practical hidden terminal scenarios with physical layer capture optimal CSMA reduces the aggressiveness of dominant flows, but the contention window sizes used by such adaptation mechanism are not long enough to solve competing flows' starvation when carrier sensing fails; 4) topologies with a “flow-in-the-middle” yield starvation in traditional CSMA but fairness in optimal CSMA, because its contention aggressiveness adaptation creates frequent transmission opportunities for the central (otherwise starved) flow; 5) optimal CSMA excessively prioritizes links with low channel quality, due to queue-based control that does not otherwise incorporate channel conditions; 6) in its current design, optimal CSMA conflicts with window-based end-to-end congestion control, and leads to a efficiency-fairness tradeoff in TCP performance. This study deepens our understanding of optimal CSMA and the general adaptation philosophy behind its design, and the derived insights suggest enhancements to optimal CSMA theory.

Contending flows in multi-hop 802.11 wireless networks compete with two fundamental asymmetries: (i) channel asymmetry, in which one flow has a stronger signal, potentially yielding physical layer capture, and (ii) topological asymmetry, in which one flow has increased channel state information, potentially yielding an advantage in winning access to the channel. Prior work has considered these asymmetries independently with a highly simplified view of the other. However, in this work, we perform thousands of measurements on coupled flows in urban environments and build a simple, yet accurate model that jointly considers information and channel asymmetries. We show that if these two asymmetries are not considered jointly, throughput predictions of even two coupled flows are vastly distorted from reality when traffic characteristics are only slightly altered (e.g., changes to modulation rate, packet size, or access mechanism). These performance modes are sensitive not only to small changes in system properties, but also small-scale link fluctuations that are common in an urban mesh network. We analyze all possible capture relationships for two-flow sub-topologies and show that capture of the reverse traffic can allow a previously starving flow to compete fairly. Finally, we show how to extend and apply the model in domains such as modulation rate adaptation and understanding the interaction of control and data traffic.

IEEE 802.11-based mesh networks can yield a throughput distribution among nodes that is spatially biased, with traffic originating from nodes that directly communicate with the gateway obtaining higher throughput than all other upstream traffic. In particular, if single-hop nodes fully utilize the gateway's resources, all other nodes communicating with the same gateway will attain very little (if any) throughput. In this paper, we show that it is sufficient to rate limit the single-hop nodes in order to give transmission opportunities to all other nodes. Based on this observation, we develop a new rate limiting scheme for 802.11 mesh networks, which counters the spatial bias effect and does not require, in principle, any control overhead. Our rate control mechanism is based on three key techniques. First, we exploit the system's inherent priority nature and control the throughput of the spatially disadvantaged nodes by only controlling the transmission rate of the spatially advantaged nodes. Namely, the single-hop nodes collectively behave as a proxy controller for multi-hop nodes in order to achieve the desired bandwidth distribution. Second, we devise a rate limiting scheme that enforces a utilization threshold for advantaged single-hop traffic and guarantees a small portion of the gateway resources for the disadvantaged multi-hop traffic. We infer demand for multi-hop flow bandwidth whenever gateway resource usage exceeds this threshold, and subsequently reduce the rates of the spatially advantaged single-hop nodes. Third, since the more bandwidth the spatially disadvantaged nodes attain, the easier they can \emph{signal} their demands, we allow the bandwidth unavailable for the advantaged nodes to be elastic, i.e., the more the disadvantaged flows use the gateway resources, the higher the utilization threshold is. We develop an analytical model to study a system characterized by such priority, dynamic utilization thresholds, and control by proxy. Moreover, we use simulations to evaluate the proposed elastic rate limiting technique.

In this paper, we consider routing in multi-hop wireless mesh networks. We analyze three standardized and commonly deployed routing mechanisms that we term "node-pair discovery" primitives. We show that use of these primitives inherently yields inferior route selection, irrespective of the protocol that implements them. This behavior originates due to overhead reduction actions that systematically yield insufficient distribution of routing information, effectively hiding available paths from nodes. To address this problem, we propose a set of "deter and rescue" routing primitives that enable nodes to discover their hidden paths by exploiting already available historic routing information. We use extensive measurements on a large operational wireless mesh network to show that with node-pair discovery primitives, inferior route selections occur regularly and cause long-term throughput degradations for network users. In contrast, the deter and rescue primitives largely identify and prevent selection of inferior paths. Moreover, even when inferior paths are selected, the new primitives reduce their duration by several orders of magnitude, often to sub-second time scales.

Wireless mesh networks are popular as a cost- effective means to provide broadband connectivity to large user populations. A mesh network placement provides coverage, such that each target client location has a link to a deployed mesh node, and connectivity, such that each mesh node wirelessly connects directly to a gateway or via intermediate mesh nodes. Prior work on placement assumes wireless propagation to be uniform in all directions, i.e., an unrealistic assumption of circular communication regions. In this paper, we present approximation algorithms to solve the NP- hard mesh node placement problem for non-uniform propagation settings. The first key challenge is incorporating non-uniform propagation, which we address by formulating the problem input as a connectivity graph consisting of discrete target coverage locations and potential mesh node locations. This graph incorporates non-uniform propagation by specifying the estimated signal quality per link. Secondly, our algorithms are the first to minimize the number of deployed mesh nodes with constant-factor approximation ratio in the non-uniform propagation setting. To achieve this, we formulate the Degree-Constrained Terminal Steiner tree problem and present approximation algorithms which leverage prior results on the Steiner tree problem. Third, it is impractical to measure all possible potential mesh links, and therefore deployment planning must rely on estimations. To address this challenge, we extend our algorithm to iteratively measure the links in the solution Steiner tree, refining the graph input on a per-link basis in order to ensure the deployed network is not disconnected. Finally, we use propagation measurements at 35,000 locations in the deployed GoogleWiFi network to investigate placement in a realistic, non-uniform propagation environment. Under this measured propagation setting, our algorithms result in up to 80% fewer mesh nodes than current algorithms and only require an average of 3 measurements per deployed mesh node to ensure backhaul connectivity.

Multi-User MIMO promises to increase the spectral efficiency of next generation wireless systems and is currently being incorporated in future industry standards. Although a significant amount of research has focused on theoretical capacity analysis, little is known about the performance of such systems in practice. In this paper, we present the design and implementation of the first multi-user beamforming system and experimental framework for wireless LANs. Using extensive measurements in an indoor environment, we evaluate the impact of receiver separation distance, outdated channel information due to mobility and environmental variation, and the potential for increasing spatial reuse. For the measured indoor environment, our results reveal that two receivers achieve close to maximum performance with a minimum separation distance of a quarter of a wavelength. We also show that the required channel information update rate is dependent on environmental variation and user mobility as well as a per-link SNR requirement. Assuming that a link can tolerate an SNR decrease of 3 dB, the required channel update rate is equal to 100 and 10 ms for non-mobile receivers and mobile receivers with a pedestrian speed of 3 mph respectively. Our results also show that spatial reuse can be increased by efficiently eliminating interference at any desired location; however, this may come at the expense of a significant drop in the quality of the served users.

In 802.11 managed wireless networks, the manager can address under-served links by rate-limiting the conflicting nodes. In order to determine to what extent each conflicting node is responsible for the poor performance, the manager needs to understand the coordination among conflicting nodes' transmissions. In this paper, we present a management framework called MIDAS (Management, Inference, and Diagnostics using Activity Share). We introduce the concept of Activity Share which characterizes the coordination among any set of network nodes in terms of the time they spend transmitting simultaneously. Unfortunately, the Activity Share cannot be locally measured by the nodes. Thus, MIDAS comprises an inference tool which, based on a combined physical, protocol, and statistical approach, infers the Activity Share by using a small set of passively collected, time-aggregate local channel measurements reported by the nodes. MIDAS uses the estimated Activity Share as the input of a simple model that predicts how limiting the transmission rate of any conflicting node would benefit the throughput of the under-served link. The model is based on the current network conditions, thus representing the first throughput model using online measurements. We implemented our tool on real hardware and deployed it on an indoor testbed. Our extensive validation combines testbed experiments and simulations. The results show that MIDAS infers the Activity Share with an average normalized relative error below 12% in all testbed experiments.

