The rising popularity of Vehicle-to-Network (V2N) applications is driven by the Ultra-Reliable Low-Latency Communications (URLLC) service offered by 5G. Distributed resources can help manage heavy traffic from these applications, but complicate traffic routing under URLLCfs strict delay requirements. In this paper, we introduce the V2N Computation Offloading and CPU Activation (V2N-COCA) problem, aiming at the monetary/energetic cost minimization via computation offloading and edge/cloud CPU activation decisions, under stringent latency constraints. Some challenges are the proven nonmonotonicity of the objective function and the no-existence of closed-formulas for the sojourn time of tasks. We present a provably tight approximation for the latter, and we design BiQui, a provably asymptotically optimal and computationally efficient algorithm for the V2N-COCA problem. We then study dynamic scenarios, introducing the Swap-Prevention problem, to account for changes in the traffic load and minimize the switching on/off of CPUs without incurring into overcosts.We prove the problemfs structural properties and exploit them to design Min-Swap, a provably correct and computationally effective algorithm for the Swap-Prevention Problem. We assess both BiQui and Min-Swap over real-world vehicular traffic traces, performing a sensitivity analysis and a stress-test. Results show that (i) BiQui is nearoptimal and significantly outperforms existing solutions; and (ii) Min-Swap reduces by a ≥90% the CPU swapping incurring into just ≤0.14% extra cost.

As mobile networks become more complex to handle increasing data traffic and a broader range of services, operators must balance the trade-offs between static and dynamic configurations. While traditional static configurations across the entire network are simpler to manage, dynamic adjustments, though more complex to operate, are better suited to adapting to evolving demands. To explore this balance, in this paper, we use real data from a mobile network to evaluate the potential gains in throughput gains, measured by downlink traffic, when dynamically adjusting configurations at both spatial and temporal scales. Our findings show that combining these dynamic adjustments leads to significant performance improvements, with traffic volume gains exceeding 30% when configurations are tailored at the cell level and to the hour scale.

The rising popularity of Vehicle-to-Network (V2N) applications is driven by the Ultra-Reliable Low-Latency Communications (URLLC) service offered by 5G. The availability of distributed resources could be leveraged to handle the enormous traffic arising from these applications, but introduces complexity in deciding where to steer traffic under the stringent delay requirements of URLLC. In this paper, we introduce the V2N Computation Offloading and CPU Activation (V2N-COCA) problem, which aims at finding the computation offloading and the edge/cloud CPU activation decisions that minimize the operational costs, both monetary and energetic, under stringent latency constraints. Some challenges are the proven non-monotonicity of the objective function w.r.t. offloading decisions, and the no-existence of closed-formulas for the sojourn time of tasks. We present a provably tight approximation for the latter, and we design BiQui, a provably asymptotically optimal and with linear computational complexity w.r.t. computing resources algorithm for the V2N-COCA problem. We assess BiQui over real-world vehicular traffic traces, performing a sensitivity analysis and a stress-test. Results show that BiQui significantly outperforms state-of-the-art solutions, achieving optimal performance (found through exhaustive searches) in most of the scenarios.

Auto-scaling techniques aim to keep the right number of active servers for the current load: if this number is too small we risk service disruption, but if it is too large we waste resources. Despite the interest in the efficient operation of this type of systems, no prior work has addressed auto-scaling techniques for Network Function Virtualization (NFV) with stringent reliability requirements such as those envisioned in 5G (5 or 6 nines). To achieve such levels of reliability, we need to account for both the activation delay until servers become available (i.e., the wake-up or activation time) and the fallible nature of servers (which may fail with some probability). In this article, we build on control theory to design an auto-scaling technique for a server farm for NFV that guarantees certain reliability while minimizing the number of active resources. We show that the use of well-established tools from control theory results in convergence times much shorter than those obtained with state-of-the-art reinforcement learning techniques. This shows that, despite the current trend to apply machine learning to all sorts of networking problems, there may be some cases where other techniques (such as control theory) can be more suitable.

