The physical layer security of a non-orthogonal multiple access (NOMA) system is investigated. In order to maximize the security level of each NOMA user in the system, a multiobjective optimization (MOO) problem is proposed for handling the relationship among conflicting objectives. A deep neural network-based framework is designed for solving the associated MOO problem and for estimating the Pareto front. The framework shows that the estimated Pareto front is very close to the true one, thus allowing designers to select Pareto optimal solutions for striking the most appropriate compromise for all users, even on dynamically time-variant basis. Numerical results are provided for illustrating the associated trade-offs.

Security threats of an IEEE 802.11ax (WiFi 6) system can occur throughout the layers of the protocol stack. Looking at the security aspect of the physical layer and from an attacker's perspective, we present how a spoofing attack can cause an access point to steer the beam dedicated to a legitimate user toward the attacker. More particularly, we propose the BeamSteal attack that takes advantage of the vulnerability of the beamforming feedback (BFF) mechanism. The purpose of the BeamSteal attack is to cause the access point to receive the wrong BFF -information-bearing bits and end up steering the beam toward the attacker instead of the legitimate user. To contrast the harmful effect of the proposed attack, we compare it with two benchmarks, namely the no attack case and the jamming attack case. Our numerical results show that the BeamSteal attack not only degrades the performance of the legitimate user, but also helps the attacker improve its performance significantly.

As potential solutions to empower transmissions among the Internet of Things (IoT) devices, ambient radio frequency (RF) backscatter technology and reconfigurable intelligent surfaces (RISs) have recently attracted a lot of attention. To improve energy and spectrum efficiency, we design a system with a transmit antenna selection (TAS)-aided base station (BS) relying on nonorthogonal multiple access (NOMA), RIS, and backscatter communications (BackCom) with robust transmission links, allowing more users to be served effectively. We adopt the two-user grouping model in the coverage of main BS associated with a particular RIS and interference from coordinate BS is also considered to showcase differences among the performance of the two different kinds of users (i.e., the IoT user with and the IoT user without a dedicated RIS). To exhibit the system performance, we derive closed-form expressions for two main system performance metrics, namely, outage probability and ergodic capacity. A degraded performance is also considered for the case of imperfect successive interference cancellation (SIC). The benefits of the BackCom RIS-aided NOMA system are then demonstrated by comparing its performance to that of traditional orthogonal multiple access (OMA) RIS-aided backscatter systems. We then introduce analytical models to characterize the impact of the main factors on the outage performance and characterize the optimal performance in specific cases. Together with extensive simulations, our analysis shows that the system performance can be adjusted by controlling factors, including power allocation coefficients, the number of metasurfaces of RIS, and target rates.

5G will enable the growing demand for Internet of Things (IoT), high-resolution video streaming, and low latency wireless services. Demand for such services is expected to growth rapid, which will require a search for Beyond 5G technological advancements in wireless communications. Part of these advancements is the need for additional spectrum, namely moving toward the terahertz (THz) range. To compensate for the high path loss in THz, narrow beamwidths are used to improve antenna gains. However, with narrow beamwidths, even minor fluctuations in device location (such as through body movement) can cause frequent link failures due to beam misalignment. In this paper, we provide a solution to these small-scale indoor movement that result in mobility-induced outages. Like a moth randomly flutters about, Mobility-induced Outages in THz (MOTH) can be ephemeral in nature and hard to avoid. To deal with MOTH we propose two methods to predict these outage scenarios: (i) Align-After-Failure (AAF), which predicts based on fixed time margins, and (ii) Align-Before-Failure (ABF), which learns the time margins through user mobility patterns. In this paper, two different online classifiers were used to train the ABF model to predicate if a mobility-induced outage is going to occur; thereby, significantly reducing the time spent in outage scenarios. Simulation results demonstrate a relationship between optimal beamwidth and human mobility patterns. Additionally, to cater to a future with dense deployment of Wireless Personal Area Network (WPAN), it is necessary that we have efficient deployment of resources (e.g., THz-APs). One solution is to maximize the user coverage for a single AP, which might be dependent on multiple parameters. We identify these parameters and observe their tradeoffs for improving user coverage through a single THz-AP.