Accurately selecting modulation rates for time-varying channel conditions is critical for avoiding performance degradations due to rate overselection when channel conditions degrade or underselection when channel conditions improve. In this paper, we design a custom cross-layer framework that enables: 1) implementation of multiple and previously unimplemented rate adaptation mechanisms; 2) experimental evaluation and comparison of rate adaptation protocols on controlled, repeatable channels as well as residential urban and downtown vehicular and nonmobile environments in which we accurately measure channel conditions with 100- s granularity; and 3) comparison of performance on a per-packet basis with the ideal modulation rate obtained via exhaustive experimental search. Our evaluation reveals that SNR-triggered protocols are susceptible to overselection from the ideal rate when the coherence time is low (a scenario that we show occurs in practice even in a nonmobile topology), and that “in situ” training can produce large gains to overcome this sensitivity. Another key finding is that a mechanism effective in differentiating between collision and fading losses for hidden terminals has severely imbalanced throughput sharing when competing links are even slightly heterogeneous. In general, we find trained SNR-based protocols outperform loss-based protocols in terms of the ability to track vehicular clients, accuracy within outdoor environments, and balanced sharing with heterogeneous links (even with physical layer capture).

A class of CSMA protocols used in a broad range of wireless applications uses synchronized contention where nodes periodically contend at intervals of fixed duration. While several models exist for asynchronous CSMA contention used in protocols like IEEE 802.11 MAC, no model exists for synchronized CSMA contention that also incorporates realistic factors like clock drifts. In this paper, we introduce a model that quantifies the interplay of clock drifts with contention window size, control packet size, and carrier sense regulated by usage of guard time. Using an FPGA-based MAC protocol implementation and controlled experiments on a wireless testbed we evaluate the model predictions on the isolated and combined impact of these key performance factors to per-flow throughput and fairness properties in both single-hop and multi-hop networks. Our model and experimental evaluation reveal conditions on protocol parameters under which the throughput of certain flows can exponentially decrease; while at the same time, it enables solutions that can offset such problems in a predictable manner.

Previous work has shown that CSMA-based protocols such as the IEEE 802.11 can yield flow starvation in multi-hop wireless networks. While prior protocol designs alleviated such starvation by utilizing MIMO, they require global synchronization to temporally align transmissions and require per-packet distribution of the complete channel state information. In this paper, we experimentally show that MIMO networks based on pre-802.11 n medium access, the state-of-the-art for asynchronous MIMO CSMA, worsen starvation as compared to SISO networks. Consequently, we design an asynchronous MIMO MAC protocol that counters starvation. We show that randomized and non-greedy antenna allocation coupled with local residual capacity estimation results in previously-starving nodes capturing a fair share of system resources while simultaneously exploiting throughput gains available to multi-antenna systems.

This paper addresses channel assignment and random medium access design for single-radio multi-channel mesh networks. Two prior approaches include: (i) designing MAC protocols that dynamically select channels based on local information and (ii) partitioning the mesh into subnetworks with different channels and using 802.11 as the medium access protocol. Both of these approaches suffer from limited throughput improvement; the first approach due to wrong or incomplete channel state information that inherently arises in a multi-hop wireless environment, while the second approach due to high interference within each subnetwork. In this paper, we first introduce D1C-CA, Distance-1 Constrained Channel Assignment. D1C-CA statically assigns channels to a set of links as a function of physical connectivity, contention, and the unique gateway functionality of mesh networks, i.e, all Internet (non-local) traffic has a gateway node as its source or destination. To design D1C-CA, we model the channel assignment problem as a new form of graph edge coloring in which edges at distance one are constrained. We prove that the problem is NP-complete and design an efficient heuristic solution for mesh networks. Second, we design an asynchronous control-channel-based MAC protocol that solves multi-channel coordination problems and employs the proposed channel assignment algorithm. Finally, we investigate the performance of our approach through extensive simulations and show considerable performance improvements compared to alternate schemes.

In this paper, we perform an extensive measurement study on a multi-tier mesh network serving 4,000 users. Such dense mesh deployments have high levels of interaction across heterogeneous wireless links. We find that this heterogeneous backhaul consisting of data-carrying (forwarding) linksandnon- data-carrying (non-forwarding) links creates two key effects on performance. First, we show that low-rate management and control packets can produce a disproportionally large degradation in data throughput. We define a metric for this effect called Wireless Overhead Multiplier and use it to quantify the impact of MAC and PHY mechanisms on the the throughput degradation. Surprisingly, we show that these multiplicative effects are primarily driven by the non-forwarding links where, in the worst case, data packets lose physical layer capture to the overhead, yielding disproportionate throughput degradation. Finally, we show that when data flows contend in this worst-case scenario, the loss-based autorate policy is unnecessarily triggered, causing throughput imbalance and poor network utilization.

Wireless mesh network deployments are popular as a cost-effective means to provide broadband connectivity to large user populations. As the network usage grows, network planners need to evolve an existing mesh network to provide additional capacity. In this paper, we study the problem of adding new capacity points (e.g., gateway nodes) to an existing mesh network. We first present a new technique for calculating gateway-limited fair capacity as a function of the contention at each gateway. Then, we present two online gateway placement algorithms that use local search operations to maximize the capacity gain on an existing network. A key challenge is that each gateway's capacity depends on the locations of other gateways and cannot be known in advance of determining a gateway placement. We address this challenge with two placement algorithms with different approaches to estimating the unknown gateway capacities. Our first placement algorithm, MinHopCount, is adapted from a solution to the facility location problem. MinHopCount minimizes path lengths and iteratively estimates the wireless capacity of each gateway location. Our second algorithm, MinContention, is adapted from a solution to the uncapacitated k-median problem and minimizes average contention on mesh nodes, i.e. the number of links in contention range of a mesh node and the number of routes using each link. We show that our gateway placement algorithms outperform a greedy heuristic by up to 64% on realistic topologies. For an example topology, we study the set of all possible gateway placements and find that there is large capacity gain between near-optimal and optimal placements, but the near-optimal placements found by local search are similar in configuration to the optimal.

Significant progress has been made in understanding the behavior of TCP and congestion-controlled traffic over multi- hop wireless networks. Despite these advances, however, no prior work identified severe throughput imbalances in the basic scenario of mesh networks, in which one-hop flows contend with two-hop flows for gateway access. In this paper, we demonstrate via real network measurements, test-bed experiments, and an analytical model that starvation exists in such a scenario, i.e., the one-hop flow receives most of the bandwidth while the two- hop flow starves. Our analytical model yields a solution consisting of a simple contention window policy that can be implemented via mechanisms in IEEE 802.11e. Despite its simplicity, we demonstrate through analysis, experiments, and simulations, that the policy has a powerful effect on network-wide behavior, shifting the network's queuing points, mitigating problematic MAC behavior, and ensuring that TCP flows obtain a fair share of the gateway bandwidth, irrespective of their spatial locations.

Accurately selecting modulation rates for time-varying channel conditions is critical for avoiding performance degradations due to rate overselection when channel conditions degrade or underselection when channel conditions improve. In this paper, we design a custom cross-layer framework that enables (i) implementation of multiple and previously unimplemented rate adaptation mechanisms, (ii) experimental evaluation and comparison of rate adaptation protocols on controlled, repeatable channels as well as residential urban and downtown vehicular and non-mobile environments in which we accurately measure channel conditions with 100-μs granularity, and (iii) comparison of performance on a per-packet basis with the ideal modulation rate obtained via exhaustive experimental search. Our evaluation reveals that SNR-triggered protocols are susceptible to overselection from the ideal rate when the coherence time is low (a scenario that we show occurs in practice even in a nonmobile topology), and that "in-situ" training can produce large gains to overcome this sensitivity. Another key finding is that a mechanism effective in differentiating between collision and fading losses for hidden terminals has severely imbalanced throughput sharing when competing links are even slightly heterogeneous. In general, we find trained SNR-based protocols outperform loss-based protocols in terms of the ability to track vehicular clients, accuracy within outdoor environments, and balanced sharing with heterogeneous links (even with physical layer capture).

In order to evaluate, improve, or expand a deployed, city-wide wireless mesh network, it is necessary to assess the network's spatial performance. In this paper, we present a general framework to accurately predict a network's well-served area, termed the metric region, via a small number of measurements. Assessment of deployed networks must address two key issues: non-uniform physical-layer propagation and high spatial variance in performance. Addressing non-uniformity, our framework estimates a mesh node's metric region via a data-driven sectorization of the region. We find each sector's boundary (radius) with a two-stage process of estimation and then measurement-driven "push-pull" refinement of the estimated boundary. To address high spatial variation, our coverage estimation couples signal strength measurements with terrain information from publicly available digital maps to estimate propagation characteristics between a wireless node and the client's location. To limit measurements and yield connected metric regions, we consider performance metrics (such as signal strength) to be monotonic with distance from the wireless node within each sector. We show that despite measured violations in coverage monotonicity, we obtain high accuracy with this assumption. We validate our estimation and refinement framework with measurements from 30,000 client locations obtained in each of two currently operational mesh networks, GoogleWiFi and TFA. We study three illustrative metrics: coverage, modulation rate, and redundancy, and find that to achieve a given accuracy, our framework requires two to five times fewer measurements than grid sampling strategies. Finally, we use the framework to evaluate the two deployments and study the average size and location of their coverage holes as well as the impact of client association policies on load-balancing.