The Google's Loon$^{TM}$initiative aims at covering rural or underdeveloped areas via fleets of high-altitude balloons supporting LTE connectivity. But how effective and stable can be the coverage provided by a network deployed via propulsion-free balloons, floating in the sky, and only loosely controllable through altitude variations? To provide some insights on the relevant performance and trade-offs, in this paper we gather real-world data from publicly available flight tracking services, and we analyze coverage and service stability in three past deployment scenarios. Besides employing a variety of metrics related to spatial and temporal coverage, we also assess service continuity, by also leveraging recently proposed “meaningful availability” metrics. While our analyses show that balloons are certainly a cost-effective way to provide a better-than-nothing and delay-tolerant service, there is yet no empirical evidence that an increase in the number of overlapping balloons may be rewarded with a substantial performance increase — in other words, we suspect that guaranteeing coverage and service stability levels comparable to that of a terrestrial cellular network is a challenging goal.

The softwarization of mobile networks enables an efficient use of resources, by dynamically scaling and re-assigning them following variations in demand. Given that the activation of additional servers is not immediate, scaling up resources should anticipate traffic demands to prevent service disruption. At the same time, the activation of more servers than strictly necessary results in a waste of resources, and thus should be avoided. Given the stringent reliability requirements of 5G applications (up to 6 nines) and the fallible nature of servers, finding the right trade-off between efficiency and service disruption is particularly critical. In this paper, we analyze a generic auto-scaling mechanism for communication services, used to de(activate) servers in a cluster, based on occupation thresholds. We model the impact of the activation delay and the finite lifetime of the servers on performance, in terms of power consumption and failure probability. Based on this model, we derive an algorithm to optimally configure the thresholds. Simulation results confirm the accuracy of the model both under synthetic and realistic traffic patterns as well as the effectiveness of the configuration algorithm. We also provide some insights on the best strategy to support an energy-efficient highly-reliable service: deploying a few powerful and reliable machines versus deploying many machines, but less powerful and reliable.

Fifth generation (5G) and beyond systems require flexible and efficient monitoring platforms to guarantee optimal key performance indicators (KPIs) in various scenarios. Their applicability in Edge computing environments requires lightweight monitoring solutions. This work evaluates different candidate technologies to implement a monitoring platform for 5G and beyond systems in these environments. For monitoring data plane technologies, we evaluate different virtualization technologies, including bare metal servers, virtual machines, and orchestrated containers. We show that containers not only offer superior flexibility and deployment agility, but also allow obtaining better throughput and latency. In addition, we explore the suitability of the Function-as-a-Service (FaaS) serverless paradigm for deploying the functions used to manage the monitoring platform. This is motivated by the event oriented nature of those functions, designed to set up the monitoring infrastructure for newly created services. When the FaaS warm start mode is used, the platform gives users the perception of resources that are always available. When a cold start mode is used, containers running the application’s modules are automatically destroyed when the application is not in use. Our analysis compares both of them with the standard deployment of microservices. The experimental results show that the cold start mode produces a significant latency increase, along with potential instabilities. For this reason, its usage is not recommended despite the potential savings of computing resources. Conversely, when the warm start mode is used for executing configuration tasks of monitoring infrastructure, it can provide similar execution times to a microservice-based deployment. In addition, the FaaS approach significantly simplifies the code logic in comparison with microservices, reducing lines of code to less than 38%, thus reducing development time. Thus, FaaS in warm start mode represents the best candidate technology to implements such management functions.

RAN virtualization will become a key technology for the last mile of next-generation mobile networks driven by initiatives such as the O-RAN alliance. However, due to the computing fluctuations inherent to wireless dynamics and resource contention in shared computing infrastructure, the price to migrate from dedicated to shared platforms may be too high. Indeed, we show in this paper that the baseline architecture of a base station's distributed unit (DU) collapses upon moments of deficit in computing capacity. Recent solutions to accelerate some signal processing tasks certainly help but do not tackle the core problem: a DU pipeline that requires predictable computing to provide carrier-grade reliability.