Future (beyond 5G) wireless networks will demand high throughput and low latency and would benefit from greenfield, contiguous, and wider bandwidth, all of which THz spectrum can provide. Although THz has been envisioned to be deployed in an indoor setting, with proper enforcement and planning, we can draw a limited number of use cases for outdoor THz communication. THz can provide high capacity and ultra-high throughput but at the cost of high path loss and sensitivity to device orientation/mobility. We identify scenarios where the use of the THz spectrum for an outdoor setting is justified and their critical operating parameters. We further categorize the applications based on the relative mobility between the access point (AP) and user equipment (UE). We present an approach for deploying THz on an outdoor framework by presenting preliminary technical parameter analysis for scenarios, like wireless backhaul, high-speed kiosks, and the aerial base station (ABS). Our preliminary analysis shows that the application for each of these scenarios is limited based on multiple parameters, such as distance, device mobility, device orientation, user geometry, antenna gain, and environment settings' which requires separate consideration and optimization.

The increasing demand for ultra-high throughput in ultra-dense networks might take a toll on 5G capacity. Moreover, with Internet-of-Things (IoT) and the growing use-cases for indoor killer-applications, it will be necessary to look beyond 5G technologies. One such promising technology is to move higher in the frequencies, such as the THz (300 GHz-10 THz) spectrum. THz has a massive number of greenfield-contiguous channels ranging from 10 GHz to 200 GHz (best case), which was not available in the traditional radio frequency (RF) or millimeter wave (mmWave) bands. Although THz has immense potential to cater to such demands, it comes with numerous challenges revolving around hardware, link budget, mobility, blockages, scheduling, and deployment. Terahertz access points (THz-APs) are sensitive to deployment and can critically impact a system's dynamics (i.e., coverage, throughput, and efficiency). In this paper, we present Strategies for High-frequency INdoor Environments or SHINE, which focuses on efficient AP deployment in the THz spectrum and draws motivation from approaches used indoor to improve lighting conditions. Due to THz's limited coverage area of a few meters, the number of THz-APs required to satisfy a densely populated room will be higher compared to today's single router/box/AP model. This increased number of THzAPs will not only increase the operational costs, but also (in some cases) can make the system inefficient. Through SHINE, we explore the deployment-related challenges and propose strategies to mitigate the same.

Ultra-densification of user equipment (UE) and access points (APs) are anticipated to take a toll on the future spectrum needs. Higher frequency bands, such as mmWave (30-300GHz) and THz spectrum (0.3-10THz), can be used to cater to the high-throughput needs of ultra-dense networks. These high-frequency bands have a tremendous amount of green-filed contiguous spectrum, ranging in hundreds of GHz. However, these bands, especially the THz bands, face numerous challenges, such as high spreading, absorption, and penetration losses. To combat these challenges, the THz-APs need to be either equipped with high transmit power, high antenna gains (i.e., narrow antenna beams), or limit the communication to short-ranges. All of these factors are bounded due to technical or economic challenges, which will result in a “distance-power dilemma” while deciding on the deployment strategy of THz-APs. In this paper, we present an analytical model to deploy THz-APs in an indoor setting efficiently. We further show through extensive numerical analysis, the optimal number of APs and optimal room length for different blocks of the THz spectrum. Furthermore, these THz-APs need to be efficiently packed to avoid outages due to handoffs, which can add more complexity to the dilemma. To mitigate the packing problem, we propose two solutions over the optimal solution: (a) Radius Increase, and (b) Repeater Assistance, and present an analytical model for each.

Despite such challenges as high path loss and equipment cost, THz communication is becoming one of the potentially viable means through which ultra-high data rate can be achieved. To compensate for the high path loss, we present parameter modeling for indoor THz communication. To maximize efficient and opportunistic use of resources, we analyze the potential workarounds for a single access point to satisfy most of the mobile terminals by varying such parameters as humidity, distance, frequency windows, beamwidths, antenna placement, and user mobility type. One promising parameter is antenna beamwidth, where narrower beams results in higher antenna gain. However, this can lead to “beamwidth dilemma” scenario, where narrower beamwidth can result in significant outages due to device mobility and orientation. In this paper, we address this challenge by presenting a mobility model that performs an extensive analysis of different human mobility scenarios, where each scenario has different data rate demands and movement patterns. We observe that for mobile users, there are optimal beamwidths that are affected by the mobility type (high mobility, constrained mobility, and low mobility) and AP placement.