Deployments of city-wide multi-hop 802.11 networks introduce challenges for maintaining client performance at vehicular speeds. We experimentally demonstrate that current network interfaces employ policies that result in long outage durations, even when clients are always in range of at least one access point. Consequently, we design and evaluate a family of client-driven handoff techniques that target vehicular mobility in multi-tier multi-hop wireless mesh networks. Our key technique is for clients to invoke an association change based on (i) joint use of channel quality measurements and AP quality scores that reflect long-term differences in AP performance and (ii) controlled measurement and hand-off time scales to balance the need for the instantaneously best association against performance penalties incurred from spurious handoffs due to channel fluctuations and marginally improved associations. We utilize a 4,000 user urban deployment to evaluate the performance of a broad class of hand-off policies.

Though the WWW has come a long way since when it was monikered the World Wide Wait, it is still not reliable during heavy workload conditions. Overloads due to sudden arrival of users (flash crowds) is known to exponentially increase download times. More recently, online banks and portals have been the target of Distributed Denial-of-Service (DDoS) attacks, which send a deluge of requests and drive away the legitimate users. These overloads pose a new set of challenges towards efficient operation at enterprises that host web content which this dissertation addresses by combining knowledge of the network as well as server performance. In particular, this dissertation proposes a web hosting architecture consisting of a grid of clusters, to provide high-performance in the presence of standard overload conditions as well as resilience during attacks. The architecture's high-performance component is provided by a server selection framework which selects the "best server" to serve a request as well as allows for an efficient multiplexing of resources across the entire cluster grid. Traditional approaches assume that minimizing network hop count minimizes client latency. In contrast, the proposed mechanism for server selection collects fine-grained server load and network latency measurements and forwards requests to the server that minimizes the total of estimated network and server delays. The architecture's DDoS- resilience is provided via a combination of anomaly detection and scheduling based mitigation of DDoS attacks. In contrast to prior work, the suspicion mechanism assigns a continuous valued vs. binary suspicion measure to each client session, and the scheduler utilizes these values to determine if and when to schedule a session's requests. Via a combination of analytical modeling and testbed experiments over an online bookstore implementation, the performance benefits achieved by the proposed cluster architecture are justified.

We address the problem of congestion control in multi-radio, multi-channel, wireless mesh networks. Compared to its single radio counterpart for which solutions exist, this problem is significantly more complex because it requires the radio channel assignments and the traffic allocations per channel be jointly optimized. We address the problem by introducing a formulation that allows its decomposition in two subproblems: A congestion control subproblem for traffic allocation to a fixed channel assignment over a node path and a discrete combinatorial channel assignment subproblem. We solve the conditional congestion control subproblem by mapping it to an optimization problem of traffic distribution to a set of radio paths. The solution provides channel congestion information that is utilized to address the channel assignment subproblem. This leads to an iterative procedure which guarantees successive increases to overall network utilization. Compared to existing work on multi- radio, multi-channel mesh networks, we show that our approach can yield significant gains both in terms of network utilization and establishing fairness.

With increasing richness in features such as personalization of content, Web applications are becoming increasingly complex and hence compute intensive. Traditional approaches for improving performance of static content Web sites have been based on the assumption that static content such as images are network intensive. However, these methods are not applicable to the dynamic content applications which are more compute intensive than static content. This paper proposes a suite of algorithms which jointly optimize the performance of dynamic content applications by reducing the client access times while also minimizing the resource utilization. A server migration algorithm allocates servers on-demand within a cluster such that the client access times are not affected even under sudden overload conditions. Further, a server selection mechanism enables statistical multiplexing of resources across clusters by redirecting requests away from overloaded clusters. We also propose a cluster decision algorithm which decides whether to migrate in additional servers at the local cluster or redirect requests remotely under different workload conditions. Through a combination of analytical modeling, trace-driven simulation over traces from large e-commerce sites and testbed implementation, we explore the performance savings achieved by the proposed algorithms.

We address the problem of identifying high throughput paths in 802.11 wireless mesh networks. We introduce an analytical model that accurately captures the 802.11 MAC protocol operation and predicts both throughput and delay of multi-hop flows under changing traffic load or routing decisions. The main idea is to characterize each link by the packet loss probability and by the fraction of busy time sensed by the link transmitter, and to capture both intra-flow and inter-flow interference. Our model reveals that the busy time fraction experienced by a node, a locally measurable quantity, is essential in finding maximum throughput paths. Furthermore, metrics that do not take this quantity into account can yield low throughput by routing over congested paths or by filtering-out non-congested paths. Based on our analytical model, we propose a novel routing metric that can be used to discover high throughput path in a congested network. Using city-wide mesh network topologies we demonstrate that our model-based metric can achieve significant performance gains with respect to existing metrics.

In this paper, we develop and analyze a low-complexity cooperative protocol that significantly increases the average throughput of multi-hop upstream transmissions for wireless tree networks. We consider a system in which transmissions are assigned to nodes in a collision free, spatial time division fashion. This protocol exploits the broadcast nature of wireless networks where the communication channel is shared between multiple adjacent nodes within interference range. For any upstream end-to-end flow in the tree, each intermediate node receives information from both one-hop and two-hop neighbors and transmits only sufficient information such that the next upstream one-hop neighbor will be able to decode the packet. This approach can be viewed as the generalization of the classical three node relay channel for end-to-end flows in which each intermediate node becomes successively source, relay and destination. We derive the achievable rate and propose an optimal schedule that realizes this rate for any regular tree network. We show that our protocol dramatically outperforms the conventional scheme where intermediate nodes simply forward the packets hop by hop. At high signal-to-noise ratio, it yields approximatively 80% throughput gain.

We introduce a low-complexity distributed slotted MAC protocol that can support all feasible arrival rates in a wireless backhaul network (WBN). For arbitrary wireless networks, such a maximum throughput protocol has been notoriously hard to realize because even if global topology information is available, the problem of computing the optimal link transmission set at each slot is NP-complete. For the logical tree structures induced by WBN traffic matrices, we first introduce a centralized algorithm that solves the optimal scheduling problem in a number of steps at most linear in the number of nodes in the network. This is achieved by discovering and exploiting a novel set of graph-theoretical properties of WBN contention graph. Guided by the centralized algorithm, we design a distributed protocol where, at the beginning of each slot, nodes coordinate and incrementally compute the optimal link transmission set. We then introduce an algorithm to compute the minimum number of steps to complete this computation, thus minimizing the per-slot overhead. Using both analysis and simulations, we show that in practice our protocol yields low overhead when implemented over existing wireless technologies and significantly outperforms existing suboptimal distributed slotted scheduling mechanisms.

We present a measurement-parameterized performance study of deployment factors in wireless mesh networks using three performance metrics: client coverage area, backhaul tier connectivity, and fair mesh capacity. For each metric, we identify and study topology factors and architectural features which strongly influence mesh performance via an extensive set of Monte Carlo simulations capturing realistic physical layer behavior. Our findings include: (i) A random topology is unsuitable for a large-scale mesh deployment due to doubled node density requirements, yet a moderate level of perturbations from ideal grid placement has a minor impact on performance. (ii) Multiple backhaul radios per mesh node is a cost-effective deployment strategy as it leads to mesh deployments costing 50% less than with a single-radio architecture, (iii) Dividing access and backhaul connections onto two separate radios does not use the second radio efficiently as it only improves fair mesh capacity 40% to 80% for most users. This is in contrast to using the second radio to move half the user population to a new network operated on the second radio. This work adds to the understanding of mesh deployment factors and their general impact on performance, providing further insight into practical mesh deployments.

In this paper, a low-complexity cooperative protocol that significantly increases the average throughput of multihop upstream transmissions for wireless tree networks is developed and analyzed. A system in which transmissions are assigned to nodes in a collision free, spatial time division fashion is considered. The suggested protocol exploits the broadcast nature of wireless networks where the communication channel is shared between multiple adjacent nodes within interference range. For any upstream end-to-end flow in the tree, each intermediate node receives information from both one-hop and two-hop neighbors and transmits only sufficient information such that the next upstream one-hop neighbor will be able to decode the packet. This approach can be viewed as the generalization of the classical three node relay channel for end-to-end flows in which each intermediate node becomes successively source, relay and destination. The achievable rate for any regular tree network is derived and an optimal schedule that realizes this rate in most cases is proposed. Our protocol is shown to dramatically outperform the conventional scheme where intermediate nodes simply forward the packets hop by hop. At high signal-to-noise ratio (SNR), it yields approximately 66% throughput gain for practical scenarios.