We demonstrate Nuberu. The scenario consists of a DU under test (DuT), and one or more DUs sharing computing resources. A dashboard lets us control (𝑖) the type of DuT: “Baseline”, implemented with a legacy full-fledged eNB, or Nuberu; (𝑖𝑖) the number of competing vDUs; and (𝑖𝑖𝑖) their SNR. A second screen shows real-time metrics: (𝑖) the processing latency of the TBs from each vDU instance; (𝑖𝑖) the throughput performance of DuT; (𝑖𝑖𝑖) the processing latency of DU jobs from DuT; and (𝑖𝑣) the ratio of latency constraint violations of DuT jobs. We show how the throughput attained by the baseline DU approach collapses upon sufficiently high computing interference from the competing DUs. Conversely, we show that the DU design introduced in [3] preserves reliability irrespective of the computing interference.

Abstract Anonymous communication tools, such as Tor, are extensively employed by users who want to keep their web activity private. But recent works have shown that when a local, passive adversary observes nothing more than the timestamp, size and direction (incoming or outgoing) of the packets, it can still identify with high accuracy the website accessed by a user. Several defenses against these website fingerprinting attacks have been proposed but they come at the cost of a significant overhead in traffic and/or website loading time. We propose a defense against website fingerprinting which exploits multihoming, where a user can access the Internet by sending the traffic through multiple networks. With multihoming, it is possible to protect against website fingerprinting by splitting traffic among the networks, i.e., by removing packets from one network and sending them through another, whereas current defenses can only add packets. This enables us to design a defense with no traffic overhead that, as we show through extensive experimentation against state-of-the-art attacks, reaches the same level of privacy as the best existing practical defenses. We describe and evaluate a proof-ofconcept implementation of our defense and show that is does not add significant loading-time overhead. Our solution is compatible with other state-of-the-art defenses, and we show that combining it with another defense further improves privacy.

The IEEE 802.11aa amendment standardised the Group Addressed Transmission Service (GATS), which extends 802.11 WLANs with a novel set of MAC mechanisms to support an effective and efficient multicast video service. The key challenge with GATS is the selection of the best scheme and its configuration for a given network scenario, as the standard does not provide any guidelines nor any assessment of the performance of each mechanism. Although some previous studies have addressed this challenge, their evaluation is either via analysis or simulations under non-realistic assumptions, or based on Quality of Service (QoS) metrics instead of video quality metrics, which are required for a proper video performance assessment. In this paper, we deploy a mid-size real-life testbed and develop a thoughtful methodology to perform an extensive Quality of Experience (QoE) evaluation of GATS under a variety of scenarios. We analyse the performance of the novel schemes under ideal conditions, as well as under controlled and non-controlled interference, assessing their ability to provide an adequate QoE and quantifying the resources left for other type of traffic. Ours is the first thorough QoE evaluation of GATS in a real-life scenario, providing key insights on their performance, and can be used to derive configuration guidelines for the schemes.

Enterprise Networking has a strong set of requirements in terms of resiliency, reliability and resources usage. With current approaches being based on monolithic and expensive infrastructures using dedicated overlay links, providers are moving to more economical hybrid solutions that encompass private dedicated links with public/regular Internet connections. However, these usually rely on complex, hardware-dependent and/or proprietary Traffic Engineering (TE) solutions, which are computationally costly, in particular for the forwarding nodes. In this paper, we propose SEMPER: a lightweight TE solution based on MP-TCP that, in contrast to other TE solutions, moves the complexity to the endpoints of the connection, and relieves the forwarding elements from complex operations or even maintaining state. As our evaluation shows, SEMPER efficiently makes use of all available paths between the endpoints while maintaining fairness, and properly adapts to variations on the available capacity.