There has long been a conundrum on how to decrease harmful interference while encouraging the denser use of radio spectrum. The traditional way to mitigate interference is through conservative ex-ante (and, to some extent ex-post) power limits and enforcement methods. However, this conservative approach does not allow room for flexibility or coordination among radio systems, systems that are now more capable of minimizing interference than radio systems from even a decade ago. Exacerbating the problem is the continuing increase in device deployment and growing heterogeneity in network types, which together may soon strain the current interference management and enforcement processes. In this paper, we will explore how identification of devices could be used to ease interference. Identification for devices might already exist in the form of station id, IP, MAC, IMSI and FCC ID. However, in a more distributed and heterogeneous model, creating a more ubiquitous identification structure could be beneficial for mitigating harmful interference. By doing so we can keep track of devices/antennas and their operation modes (i.e., technical parameters), which, beyond interference mitigation, could also benefit enforcement, billing, spectrum sharing and security issues. In this paper, we show the application of granular identification of devices together with a greedy algorithm for improving interference management among heterogeneous networks.

In wireless multicast multimedia streaming, every data block (i.e., a group of packets) needs to be delivered within a hard deadline. On the other hand, to provide multilevel services, the widely adopted scalable video coding (SVC) prioritizes a video bit stream into a base layer and several enhancement layers. In this paper, we combine SVC with the transmission delay constraint and focus on multicasting hard deadline constrained prioritized (HDCP) data over wireless erasure channels. Specifically, we first define the performance metric and formulate the optimization problem. Then, we focus on a new adaptive RNC encoding and scheduling scheme to maximize the effective network throughput. Particularly, we propose simple and efficient greedy scheduling technique, which not only obtains near-optimal performance with low-time complexity but also suits time-varying fading channels. In addition, we extend our discussion to the more practical scenario with erroneous feedback and propose sampling-based feedback mechanism to reduce the system overhead. Both analytical and simulation results are provided to corroborate the effectiveness of the proposed techniques.

Recent work has examined techniques to estimate the “best” modulation rate for data networks such as 802.11a/g. While accurate rate estimation yields better rate-selection decisions and increased throughput, those methods must still choose between a handful of modulation rates. Each modulation rate is effective in a range of actual signal-to-noise ratios (SNRs) but the limited number of practical rates means that transmitters are often forced to “step down” to a lower data rate despite having a higher SNR than the minimum required for that lower rate. In this paper we describe, evaluate and implement a practical multiuser communication scheme that exploits these discrete “steps” in modulation rates to transmit two packets in the time normally needed to transmit a single packet, increasing aggregate throughput precisely when it is most needed—when the network is busy and suffers from rate unfairness. Because the method transmits a group of packets simultaneously, we call this scheme Group Rate Transmission with Intertwined Symbols, or GRaTIS. In addition to up to 120% improvement in network throughput achieved by GRaTIS, the technique is backward compatible with 802.11 and doesn’t require complex DSP algorithms as required by competing methods.

In this paper we introduce WASP, a general communication layer for hybrid wireless networks where multiple networks are used to complement each other. In our system, we capitalize on an infrastructure with a ubiquitous,wide-area network to help enable the creation of a local mobile ad-hocnetwork in an efficient, scalable, evolvable, and manageable way. In particular, in an architecture inspired by software-defined networking,we decouple the control plane and data plane in the mobile devices and shift the control plane to a centralized controller. The controller, reachable via the wide-area network, manages a collection of mobile devices by informing each device how to handle traffic based on neighbor information provided by the mobile devices. With this, a mobile ad-hoc network can help reduce the data burden on the ubiquitous network, and the ubiquitous network can help reduce the burden on the mobile devices. WASP can be used in different networks with different applications such as cellular and military networks. In this paper, we based our implementation on Android and tested on a collection of Google Nexus-4 devices to measure metrics such as battery consumption. We evaluate on an extended ns-3 simulation platform which we added the ability to run unmodified Android applications on the nodes within ns-3. Our experiments show that WASP scales better than traditional ad-hoc networks with only a minimal trade off of energy. Additionally, we show that a content distribution scheme using WASP on smart phones with cellular data plans significantly offloads bandwidth from the cellular infrastructure, and in turn reduces expensive data usage and energy usage.