Multi-hop wireless networks employing random access protocols have been shown to incur large discrepancies in the throughputs achieved by the flows sharing the network. Indeed, flow throughputs can span orders of magnitude from near starvation to many times greater than the mean. In this paper, we address the foundations of this disparity. We show that the fundamental cause is not merely differences in the number of contending neighbors, but a generic coordination problem of CSMA-based random access in a multi-hop environment. We develop a new analytical model that incorporates this lack of coordination, identifies dominating and starving flows and accurately predicts per-flow throughput in a large-scale network. We then propose metrics that quantify throughput imbalances due to the MAC protocol operation. Our model and metrics provide a deeper understanding of the behavior of CSMA protocols in arbitrary topologies and can aid the design of effective protocol solutions to the starvation problem.

Countering Distributed Denial of Service (DDoS) attacks is becoming ever more challenging with the vast resources and techniques increasingly available to attackers. In this paper, we consider sophisticated attacks that are protocol-compliant, non-intrusive, and utilize legitimate application-layer requests to overwhelm system resources. We characterize application-layer resource attacks as either request flooding, asymmetric, or repeated one-shot, on the basis of the application workload parameters that they exploit. To protect servers from these attacks, we propose a counter-mechanism that consists of a suspicion assignment mechanism and a DDoS-resilient scheduler, DDoS Shield. In contrast to prior work, our suspicion mechanism assigns a continuous valued vs. binary measure to each client session, and the scheduler utilizes these values to determine if and when to schedule a session’s requests. Using testbed experiments on a web application, we demonstrate the potency of these resource attacks and evaluate the efficacy of our counter-mechanism. For instance, we effect an asymmetric attack which overwhelms the server resources, increasing the response time of legitimate clients from 0.1 seconds to 10 seconds. Under the same attack scenario, DDoS Shield limits the effects of false-negatives and false-positives and improves the victims’ performance to 0.8 seconds.

Summary form only given, as follows. Many cities are embarking on ambitious plans to cover large geographical areas with high-performance wireless access networks employing a mesh architecture. In this talk, I will describe key challenges encompassing mesh network architectures, technologies, and protocols, as well as new applications enabled by mesh. I will draw on our experiences from the deployment and operation of the Technology For All mesh network in Houston, Texas, an IEEE 802.11 network serving the low-income community.

Existing multi-channel protocols have been demonstrated to significantly increase aggregate throughput compared to single-channel protocols. However, we show that despite such improvements in aggregate throughput, existing protocols can lead to flow starvation in a multi-hop network, a phenomenon that also occurs with single-channel protocols. In this paper, we devise Asynchronous Multi-channel Coordination Protocol (AMCP), a distributed medium access protocol that not only increases aggregate throughput, but more importantly, addresses the fundamental coordination problems that lead to starvation. Based on AMCP's counter-starvation mechanisms, we analytically derive and experimentally validate an ap-proximate lower bound on the throughput of any flow in an arbitrary topology. We also demonstrate that AMCP can deliver significantly higher per-flow throughput than both IEEE 802.11 and existing multi-channel solutions. In addition to its performance properties, AMCP is both simple in that it operates using the primitives of IEEE 802.11 DCF, and cost-effective in that it requires only a single half-duplex transceiver and no infrastructure support.

Multihop wireless mesh networks can provide Internet access over a wide area with minimal infrastructure expenditure. In this work, we present a measurement driven deployment strategy and a data-driven model to study the impact of design and topology decisions on network-wide performance and cost. We perform extensive measurements in a two-tier urban scenario to characterize the propagation environment and correlate received signal strength with application layer throughput. We find that well-known estimates for pathloss produce either heavily overprovisioned networks resulting in an order of magnitude increase in cost for high pathloss estimates or completely disconnected networks for low pathloss estimates. Modeling throughput with wireless interface manufacturer specifications similarly results in severely underprovisioned networks. Further, we measure competing, multihop flow traffic matrices to empirically define achievable throughputs of fully backlogged, rate limited, and web-emulated traffic. We find that while fully backlogged flows produce starving nodes, rate-controlling flows to a fixed value yields fairness and high aggregate throughput. Likewise, transmission gaps occurring in statistically multiplexed web traffic, even under high offered load, remove starvation and yield high performance. In comparison, we find that well-known noncompeting flow models for mesh networks over-estimate network-wide throughput by a factor of 2. Finally, our placement study shows that a regular grid topology achieves up to 50 percent greater throughput than random node placement.

Since its inception in 1981, IEEE INFOCOM has been bringing together a tremendous and rich diversity of authors from universities, government and industry. The popularity of INFOCOM as the premier forum for networking research continues to grow. We are very proud of the final INFOCOM 2005 program, which includes 61 high-quality regular paper sessions, 3 panels on both timely and challenging issues in networking, 8 instructive tutorials and two inspiring keynote speeches. This year, 1419 papers from 44 different countries were submitted to INFOCOM. The submitted papers cover virtually all aspects of networking research. The paper selection was handled by an outstanding Technical Program Committee. Each paper was rigorously reviewed by at least three Technical Program Committee members, although some papers received as many as five written reviews. Based on the referees' comments and ratings, the Technical Program Committee Co-Chairs made a preliminary cut, accepting 110 ("clear accept") of the top papers and rejecting 909 ("clear reject"). The remaining 400, having mixed reviews, were discussed at our TPC meeting at Rice University in Houston on October 16. We had an excellent TPC meeting with high attendance (100+) and a hard-working group. 18 Specialist groups ofTPC members were constituted, each responsible for the decision for approximately 22 papers. 134 more papers were accepted at the TPC meeting. Thus, 244 papers were accepted all together by the TPC, which translates into an acceptance rate of 17%. The accepted papers were chosen through a highly competitive but fair process and are truly representative of the state-of-the-art in networking research.

In this paper, we decompose a large- or small-scale multi-hop wireless network into embedded subgraphs, each consisting of four nodes and two flow pairs. We systematically study all twelve possible topologies that arise according to whether the different nodes are in radio range of each other. We show that under both a random spatial distribution of nodes and random waypoint mobility with shortest-path routing, a critical and highly probable scenario is a class in which the channel state shared by the two flows is not only incomplete (i.e., the graph is not fully connected), but there is also asymmetry in the state between the two flows. We develop an accurate analytical model validated by simulations to characterize the long-term unfairness that naturally arises when CSMA with two- or four-way handshake is employed as a random access protocol. Moreover, we show that another key class of topologies consists of incomplete but symmetric shared state. We show via modeling and simulations that in this case, the system achieves long-term fairness, yet endures significant durations in which one flow dominates channel access with many repeated transmissions before relinquishing the channel. The model predicts the time-scales of this unfairness as a function of system parameters such as the maximum retransmission limit.

Peer-to-peer (p2p) file sharing systems are characterized by highly replicated content distributed among nodes with enormous aggregate resources for storage and communication. These properties alone are not sufficient, however, to render p2p networks immune to denial-of-service (DoS) attack. In this paper, we study, by means of analytical modeling and simulation, the resilience of p2p file sharing systems against DoS attacks, in which malicious nodes respond to queries with erroneous responses. We consider the file-targeted attacks in current use in the Internet, and we introduce a new class of p2p-network-targeted attacks.In file-targeted attacks, the attacker puts a large number of corrupted versions of a single file on the network. We demonstrate that the effectiveness of these attacks is highly dependent on the clients' behavior. For the attacks to succeed over the long term, clients must be unwilling to share files, slow in removing corrupted files from their machines, and quick to give up downloading when the system is under attack.In network-targeted attacks, attackers respond to queries for any file with erroneous information. Our results indicate that these attacks are highly scalable: increasing the number of malicious nodes yields a hyperexponential decrease in system goodput, and a moderate number of attackers suffices to cause a near-collapse of the entire system. The key factors inducing this vulnerability are (i) hierarchical topologies with misbehaving "supernodes," (ii) high path-length networks in which attackers have increased opportunity to falsify control information, and (iii) power-law networks in which attackers insert themselves into high-degree points in the graph.Finally, we consider the effects of client counter-strategies such as randomized reply selection, redundant and parallel download, and reputation systems. Some counter-strategies (e.g., randomized reply selection) provide considerable immunity to attack (reducing the scaling from hyperexponential to linear), yet significantly hurt performance in the absence of an attack. Other counter-strategies yield little benefit (or penalty). In particular, reputation systems show little impact unless they operate with near perfection.