We study the fair coexistence of scheduled and random access transmitters sharing the same frequency channel. Interest in coexistence is topical due to the need for emerging unlicensed LTE technologies to coexist fairly with WiFi. However, this interest is not confined to LTE/WiFi as coexistence is likely to become increasingly commonplace in IoT networks and beyond 5G. In this paper, we show that mixing scheduled and random access incurs an inherent throughput/delay cost and the cost of heterogeneity. We derive the joint proportional fair rate allocation, which casts useful light on current LTE/WiFi discussions. We present experimental results on inter-technology detection and consider the impact of imperfect carrier sensing.

Rate adaptation in 802.11 WLANs has received a lot of attention from the research community, with most of the proposals aiming at maximising throughput based on network conditions. Considering energy consumption, an implicit assumption is that optimality in throughput implies optimality in energy efficiency, but this assumption has been recently put into question. In this paper, we address via analysis and experimentation the relation between throughput performance and energy efficiency in multi-rate 802.11 scenarios. We demonstrate the trade-off between these performance figures, confirming that they may not be simultaneously optimised, and analyse their sensitivity towards the energy consumption parameters of the device. Our results provide the means to design novel rate adaptation schemes that takes energy consumption into account.

Increasing the density of access points is one of the most effective mechanisms to cope with the growing traffic demand in wireless networks. To prevent energy wastage at low loads, a resource-on-demand (RoD) scheme is required to opportunistically (de)activate access points as network traffic varies. While previous publications have analytically modeled these schemes in the past, they have assumed that resources are immediately available when activated, an assumption that leads to inaccurate results and might result in inappropriate configurations of the RoD scheme. In this paper, we analyze a general RoD scenario with N access points and non-zero start-up times. We first present an exact analytical model that accurately predicts performance but has a high computational complexity, and then derive a simplified analysis that sacrifices some accuracy in exchange for a much lower computational cost. To illustrate the practicality of this model, we present the design of a simple configuration algorithm for RoD. Simulation results confirm the validity of the analyses, and the effectiveness of the configuration algorithm.

The 802.11e standard enables user configuration of several MAC parameters, making WLANs vulnerable to users that selfishly configure these parameters to gain throughput. In this paper, we propose a novel distributed algorithm to thwart such selfish behavior. The key idea of the algorithm is for stations to react, upon detecting a misbehavior, by using a more aggressive configuration that penalizes the misbehaving station. We show that the proposed algorithm guarantees global stability while providing good response times. By conducting an analysis of the effectiveness of the algorithm against selfish behaviors, we also show that a misbehaving station cannot obtain any gain by deviating from the algorithm. Simulation results confirm that the proposed algorithm optimizes throughput performance while discouraging selfish behavior. We also present an experimental prototype of the proposed algorithm demonstrating that it can be implemented on commodity hardware.

In the past years, researchers have been advocating for flexible 802.11 devices that dynamically adapt to the varying network conditions, looking for efficient alternatives to the 802.11 standard MAC. In this work we demonstrate that this flexibility is readily available at the MAC level, and its operation can be tuned by re-programming the firmware inside the wireless chipsets that are built on relatively generic hardware modules. We show this by implementing the new amendment IEEE 802.11aa in legacy equipments by simply coding the frame exchange schemes at the firmware level. Nevertheless, we claim that the lack of flexibility in the way these modules interact results in a bottleneck that severely degrades performance. In our work, we prove this inefficiency of the 802.11 hardware architecture that hinders high throughput features, as in our case study of 802.11aa reliable multicast. To solve this problem, we provide new directions for the revision of the current hardware architecture and propose a new vision for the future design of wireless chipsets.