Our dependence on mobile communications continues to grow; however, wireless devices may encounter inadequate coverage due to a variety of shortage and outage circumstances. In particular, in disaster situations, the access to communications is critical for rescue operations while local wireless infrastructure may have suffered damage. In this paper, we demonstrate the concept of hybrid cellular mobile ad hoc network (hybrid cellular-MANET) to extend wireless coverage by showing a fully functioning microblogging system for smartphones and tablets without requiring modifications of the existing wireless infrastructure in an emulated disaster area. Participating devices connect to each other through WiFi radio to form a hybrid cellular-MANET, relaying data off the MANET through the nodes that have sufficient cellular forwarding capability. We have proposed a self-organizing, mobility-aware, multi-path routing protocol (HMANET) to control the data forwarding in the hybrid cellular-MANET. We compare its performance with the classic Hybrid Wireless Mesh Protocol (HWMP) used in the IEEE 802.11s standard in the built microblogging system. Our experimental results show that the HMANET protocol statistically outperforms the HWMP protocol in terms of adaptiveness to role change and mobility in the hybrid cellular-MANET.

Who gets to use radio spectrum, and when, where, and how? Scheduling (who, where, when) and system configuration (how) are fundamental problems in radio communication and wireless networking. Optimization decomposition based on Lagrangian relaxation of signal quality requirements provides a mathematical framework for solving this type of combined problem. This paper demonstrates the technique as a solution to spatial reuse time-division multiple access (STDMA) scheduling with reconfigurable antennas. The joint beam steering and scheduling (JBSS) problem offers both a challenging mathematical structure and significant practical value. We present algorithms for JBSS and describe an implemented system based on these algorithms. We achieve up to 600% of the throughput of TDMA with a mean of 234% in our experiments. The decomposition approach leads to a working distributed protocol producing optimal solutions in an amount of time that is at worst linear in the size of the input. This is, to the best of our knowledge, the first actually implemented wireless scheduling system based on dual decomposition. We identify and briefly address some of the challenges that arise in taking such a system from theory to reality.

As we move forward towards the next generation of wireless protocols, the push for a better radio physical layer is ever increasing. Conventional radio architectures are limited to narrow operating regions and fails to adapt with changing technology. This is further strengthened with the advent of cognitive radio, which needs a more versatile and flexible framework that is programmable within the timing constraints of a protocol. In this paper we present an architecture for Software Defined Cognitive Radio that caters to the specific baseband processing requirements in a changing environment. We aim to provide more flexibility by de-constructing the radio pipeline into a framework of user controlled kernels that can be reconfigured at run-time. This architecture provides the bare-bones of a OFDM based radio physical layer that can adapt to perform a varied number of tasks in different radio networks. We also present a novel message based real-time reconfiguration method to transmit and receive a wide range of waveforms used in concurrent wireless protocols.

Open-access 802.11 wireless networks are commonly deployed in cafes, bookstores, and other public spaces to provide free Internet connectivity. These networks are convenient to deploy, requiring no out-of-band key exchange or prior trust relationships. However, such networks are vulnerable to a variety of threats including the evil twin attack where an adversary clones a client's previously-used access point for a variety of malicious purposes including malware injection or identity theft. We propose defenses that aim to maintain the simplicity, convenience, and usability of open-access networks while offering increased protection from evil twin attacks. First, we present an evil twin detection strategy called context-leashing that constrains access point trust by location. Second, we propose that wireless networks be identified by uncertified public keys and design an SSH-style authentication and session key establishment protocol that fits into the 802.1X standard. Lastly, to mitigate the pitfalls of SSH-style authentication, we present a crowd-sourcing-based reporting protocol that provides historical information for access point public keys while preserving the location privacy of users who contribute reports.

Vehicular safety systems for collisions or sensing rapid changes in traffic typically use two methods to communicate and disseminate traffic hazards. Many current systems use RADAR systems that transmit a radio wave and sense the reflective waves for angle-of-arrival or time-of-arrival information. Several proposed systems use vehicular networks to disseminate information about braking, emergencies or road conditions; when coupled with accelerometer or GPS information, these radio systems may also offer information on speed, traffic density or distance. In-vehicle RADAR systems are relatively expensive; vehicular radio based systems are less expensive. In this paper, we present a cooperative technology that combines these two techniques, seeking to adopt characteristics of both systems by employing a software defined radio for “cooperative RADAR” and vehicular networking. Our method uses multicarrier wireless communication to detect and disseminate. Using precise timing and synchronization, we can detect the distance of each of the vehicles, their current velocity and current acceleration or deceleration conditions. Using simultaneous, multi-party acknowledgments, we can rapidly disseminate or determine information about a number of vehicles in an efficient manner.