Inter-server coordinated scheduling is a mechanism for downstream nodes to increase or decrease a packet's priority according to the congestion incurred at upstream nodes. In this paper, we derive an end-to-end schedulability condition for a broad class of coordinated schedulers that includes Core-stateless Jitter Virtual Clock (CJVC) and Coordinated Earliest Deadline First (CEDF). In contrast to previous approaches, our technique purposely allows flows to violate their local priority indexes while still providing an end-to-end delay bound. We show that under a simple priority assignment scheme, coordinated schedulers can outperform WFQ schedulers, while replacing per-flow scheduling operations with a simple coordination rule. Finally, we illustrate the performance advantages of coordination through numerical examples and simulation experiments.

The IEEE 802.11 wireless media standard supports multiple frequency channels as well as multiple data rates at the physical (PHY) layer. In this paper, we introduce the multi-channel opportunistic auto rate (MOAR), an enhanced MAC protocol for multi-channel and multi-rate IEEE 802.11 enabled wireless ad hoc networks to opportunistically exploit the presence of frequency diversity (in the form of multiple frequency channels). The key mechanism of MOAR is that if the signal to noise ratio on the current channel is not favorable, mobile nodes can opportunistically skip to better quality frequency channels enabling data transmission at a higher rate. As channel separation for IEEE 802.11 is greater than the coherence bandwidth, different channels experience independent fading and hence there is a high probability that the skipping nodes will find better channel conditions on one of the other frequency channels. Each skip comes at the cost of resources spent in channel measurement since channel quality of different channels is not known a priori. Consequently, we devise an optimal skipping rule for MOAR which maps the channel conditions at the PHY layer to a MAC rule which allows each node to determine its optimum number of skips based on average channel conditions. Finally, we perform an extensive set of ns-2 simulations to evaluate the performance of MOAR and the impact of such factors as location distribution, channel conditions and error in channel measurements on the throughput gains offered by MOAR.

Receiver-driven TCP protocols delegate key congestion control functions to receivers. Their goal is to exploit information available only at receivers in order to improve latency and throughput in diverse scenarios ranging from wireless access links to wireline and wireless Web browsing. Unfortunately, in contrast to today's sender-driven protocols, receiver-driven congestion control introduces an incentive for misbehavior. Namely, the primary beneficiary of a flow (the receiver of data) has both the means and incentive to manipulate the congestion control algorithm in order to obtain higher throughput or reduced latency. We study the deployability of receiver-driven TCP in environments with untrusted receivers which may tamper with the congestion control algorithm for their own benefit. Using analytical modeling and extensive simulation experiments, we show that deployment of receiver-driven TCP must strike a balance between enforcement mechanisms, which can limit performance, and complete trust of end-points, which results in vulnerability to cheaters and even DoS attackers.

Multipath routing enables a network's traffic to be split among two or more possibly disjoint paths in order to reduce latency, improve throughput, and balance traffic loads. Yet, once the control plane establishes multiple routes, a policy is needed for efficiently splitting traffic among the selected paths. In this paper, we introduce opportunistic multipath scheduling (OMS), a technique for exploiting short term variations in path quality to minimize delay, while simultaneously ensuring that the splitting rules dictated by the routing protocol are satisfied. In particular, OMS uses measured path conditions on time scales of up to several seconds to opportunistically favor low-latency high-throughput paths. Consequently, OMS ensures that over longer time scales relevant for traffic management policies, traffic is split according to the ratios determined by the routing protocol. We develop a model of OMS and derive an asymptotic lower bound on the performance of OMS as a function of path conditions (mean, variance, and Hurst parameter) for self-similar traffic. An example finding from the model is that long-time-scale traffic fluctuations represented by a larger Hurst parameter improve the performance gain of OMS vs. round-robin scheduling, even under paths that are statistically identical. Finally, we use an extensive simulation-based performance study to evaluate the accuracy of the analytical model, explore the impact of OMS on TCP throughput, and study the impact of factors such as delayed measurements

Traditional approaches to mirroring, caching, and content distribution have an underlying assumption that minimizing network hop count minimizes client latency. However, with uncongested backbones and potentially high-latency service times for dynamic content, such techniques are of limited effectiveness. We present an architecture in which dispatchers at an overloaded Internet data center (IDC) redirect requests for dynamic content to a geographically remote but less loaded IDC. We show with both analytical modeling as well as testbed experiments that the delay savings of redirecting requests to a lightly loaded IDC can far outweigh the overhead in interIDC network latency. Consequently, client end-to-end delays are significantly reduced without requiring modifications to clients, servers, or DNS.

Significant progress has been made towards making ad hoc networks secure and DoS resilient. However, little attention has been focused on quantifying DoS resilience: Do ad hoc networks have sufficiently redundant paths and counter-DoS mechanisms to make DoS attacks largely ineffective? Or are there attack and system factors that can lead to devastating effects? In this paper, we design and study DoS attacks in order to assess the damage that difficult-to-detect attackers can cause. The first attack we study, called the JellyFish attack, is targeted against closed-loop flows such as TCP; although protocol compliant, it has devastating effects. The second is the Black Hole attack, which has effects similar to the JellyFish, but on open-loop flows. We quantify via simulations and analytical modeling the scalability of DoS attacks as a function of key performance parameters such as mobility, system size, node density, and counter-DoS strategy. One perhaps surprising result is that such DoS attacks can increase the capacity of ad hoc networks, as they starve multi-hop flows and only allow one-hop communication, a capacity-maximizing, yet clearly undesirable situation.

Wireless IEEE 802.11 networks in residences, small businesses, and public "hot spots" typically encounter the wireline access link (DSL, cable modem, T1, etc.) as the slowest and most expensive part of the end-to-end path. Consequently, network architectures have been proposed that employ multiple wireless hops in route to and from the wired Internet. Unfortunately, use of current media access and transport protocols for such systems can result in severe unfairness and even starvation for flows that are an increasing number of hops away from a wired Internet entry point. Our objective is to study fairness and end-to-end performance in multihop wireless backhaul networks via the following methodology. First, we develop a formal reference model that characterizes objectives such as removing spatial bias (i.e., providing performance that is independent of the number of wireless hops to a wire) and maximizing spatial reuse. Second, we perform an extensive set of simulation experiments to quantify the impact of the key performance factors towards achieving these goals. For example, we study the roles of the MAC protocol, end-to-end congestion control, antenna technology, and traffic types. Next, we develop and study a distributed layer 2 fairness algorithm which targets to achieve the fairness of the reference model without modification to TCP. Finally, we study the critical relationship between fairness and aggregate throughput and in particular study the fairness-constrained system capacity of multihop wireless backhaul networks.

The Resilient Packet Ring (RPR) IEEE 802.17 standard is a new technology for high-speed backbone metropolitan area networks. A key performance objective of RPR is to simultaneously achieve high utilization, spatial reuse, and fairness, an objective not achieved by current technologies such as SONET and Gigabit Ethernet nor by legacy ring technologies such as FDDI. The core technical challenge for RPR is the design of a bandwidth allocation algorithm that dynamically achieves these three properties. The difficulty is in the distributed nature of the problem, that upstream ring nodes must inject traffic at a rate according to congestion and fairness criteria downstream. Unfortunately, we show that under unbalanced and constant-rate traffic inputs, the RPR fairness algorithm suffers from severe and permanent oscillations spanning nearly the entire range of the link capacity. Such oscillations hinder spatial reuse, decrease throughput, and increase delay jitter. In this paper, we introduce a new dynamic bandwidth allocation algorithm called Distributed Virtual-time Scheduling in Rings (DVSR). The key idea is for nodes to compute a simple lower bound of temporally and spatially aggregated virtual time using per-ingress counters of packet (byte) arrivals. We show that with this information propagated along the ring, each node can remotely approximate the ideal fair rate for its own traffic at each downstream link. Hence, DVSR flows rapidly converge to their ring-wide fair rates while maximizing spatial reuse. To evaluate DVSR, we develop an idealized fairness reference model and bound the deviation in service between DVSR and the reference model, thereby bounding the unfairness. With simulations, we find that compared to current techniques, DVSR's convergence times are an order of magnitude faster (e.g., 2 versus 50 ms), oscillations are mitigated (e.g., ranges of 0.1% versus up to 100%), and nearly complete spatial reuse is achieved (e.g., 0.1% throughput loss versus 33%). Finally, we provide a proof-of-concept implementation of DVSR on a 1 Gb/s network processor testbed and report the results of testbed measurements.