Current IEEE 802.11 WLANs suffer from the well-known rate anomaly problem, which can drastically reduce network performance. Opportunistic relaying can address this problem, but three major considerations, typically considered separately by prior work, need to be taken into account for an efficient deployment in real-world systems: 1) relaying could imply increased power consumption, and nodes might be heterogeneous, both in power source (e.g., battery-powered versus socket-powered) and power consumption profile; 2) similarly, nodes in the network are expected to have heterogeneous throughput needs and preferences in terms of the throughput versus energy consumption tradeoff; and 3) any proposed solution should be backwards-compatible, given the large number of legacy 802.11 devices already present in existing networks. In this paper, we propose a novel framework, Self-Optimizing, Legacy-Compatible Opportunistic Relaying (SOLOR), which jointly takes into account the above considerations and greatly improves network performance even in systems comprised mostly of vanilla nodes and legacy access points. SOLOR jointly optimizes the topology of the network, i.e., which are the nodes associated to each relay-capable node; and the relay schedules, i.e., how the relays split time between the downstream nodes they relay for and the upstream flow to access points. Our results, obtained for a large variety of scenarios and different node preferences, illustrate the significant gains achieved by our approach. Specifically, SOLOR greatly improves network throughput performance (more than doubling it) and power consumption (up to 75% reduction) even in systems comprised mostly of vanilla nodes and legacy access points. Its feasibility is demonstrated through testbed experimentation in a realistic deployment.

This paper provides an in-depth understanding of the per-frame energy consumption behavior in 802.11 wireless LAN devices. Extensive measurements are performed for seven devices of different types (wireless routers, smartphones, tablets, and embedded devices) and for both UDP and TCP traffic. Experimental results unveil that a substantial fraction of energy consumption, hereafter descriptively named cross-factor, may be ascribed to each individual frame while it crosses the protocol stack (OS, driver, NIC) and is independent of the frame size. Our findings, summarized in a convenient energy consumption model, contrast traditional models that (implicitly) amortize such energy cost component in a fixed baseline cost or in a toll proportional to the frame size and raise the alert that, in some cases, conclusions drawn using traditional energy models may be fallacious.

Distributed opportunistic scheduling (DOS) techniques have been recently proposed for improving the throughput performance of wireless networks. With DOS, each station contends for the channel with a certain access probability. If a contention is successful, the station measures the channel conditions and transmits in case the channel quality is above a certain threshold. Otherwise, the station does not use the transmission opportunity, allowing all stations to recontend. A key challenge with DOS is to design a distributed algorithm that optimally adjusts the access probability and the threshold of each station. To address this challenge, in this paper, we first compute the configuration of these two parameters that jointly optimizes throughput performance in terms of proportional fairness. Then, we propose an adaptive algorithm based on control theory that converges to the desired point of operation. Finally, we conduct a control theoretic analysis of the algorithm to find a setting for its parameters that provides a good tradeoff between stability and speed of convergence. Simulation results validate the design of our mechanism and confirm its advantages over previous works.

Handling voice traffic in existing WLANs is extremely inefficient, due to the large overhead of the protocol operation as well as the time spent in contention. In this paper, we propose a simple scheme (VoIPiggy) to improve the efficiency of WLANs with voice traffic. The key idea of the mechanism is to piggyback voice frames onto the MAC layer acknowledgments, which reduces both the frame overhead and the time wasted in contention. To quantify the gains of our proposal, we first study its performance by means of a capacity and delay analysis of a WLAN operating under the VoIPiggy mechanism. Then, we present an implementation of the mechanism using commercial off-the-shelf devices, which involves programming at the driver and firmware levels. The performance of the proposed scheme is evaluated in a large-scale testbed consisting of 30 devices. Our extensive measurements, which are comprised of different network conditions in terms of number of active nodes, traffic load and transmission rates, confirm that the experimental results match the analytical ones, and show a dramatic performance improvement for both “voice only” and “voice and data” scenarios.

In this paper, we propose to provide throughput guarantees in heterogeneous wireless mesh networks by jointly optimizing routing and Medium Access Control configuration. Our solution is based on the notion of linearized capacity region, which provides a technology-independent way of representing the capacity of a wireless link thereby hiding the technology specifics to the upper layers. From the available capacity of the underlying links as given by the linearized capacity region, we propose two routing algorithms based on multipath and single path that find optimal paths for all the flows in the network given their throughput requirements. The throughput allocation resulting from routing is then provided to each link, which uses this information to optimize its technology-specific Medium Access Control parameters. The proposed approach is evaluated in a heterogeneous scenario comprising Wireless Local Area Networks WLAN and Worldwide Interoperability for Microwave Access WiMAX technologies and is shown to outperform previous solutions by at least a factor of 2.Copyright © 2012 John Wiley & Sons, Ltd.