802.11 localization algorithms provide the ability to accurately position and track wireless clients thereby enabling location-based services and applications. However, we show that these localization techniques are vulnerable to non-cryptographic attacks where an adversary uses a low-cost directional antenna to appear from the localization algorithm's perspective to be in another arbitrary location of their choosing. The attacker's ability to actively influence where they are positioned is a key distinguishing feature of the directional attack relative to prior localization attacks that use transmit power control to introduce localization errors. We implement a representative set of received signal strength-based localization algorithms and evaluate the attack in a real office building environment. To mitigate the attack's effectiveness, we develop and evaluate an attack detection scheme that offers a high detection rate with few false positives.

Network protocols have traditionally been designed using a layered method in part because it is easier to implement some portions of network protocols in software and other portions must be implemented in hardware for performance reasons. These different implementation techniques enforce layer boundaries. In this paper, we show that with the advent of software defined radios, it becomes possible to blur those layer boundaries and produce higher performance network protocols as a result. In this paper we exploit a programmable physical layer and simultaneous transmission to have clients signal whether they have packets to send. By detecting the high energy at the simultaneous transmission, the AP gets the following information: a) which stations have packets to send and b) whether the traffic load is high, medium or low. Again, using the programmable physical layer, the AP schedules clients efficiently while wasting little of the spectrum on signaling overhead. The proposed protocol is a) fast, since no packet transmission is required for polling responses and all clients respond concurrently; b) reliable, as the poll response is contention free and c) scalable. We demonstrate the feasibility of implementing such a system using a FPGA based prototype software defined radio platform. We then show how the MAC protocol can scale using the QualNet network simulator and compare the performance to a contention based protocol.

Tor is currently the most popular low latency anonymizing overlay network for TCP-based applications. However, it is well understood that Tor's path selection algorithm is vulnerable to end-to-end traffic correlation attacks since it chooses Tor routers in proportion to their perceived bandwidth capabilities. Prior work has shown that the fraction of malicious routers and the amount of adversary-controlled bandwidth are significant factors for predicting the number of paths that an adversary can compromise. We extend this prior work by identifying that the application-layer protocol being transported is also a significant factor in predicting path compromise. Through a simulation study driven by data obtained from the real Tor network, we show that ports commonly associated with peer-to-peer file sharing protocols and the simple mail transport protocol (SMTP) are significantly more vulnerable to this attack than other ports.

Network protocol designers, both at the physical and network level, have long considered interference and simultaneous transmission in wireless protocols as a problem to be avoided. This, coupled with a tendency to emulate wired network protocols in the wireless domain, has led to artificial limitations in wireless networks.

Realistic radio modeling is crucial for accurate simulation of wireless networks. This paper examines the effect of using directional antennas in real environments with non-trivial multipath effects. We find that the actual variation in signal strength as a function of antenna direction differs appreciably - sometimes dramatically - from what the antenna power (gain) pattern alone would suggest. We quantify and analyze this difference across several antenna types and environments, and provide a generalizable parametric model to support more realistic planning, simulation and analysis.

Increasingly, directional antennas are being used in wireless networks. Such antennas can improve the quality of individual links and decrease overall interference. However, the interaction of environmental effects with signal directionality is not well understood. We observe that state of the art simulators make simplifying assumptions which are often unrealistic and can give a misleading picture of application layer performance. Because simulators are often used for prototyping and validating new ideas, their realism and accuracy are of primary importance. In this paper, we apply a new empirical simulation method for directional antennas and study how well this models reality. We show that not only is our model easy to implement, but is also more accurate and thus better able to predict the performance of propagation-sensitive applications.