Service prioritization among different traffic classes is an important goal for the future Internet. Conventional approaches to solving this problem consider the existing best-effort class as the low-priority class, and attempt to develop mechanisms that provide "better-than-best-effort" service. In this paper, we explore the opposite approach, and devise a new distributed algorithm to realize a low-priority service (as compared to the existing best effort) from the network endpoints. To this end, we develop TCP Low Priority (TCP-LP), a distributed algorithm whose goal is to utilize only the excess network bandwidth as compared to the "fair share" of bandwidth as targeted by TCP. The key mechanisms unique to TCP-LP congestion control are the use of one-way packet delays for congestion indications and a TCP-transparent congestion avoidance policy. Our simulation results show that: (1) TCP-LP is largely non-intrusive to TCP traffic; (2) both single and aggregate TCP-LP flows are able to successfully utilize excess network bandwidth; moreover, multiple TCP-LP flows share excess bandwidth fairly; (3) substantial amounts of excess bandwidth are available to low-priority class, even in the presence of "greedy" TCP flows; (4) the response times of web connections in the best-effort class decrease by up to 90% when long-lived bulk data transfers use TCP-LP rather than TCP.

Emerging spread spectrum high-speed data networks utilize multiple channels via orthogonal codes or frequency-hopping patterns such that multiple users can transmit concurrently. In this paper, we develop a framework for opportunistic scheduling over multiple wireless channels. With a realistic channel model, any subset of users can be selected for data transmission at any time, albeit with different throughputs and system resource requirements. We first transform selection of the best users and rates from a complex general optimization problem into a decoupled and tractable formulation: a multiuser scheduling problem that maximizes total system throughput and a control-update problem that ensures long-term deterministic or probabilistic fairness constraints. We then design and evaluate practical schedulers that approximate these objectives.

Denial of Service attacks are presenting an increasing threat to the global inter-networking infrastructure. While TCP's congestion control algorithm is highly robust to diverse network conditions, its implicit assumption of end-system cooperation results in a well-known vulnerability to attack by high-rate non-responsive flows. In this paper, we investigate a class of low-rate denial of service attacks which, unlike high-rate attacks, are difficult for routers and counter-DoS mechanisms to detect. Using a combination of analytical modeling, simulations, and Internet experiments, we show that maliciously chosen low-rate DoS traffic patterns that exploit TCP's retransmission time-out mechanism can throttle TCP flows to a small fraction of their ideal rate while eluding detection. Moreover, as such attacks exploit protocol homogeneity, we study fundamental limits of the ability of a class of randomized time-out mechanisms to thwart such low-rate DoS attacks.

The IETF's integrated services (IntServ) architecture, together with reservation aggregation, provides a mechanism to support the quality-of-service demands of real-time flows in a scalable way, i.e., without requiring that each router be signaled with the arrival or departure of each new flow for which it forwards data. However, reserving resources in "bulk" implies that the reservation does not precisely match the true demand. Consequently, if the flows' demanded bandwidth varies rapidly and dramatically, aggregation can incur significant performance penalties of under-utilization and unnecessarily rejected flows. On the other hand, if demand varies moderately and at slower time scales, aggregation can provide an accurate and scalable approximation to IntServ. We develop a simple analytical model and perform extensive trace-driven simulations to explore the effectiveness of aggregation under a broad class of factors. Example findings include: 1) a simple single-time-scale model with random noise can capture the essential behavior of surprisingly complex scenarios; 2) with a two-order-of-magnitude separation between the dominant time scale of demand and the time scale of signaling and moderate levels of secondary noise, aggregation achieves a performance that closely approximates that of IntServ.

Two recent advances have resulted in significant improvements in Web server quality-of-service. First, both centralized and distributed Web servers can provide isolation among service classes by fairly distributing system resources. Second, session admission control can protect classes from performance degradation due to overload. The goal of this work is to design a general "front-end" algorithm that uses these two building blocks to support a new Web service model, namely, multiclass services which control response latencies to within prespecified targets. Our key technique is to devise a general service abstraction to adaptively control not only the latency of a particular class, but also to bound the interclass relationships. In this way, we capture the extent to which classes are isolated or share system resources (as determined by the server architecture and system internals) and hence their effects on each other's QoS. For example, if the server provides class isolation (i.e., a minimum fraction of system resources independent of other classes), yet also allows a class to utilize unused resources from other classes, the algorithm infers and exploits this behavior, without an explicit low level model of the server. Thus, as new functionalities are incorporated into Web servers, the approach naturally exploits their properties to efficiently satisfy the classes' performance targets. We validate the scheme with trace driven simulations.

Quality-of-service mechanisms and differentiated service classes are increasingly available in networks and Web servers. While network and Web server clients can assess their service by measuring basic performance parameters such as packet loss and delay, such measurements do not expose the system's core QoS functionality such as multiclass service discipline. In this paper, we develop a framework and methodology for enabling network and Web server clients to assess system's multiclass mechanisms and parameters. Using hypothesis testing, maximum likelihood estimation, and empirical arrival and service rates measured across multiple time scales, we devise techniques for clients to: 1) determine the most likely service discipline among earliest deadline first, class-based weighted fair queuing, and strict priority; 2) estimate the system's parameters with high confidence; and (3) detect and parameterize non work-conserving elements such as rate limiters. We describe the important role of time scales in such a framework and identify the conditions necessary for obtaining accurate and high confidence inferences.

We present wireless credit-based fair queuing (WCFQ), a new scheduler for wireless packet networks with provable statistical short- and long-term fairness guarantees. WCFQ exploits the fact that users contending for the wireless medium will have different "costs" of transmission depending on their current channel condition. For example, in systems with variable coding, a user with a high-quality channel can exploit its low-cost channel and transmit at a higher data rate. Similarly, a user in a code-division multiple access system with a high-quality channel can use a lower transmission power. Thus, WCFQ provides a mechanism to exploit inherent variations in channel conditions and select low-cost users in order to increase the system's overall performance (e.g., total throughput). However, opportunistic selection of the best user must be balanced with fairness considerations. In WCFQ, we use a credit abstraction and a general "cost function" to address these conflicting objectives. This provides system operators with the flexibility to achieve a range of performance behaviors between perfect fairness of temporal access independent of channel conditions and purely opportunistic scheduling of the best user without consideration of fairness. To quantify the system's fairness characteristics within this range, we develop an analytical model that provides a statistical fairness bound in terms of the cost function and the statistical properties of the channel. An extensive set of simulations indicate that the scheme is able to achieve significant throughput gains while balancing temporal fairness constraints.

The IEEE 802.11 wireless media access standard supports multiple data rates at the physical layer. Moreover, various auto rate adaptation mechanisms at the medium access layer have been proposed to utilize this multi-rate capability by automatically adapting the transmission rate to best match the channel conditions. In this paper, we introduce the Opportunistic Auto Rate (OAR) protocol to better exploit durations of high-quality channels conditions. The key mechanism of the OAR protocol is to opportunistically send multiple back-to-back data packets whenever the channel quality is good. As channel coherence times typically exceed multiple packet transmission times for both mobile and non-mobile users, OAR achieves significant throughput gains as compared to state-of-the-art auto-rate adaptation mechanisms. Moreover, over longer time scales, OAR ensures that all nodes are granted channel access for the same time-shares as achieved by single-rate IEEE 802.11. We describe mechanisms to implement OAR on top of any existing auto-rate adaptation scheme in a nearly IEEE 802.11 compliant manner. We also analytically study OAR and characterize the gains in throughput as a function of the channel conditions. Finally, we perform an extensive set of ns-2 simulations to study the impact of such factors as node velocity, channel conditions, and topology on the throughput of OAR.

Wireless emph ad hoc networks based on the IEEE 802.11 protocol can incur severe unfairness even in simple topologies. In particular, two topological properties that we define in a graph-theoretic framework and refer to as information asymmetry and perceived collisions result in significant performance degradations and unfairness. In this paper, we present the design and analysis of Distributed Wireless Ordering Protocol (DWOP), a distributed scheduling and media access algorithm targeted towards ensuring that packets access the medium in an order defined by an ideal reference scheduler such as FIFO, Virtual Clock, or Earliest Deadline First. In this way, DWOP enables QoS differentiation as well as fairness when combined with TCP. Our key technique is piggybacking head-of-line packet priorities in IEEE 802.11 control messages so that nodes can assess the relative priority of their own queued packets. With a graph-theoretic problem formulation, we design DWOP to achieve the exact reference ordering in fully connected graphs, and to have well-characterized deviations from the reference order in more complex topologies. A simple theoretical model indicates that the scheme attains rapid convergence for newly arriving nodes, and extensive simulations indicate that nearly exact reference ordering can be achieved, even in complex asymmetric and perceived collision topologies.