In the design of wireless networking protocols and systems, simulation has become the primary form of initial validation and performance evaluation. Hence, ensuring the realism of simulators and simulation methods is fundamental for simulated results to be interpretable. In this paper, we provide a simulation framework for infrastructure wireless network traffic that allows researchers to use publicly available captured traces as a primary or background traffic source. We investigate the question of trace classification as a necessary task for these traces to be useful and apply our framework to a well-known power-saving application, showing that the use of real traffic provides substantially different results as compared to traffic generated from an application-specific fitted model or contrived source. Additionally, we show how trace classification provides unique insights into application behavior in both typical and extreme scenarios.

In recent years, a variety of algorithms for cognitive radio networks have been proposed. Many of these algorithms rely on the exchange of control information among the cognitive radio nodes and often require the presence of a globally available control channel. This requirement however poses a problem in a practical deployment: First, due to spectrum fluctuations such common control channel may be unknown at deployment stage. Second, when designating a fixed, dedicated control channel (for example in licensed spectrum), this will increase costs and expose vulnerability to the operation of the cognitive radio network. Thus, to overcome this difficulty, control channels should be dynamically assigned and managed in cognitive radio networks. In this paper, we propose the use of swarm intelligence as a way to dynamically find and manage such control channels in cognitive radio networks. The system we describe is able to independently identify viable control channels and adapt in presence of changing spectrum. We formalize the problem of control channel assignments to the multi-commodity flow problem, measure the performance of our approach in a hardware implementation and software simulation and compare the results against the theoretically optimal solution.

In this paper we use a large dataset of wireless user activity traces to test the various dynamic power management schemes. We also present and test our own empirically-driven dynamic power-saving algorithms, which are based on prior observations of user activity patterns. We believe that this sort of analysis can guide adoption of a user-behavior driven approach to radio and communications power management, and, in networking-centric devices, power management for the entire device. Additionally, understanding the characteristics of user-activity and efficient mechanisms to predict this activity can help inform the design of power-saving schemes for future networking protocols.

We present BitBlender, an efficient protocol that provides an anonymity layer for BitTorrent traffic. BitBlender works by creating an ad-hoc multi-hop network consisting of special peers called "relay peers" that proxy requests and replies on behalf of other peers. To understand the effect of introducing relay peers into the BitTorrent system architecture, we provide an analysis of the expected path lengths as the ratio of relay peers to normal peers varies. A prototype is implemented and experiments are conducted on Planetlab to quantify the performance overhead associated with the protocol. We also propose protocol extensions to add confidentiality and access control mechanisms, countermeasures against traffic analysis attacks, and selective caching policies that simultaneously increase both anonymity and performance. We finally discuss the potential legal obstacles to deploying an anonymous file sharing protocol. This work is among the first to propose a privacy enhancing system that is designed specifically for a particular class of peer-to-peer traffic.

The physical-layer models commonly used in current networking research only minimally address the interaction of directional antennas and radio propagation. This paper compares the models found in popular simulation tools with measurements taken across a variety of links in multiple environments. We find that the effects of antenna direction are significantly different from the models used by the common wireless network simulators. We propose a parametric model which better captures the effects of different propagation environments on directional antenna systems. We believe that adopting this model will allow more realistic simulation of protocols relying on directional antennas, supporting better design and more valid assessment of those protocols.

In recent years, cognitive radios that follow dynamic spectrum access policies have been proposed to overcome spectrum scarcity and to make better use of spectrum opportunities while avoiding interference to other users. The central component of such a cognitive radio is the control algorithm driving its sensing, learning and adaptation process. These three tasks however are both computationally expensive and resource intensive and it is therefore in the cognitive radio's best interest to minimize the time spent to sense, learn and adapt to its surroundings while still meeting its operational targets. In this paper, we present the rapid adaptation architecture, a statistical system that can be used in conjunction with existing cognitive radio control algorithms to speed up the learning and adaptation process without loosing significant accuracy. Through this system, control algorithms can be made more efficient by a factor of 2 or more, thus providing the cognitive radio with faster, more resource saving adaptations without major changes to the algorithm's inner workings or the overall cognitive radio.

This paper presents a method for improving the performance of Wireless Mesh Networks (WMN) through the use of multichannel wormhole switching. Current WMNs based on contention-based medium access control (MAC) such as ";WiFi"; suffer from high latency and low resource utilization because of competition for the shared single-channel medium. Through simulation we compare WMNs using contention-based wireless nodes versus WMNs using contention-free ";flit-relay"; wireless nodes. We demonstrate our ";flit-relay"; design as a promising low latency alternative to CSMA/CA for providing WMNs. The approximate 800-fold improvement in latency over WMNs using wireless nodes with a contention-based MAC and competitive setup times for VoIP support the argument for more development on pursuing this technology.

Network processors provide an economical programmable platform to handle the high throughput and frame rates of modern and next-generation communication systems. However, these platforms have exchanged general-purpose capabilities for performance.

In recent years, several algorithms for controlling cognitive radio platforms have been proposed. In this paper, we review the existing approaches that have been developed for cognitive radio control algorithms and extract the common sensing and control requirements for those algorithms. We also briefly discuss the challenges of defining representative testing scenarios. We then synthesize our experience implementing cognitive radio control algorithms and extract a set of pragmatic issues challenging researchers in cognitive radios. We conclude with a set of open questions and problems and discuss implications for future research.

Multimedia requirements of the 1990's drove wired and optical network architects to reconsider the inefficiencies of packet switching and consider long proven methods such as circuit-switching to implement traffic engineering in order to reduce end-to-end delay. This resulted in the development of asynchronous transfer mode (ATM) and multi-protocol label switching (MPLS) technologies. Because both are mature and proven technologies for wired and optical network architectures, much research has been done to apply these methods to wireless mesh networks. But optimal performance improvement eludes wireless mesh network designers because of differences between the wired/optical and wireless environments in the provision of non-interfering unidirectional internodal links and lack of a wireless circuit switch. We propose a wireless mesh networking architecture that will provide low-latency and potentially higher throughput, based upon the availability of multiple channels, a circuit-switch implemented at the physical layer, and a reservation protocol that will assign channels to provide non-interfering unidirectional internodal links.

This work was motivated by a discussion that two of the coauthors (computer science professors) had with the other coauthor (a law professor and a former computer crime Trial Attorney at the U.S. Department of Justice), in which it was pointed out that some of the network measurements that the computer scientists were thinking of making might potentially violate Federal laws.

Deployments of wireless LANs consisting of hundreds of 802.11 access points with a large number of users have been reported in enterprises as well as college campuses. However, due to the unreliable nature of wireless links, users frequently encounter degraded performance and lack of coverage. This problem is even worse in unplanned networks, such as the numerous access points deployed by homeowners. Existing approaches that aim to diagnose these problems are inefficient because they troubleshoot at too high a level, and are unable to distinguish among the root causes of degradation. This paper designs, implements, and tests fine-grained detection algorithms that are capable of distinguishing between root causes of wireless anomalies at the depth of the physical layer. An important property that emerges from our system is that diagnostic observations are combined from multiple sources over multiple time instances for improved accuracy and efficiency.

Seamless interoperability between two dissimilar networks require handoff from one network to the other. Such handoffs are known as vertical handoffs. Vertical handoff introduces a shift in the approach to handoffs. It deals with handoffs between dissimilar networks, such as from an access point to a base station or vice versa. A horizontal handoff, on the other hand, involves the scenario wherein the handoff is within the same network such as handoffs between cells. Most of the existing research proposes to implement vertical handoff on an overlay network, wherein a user moves from one geographic location to another, such as moving from a WLAN coverage area to a cellular coverage area, or vice versa. This research discusses the need to trigger a vertical handoff based on changes in the mobile environment independent of geographic changes of a user. We develop a novel framework that executes vertical handoff based on a multilayer approach coupled together with adjunct information such as pricing and user preference. This framework allows changes in applications, variations in network conditions and user preferences to trigger vertical handoffs. We conclude by providing a general evaluation of the framework.

Selective encryption is a technique to save computational complexity or enable new system functionality by encrypting only a portion of a compressed bitstream while achieving adequate security. Although suggested in a number of specific cases, selective encryption could be much more widely used in consumer electronic applications, ranging from mobile multimedia terminals to digital cameras, were it subjected to a more thorough security analysis. We describe selective encryption and develop a simple scalar quantizer example to demonstrate the power of the concept, list a number of potential consumer electronics applications, then describe an appropriate method for developing and analyzing selective encryption for particular compression algorithms. We summarize results from the application of this method to the MPEG-2 video compression algorithm.