In multihop networks, packet schedulers at downstream nodes have an opportunity to make up for excessive latencies due to congestion at upstream nodes. Similarly, when packets incur low delays at upstream nodes, downstream nodes can reduce priority and schedule other packets first. The goal of this paper is to define a framework for design and analysis of coordinated multihop scheduling (CMS) which exploits such internode coordination. We first provide a general CMS definition which enables us to classify a number of schedulers from the literature, including G-EDF, FIFO+, CEDF, and work-conserving CJVC as examples of CMS schedulers. We then develop a distributed theory of traffic envelopes which enables us to derive end-to-end statistical admission control conditions for CMS schedulers. We show that CMS schedulers are able to limit traffic distortion to within a narrow range resulting in improved end-to-end performance and more efficient resource utilization. Consequently, our technique exploits statistical resource sharing among flows, classes, and nodes, and our results provide the first statistical multinode multiclass admission control algorithm for networks of work conserving servers.

Quality of service mechanisms and differentiated service classes are increasingly available in networks and servers. While network clients can assess their service by measuring basic performance parameters such as packet loss and delay, such measurements do not expose the network's core QoS functionality. We develop a framework and methodology for enabling network clients to assess a system's multi-class mechanisms and parameters. Using hypothesis testing, maximum likelihood estimation, and empirical arrival and service rates measured across multiple time scales, we devise techniques for clients to (1) determine the most likely service discipline among EDF, WFQ, and SP, (2) estimate the server's parameters with high confidence, and (3) detect and parameterize non-work-conserving elements such as rate limiters. We describe the important role of time scales in such a framework and identify the conditions necessary for obtaining accurate and high confidence inferences.

Providing quality of service in random access multi-hop wireless networks requires support from both medium access and packet scheduling algorithms. However, due to the distributed nature of ad hoc networks, nodes may not be able to determine the next packet that would be transmitted in a (hypothetical) centralized and ideal dynamic priority scheduler. In this paper, we develop two mechanisms for QoS communication in multi-hop wireless networks. First, we devise distributed priority scheduling a technique that piggybacks the priority tag of a node's head-of-line packet onto handshake and data packets; e.g., RTS/DATA packets in IEEE 802.11. By monitoring transmitted packets, each node maintains a scheduling table which is used to assess the node's priority level relative to other nodes. We then incorporate this scheduling table into existing IEEE 802.11 priority back-off schemes to approximate the idealized schedule. Second, we observe that congestion, link errors, and the random nature of medium access prohibit an exact realization of the ideal schedule. Consequently, we devise a scheduling scheme termedmulti-hop coordinationso that downstream nodes can increase a packet's relative priority to make up for excessive delays incurred upstream. We next develop a simple analytical model to quantitatively explore these two mechanisms. In the former case, we study the impact of the probability of overhearing another packet's priority index on the scheme's ability to achieve the ideal schedule. In the latter case, we explore the role of multi-hop coordination in increasing the probability that a packet satisfies its end-to-end QoS target. Finally, we perform a set of ns-2 simulations to study the scheme's performance under more realistic conditions.

Allocating resources for multimedia traffic flows with real-time performance requirements is an important challenge for future packet networks. However, in large-scale networks, individually managing each traffic flow on each of its traversed routers has fundamental scalability limitations, in both the control plane's requirements for signaling, state management, and admission control, and the data plane's requirements for per-flow scheduling mechanisms. In this paper, we develop a scalable architecture and algorithm for quality-of-service management termed egress admission control. In our approach, resource management and admission control are performed only at egress routers, without any coordination among backbone nodes or per-flow management. Our key technique is to develop a framework for admission control under a general "black box" model, which allows for cross traffic that cannot be directly measured, and scheduling policies that may be ill-described across many network nodes. By monitoring and controlling egress routers' class-based arrival and service envelopes, we show how network services can be provisioned via scalable control at the network edge. We illustrate the performance of our approach with a set of simulation experiments using highly bursty traffic flows and find that despite our use of distributed admission control, our approach is able to accurately control the system's admissible region under a wide range of conditions.

The goal of admission control is to support the quality-of-service demands of real-time applications via resource reservation. We introduce a new approach to measurement-based admission control for multiclass networks with link sharing. We employ adaptive and measurement-based maximal rate envelopes of the aggregate traffic flow to provide a general and accurate traffic characterization that captures its temporal correlation as well as the available statistical multiplexing gain. In estimating the applications' future performance, we introduce the notion of a schedulability confidence level which describes the uncertainty of the measurement-based "prediction" and reflects temporal variations in the measured envelope. We then devise techniques to control loss probability for a buffered multiplexer servicing heterogeneous and bursty traffic flows, even in the regime of a moderate number of traffic flows, which is important in link-sharing environments. Finally, we have developed an implementation of the scheme on a prototype router and performed a testbed measurement study, which together with extensive trace-driven simulations illustrates the effectiveness of the approach in practical scenarios.

In multi-hop networks, packet schedulers at downstream nodes have an opportunity to make up for excessive latencies due to congestion at upstream nodes. Similarly when packets incur low delays at upstream nodes, downs stream nodes can reduce priority and schedule other packets first. The goal of this paper is to define a framework for design and analysis of coordinated network scheduling (CNS) which exploit such inter-node coordination. The first provide a general CNS definition which enables us to classify a number of schedulers from the literature including, FIFO+, CEDF and work-conserving CJVC as examples of CNS schedulers. We then develop a distributed theory of traffic envelopes which enables us to derive end-to-end statistical admission control conditions for CNS schedulers. We show that CNS schedulers are able to limit traffic distortion to within a narrow range resulting in improved end-to-end performance and more efficient resource utilization.

Provisioning multiple service classes with different performance characteristics (e.g., throughput and delay) is an important challenge for future packet networks. However, in large-scale networks, individually managing each traffic flow on each of its traversed routers has fundamental scalability limitations, in both the control plane's requirements for signaling, state management, and admission control, and the data plane's requirements for per-flow scheduling mechanisms. In this paper, we develop a scalable technique for quality-of-service management termed egress admission control. In our approach, resource management and admission control are performed only at egress routers, without any coordination among backbone nodes or per-flow management. Our key technique is to develop a framework for admission control under a general "black box" model, which allows for cross traffic that cannot be directly measured, and scheduling policies that may be ill-described across many network nodes. By monitoring and controlling egress routers' class-based arrival and service envelopes, we show how network services can be provisioned via scalable control at the network edge. We illustrate the performance of our approach with a set of simulation experiments using highly bursty traffic flows and find that despite our use of coarse-grained system control, our approach is able to accurately control the system's admissible region under a wide range of conditions.

The traditional approach to implementing admission control, as exemplified by the Integrated Services proposal in the IETF, uses a signalling protocol to establish reservations at all routers along the path. While providing excellent quality-of-service, this approach has limited scalability because it requires routers to keep per-flow state and to process per-flow reservation messages. In an attempt to implement admission control without these scalability problems, several recent papers have proposed various forms of endpoint admission control. In these designs, the hosts (the endpoints) probe the network to detect the level of congestion; the host admits the flow only if the detected level of congestion is sufficiently low. This paper is devoted to the study of endpoint admission control. We first consider several architectural issues that guide (and constrain) the design of such systems. We then use simulations to evaluate the performance of endpoint admission control in various settings. The modest performance degradation between traditional router-based admission control and endpoint admission control suggests that a real-time service based on endpoint probing may be viable.

Supporting quality of service (QoS) guarantees in wireless networks requires that admission control algorithms incorporate user mobility, and limit the probability that sufficient resources are unavailable when a user must handoff. We develop a framework for designing admission control algorithms in wireless networks that support guaranteed QoS. First, we devise a taxonomy to explore the mathematical structure and practical design tradeoffs encountered in developing admission control algorithms. We next introduce the perfect knowledge admission control algorithm, which, while unrealizable in practice, serves as a benchmark for evaluating admission control algorithms by using future knowledge of handoff events to exactly control the admissible region. Finally, we perform an extensive set of simulations (including trace-driven simulations) and, applying the perfect knowledge algorithm, we study several admission control algorithm from the literature, identify a number of key system parameters for algorithm design, and quantify the fundamental tradeoffs in complexity and accuracy as revealed by the taxonomy.

Networks that support multiple services through "link-sharing" must address the fundamental conflicting requirement between isolation among service classes to satisfy each class' quality of service requirements, and statistical sharing of resources for efficient network utilization. While a number of service disciplines have been devised which provide mechanisms to both isolate flows and fairly share excess capacity, admission control algorithms are needed which exploit the effects of inter-class resource sharing. In this paper, we develop a framework of using statistical service envelopes to study inter-class statistical resource sharing. We show how this service envelope enables a class to over-book resources beyond its deterministically guaranteed capacity by statistically characterizing the excess service available due to fluctuating demands of other service classes. We apply our techniques to several multi-class schedulers, including generalized processor sharing, and design new admission control algorithms for multi-class link-sharing environments. We quantify the utilization gains of our approach with a set of experiments using long traces of compressed video.

In order for a network resource reservation scheme to efficiently support bursty real-time traffic streams, it must exploit the effects of statistical multiplexing. Moreover providing statistical services with deterministic traffic models has the advantage that deterministic client-specified traffic parameters may be efficiently policed or enforced by the network. We study the impact of the traffic's time scales on the effectiveness of such enforceable network services. In particular we use single and dual time-scale traffic sources to illustrate the importance of explicitly incorporating the source's multiple-time-scale nature into both the deterministic traffic model as well as the admission control algorithm. By investigating the errors introduced with a single time scale scheme, we show that even with an ideal choice of traffic parameters, a single-time scale approach can significantly under-estimate the true admissible region for dual time-scale traffic.

Providing statistical quality-of-service guarantees introduces conflicting requirements for both deterministic traffic models to isolate and police users and statistical multiplexing to efficiently utilize and share network resources. We address this issue by introducing two schemes for providing statistical services to deterministically policed sources: (1) adversarial mode resource allocation in which we bound the stochastic envelopes of policed streams and provide a statistical service for adversarial or worst case sources and (2) non-adversarial mode allocation in which we approximate the stochastic envelopes of policed, but non-worst-case streams in order to exploit a further statistical multiplexing gain in the typical case. Our key technique is to study the problem within the domain of deterministic and stochastic traffic envelopes, which allows us to explicitly consider sources with rate variations over multiple time scales, obtain results for any deterministic traffic model, and apply accurate admission control tests for buffered priority schedulers. We evaluate the scheme's performance with experiments using traces of compressed video and show that substantial statistical multiplexing gains are achieved.

A crucial problem for the efficient design and management of integrated services networks is how to best allocate network resources for heterogeneous and bursty traffic streams in multiplexers that support prioritized service disciplines. In this paper, we introduce a new approach for determining per-connection performance parameters such as delay-bound violation probability and loss probability in multi-service networks. The approach utilizes a traffic characterization consisting of the variances of a stream's rate distribution over multiple interval lengths, which captures its burstiness properties and autocorrelation structure. From this traffic characterization, we provide a simple and efficient resource allocation algorithm by deriving stochastic delay-bounds for static priority schedulers and employing a Gaussian approximation over intervals. To evaluate the scheme, we perform trace-driven simulation experiments with long traces of MPEG-compressed video and show that our approach is accurate enough to capture most of the inherent statistical multiplexing gain, achieving average network utilizations of up to 90% for these traces and substantially outperforming previous "effective bandwidth" techniques.

Variable bit-rate traffic that requires a bounded-delay network service is one of the most important types of traffic in future integrated services networks. We introduce a new deterministic traffic model called deterministic bounding interval-length dependent (D-BIND) to capture the important multiplexing properties of bursty streams. With the D-BIND model, clients specify their traffic to the network via multiple rate-interval pairs (R/sub k/, I/sub k/), where a rate R/sub k/ is a bounding or worst case rate over every interval of length I/sub k/. The model captures the intuitive property that, over longer interval lengths, a source may be bounded by a rate lower than its peak rate and closer to its long-term average rate. We analyze the new model in the context of a deterministic service, and we quantify its performance benefits using a set of experiments with traces of MPEG-compressed video. We show that D-BIND's more accurate characterization of traffic streams leads to substantial improvements in network utilization as compared to previous traffic models.

Current solutions to providing statistical performance guarantees to bursty traffic such as compressed video encounter several problems: (1) source traffic descriptors are often too simple to capture the burstiness and important time-correlations of VBR sources or too complex to be used for admission control algorithms; (2) stochastic descriptions of a source are inherently difficult for the network to enforce or police; (3) multiplexing inside the network's queues may change the stochastic properties of the source in an intractable way, precluding the provision of end-to-end QoS guarantees to heterogeneous sources with different performance requirements. We present a new approach to providing end-to-end statistical performance guarantees that overcomes these limitations. We term the approach hybrid bounding interval dependent (H-BIND) because it uses the deterministic-BIND traffic model to capture the correlation structure and burstiness properties of a stream; but unlike a deterministic performance guarantee, it achieves a statistical multiplexing gain (SMG) by exploiting the statistical properties of deterministically-bounded streams. Using traces of MPEG-compressed video, we show that the H-BIND scheme can achieve average network utilizations of up to 86% in a realistic scenario.

Compressed digital video is one of the most important traffic types in future integrated services networks. However, a network service that supports delay-sensitive video imposes many problems since compressed video sources are variable bit rate (VBR) with a high degree of burstiness. In this paper, we consider a network service that can provide deterministic guarantees on the minimum throughput and the maximum delay of VBR video traffic. A common belief is that due to the burstiness of VBR traffic, such a service will not be efficient and will necessarily result in low network utilization. We investigate the fundamental limits and trade-offs in providing deterministic performance guarantees to video and use a set of 10 to 30 min. long MPEG-compressed video traces for evaluation. Contrary to conventional wisdom, we are able to show that, in many cases, a deterministic service can be provided to video traffic while maintaining a reasonable level of network utilization. We first consider an ideal network environment that employs the most accurate deterministic, time-invariant video traffic characterizations, the optimal earliest-deadline-first packet schedulers, and exact admission control conditions. The utilization achievable in this situation provides the fundamental limits of a deterministic service. We then investigate the utilization limits in a network environment that takes into account practical constraints, such as the need for simple and efficient policing mechanisms, packet scheduling algorithms, and admission control tests.

Compressed digital video is one of the most important traffic types in future integrated services networks. However, a network service that supports delay-sensitive video imposes many problems since compressed video sources are variable bit rate (VBR) with a high degree of burstiness. In this paper, we consider a network service that can provide deterministic guarantees on the minimum throughput and the maximum delay of VBR video traffic. A common belief is that due to the burstiness of VBR traffic, such a service will not be efficient and will necessarily result in low network utilization. We investigate the fundamental limits and tradeoffs in providing deterministic performance guarantees to video and use a set of 10 to 90 minute long MPEG-compressed video traces for evaluation. Contrary to conventional wisdom, we are able to show that, in many cases, a deterministic service can be provided to video traffic while maintaining a reasonable level of network utilization. We first consider an ideal network environment that employs the most accurate deterministic, time-invariant video traffic characterizations, Earliest-Deadline-First packet schedulers, and exact admission control conditions. The utilization achievable in this situation provides the fundamental limits of a deterministic service. We then investigate the utilization limits in a network environment that takes into account practical constraints, such as the need for fast policing mechanisms, simple packet scheduling algorithms, and efficient admission control tests.

Emerging distributed multimedia applications have stringent performance requirements in terms of bandwidth, delay, delay-jitter, and loss rate. The Tenet real-time protocol suite provides the services and mechanisms for delivering such performance guarantees, even during periods of high network load and congestion. The protocols achieve this by using resource management, connection admission control, and appropriate packet service disciplines inside the network. The Sequoia 2000 network employs the Tenet Protocol Suite at each of its hosts and routers making it one of the first wide area packet-switched networks to provide end-to-end per-connection performance guarantees. This paper presents experiments with the Tenet protocols on the Sequoia 2000 network including measurements of the performance of the protocols, the service recieved by real multimedia applications using the protocols, and comparisons with the service received by applications that use the Internet protocols (UDP/IP). We conclude that the Tenet protocols successfully protect the real-time channels from other traffic in the network, including other real-time channels, and allow channels to continue to meet their performance guarantees, even when the network is highly loaded.

This paper demonstrates a new, efficient, and general approach for providing end-to-end performance guarantees in integrated services networks. This is achieved by modeling a traffic source with a family of bounding interval-dependent (BIND) random variables and by using a rate-controlled service discipline inside the network. The traffic model stochastically bounds the number of bits sent over time intervals of different length. The model captures different source behavior over different time scales by making the bounding distribution an explicit function of the interval length. The service discipline, RCSP, has the priority queueing mechanisms necessary to provide performance guarantees in integrated services networks. In addition, RCSP provides the means for efficiently extending the results from a single switch to a network of arbitrary topology. These techniques are derived analytically and then demonstrated with numerical examples.

Galileo is a flexible tool for simulation of heterogeneous real-time communication networks and for development and validation of network protocols. Galileo provides several unique features that make it particularly suitable for the simulation and analysis of networks that provide quality-of-service guarantees. First, its object-oriented programming environment provides the means for a modular, hierarchical, heterogeneous description of networks. Second, its multimedia device interface provides the tools for a qualitative analysis of network protocols. Finally, Galileo's network interface provides interaction with actual networks to access real data and simulate realistic multimedia scenarios.>