Current trends on mobile traffic show an exponential grow of the traffic consumed by users from smartphones and other portable devices. The explosion of traffic in cellular networks has forced operators to start deploying solutions to alleviate the congestion on their capacity-limited and expensive radio access networks. One of the solutions being discussed is the so called 3G offload that enables the terminals to use other technologies such as WiFi to offload some of the traffic. IP flow mobility is one mechanism providing 3G offload, by enabling selected flows to be moved among network interfaces. Although this is a very promising technology, it is not clear yet how it will affect the protocols currently in use to provide IP mobility in cellular networks, e.g., Proxy Mobile IPv6. The use of 3G offloading does not only benefits the operators, but also the final user, as it might extend the battery lifetime of its terminal. In this paper we first describe some network-based IP flow mobility extensions, highlighting important design choices. Secondly, we focus on providing experimental measurements showing how the use of this technology can result in an extended battery life for the case of 3G and WiFi enabled terminals.

Video traffic is foreseen to account for the majority of the Internet traffic in the near future. While the demand of video transmission keeps growing, the vast majority of wireless equipment deployed in the home environment, based on IEEE 802.11, cannot satisfy the amount of bandwidth that the video applications require. In order to cope with the increasing demand of multimedia traffic, the IEEE 802.11aa Task Group has recently standardized new mechanisms to allow efficient and robust transmission of multicast flows in Wireless LAN. However, the standard leaves open the choice of which one to use for a given scenario. In this paper, we explore the new mechanisms introduced by the 802.11aa Task Group, providing insights of the new choices for handling group addressed frames, by carrying out extensive simulations. Our results highlight the various trade-offs each mechanism has in terms of robustness, resource consumption and complexity, and provide a set of recommended guidelines for their use.

Distributed opportunistic scheduling (DOS) is inherently more difficult than conventional opportunistic scheduling due to the absence of a central entity that knows the channel state of all stations. With DOS, stations use random access to contend for the channel and, upon winning a contention, they measure the channel conditions. After measuring the channel conditions, a station only transmits if the channel quality is good; otherwise, it gives up the transmission opportunity. The distributed nature of DOS makes it vulnerable to selfish users: By deviating from the protocol and using more transmission opportunities, a selfish user can gain a greater share of wireless resources at the expense of “well-behaved” users. In this paper, we address the problem of selfishness in DOS from a game-theoretic standpoint. We propose an algorithm that satisfies the following properties: 1) When all stations implement the algorithm, the wireless network is driven to the optimal point of operation; and 2) one or more selfish stations cannot obtain any gain by deviating from the algorithm. The key idea of the algorithm is to react to a selfish station by using a more aggressive configuration that (indirectly) punishes this station. We build on multivariable control theory to design a mechanism for punishment that is sufficiently severe to prevent selfish behavior, yet not so severe as to render the system unstable. We conduct a game-theoretic analysis based on repeated games to show the algorithm's effectiveness against selfish stations. These results are confirmed by extensive simulations.

A thorough understanding of the power consumption behavior of real world wireless devices is of paramount importance to ground energy-efficient protocols and optimizations on realistic and accurate energy models. This paper provides an in-depth experimental investigation of the per-frame energy consumption components in 802.11 Wireless LAN devices. To the best of our knowledge, our measurements are the first to unveil that a substantial fraction of energy consumption, hereafter descriptively named cross-factor, may be ascribed to each individual frame while it crosses the protocol/implementation stack (OS, driver, NIC). Our findings, summarized in a convenient new energy consumption model, contrast traditional models which either neglect or amortize such energy cost component in a fixed baseline cost, and raise the alert that, in some cases, conclusions drawn using traditional energy models may be fallacious.

Distributed Opportunistic Scheduling (DOS) techniques have been recently proposed to improve the throughput performance of wireless networks. With DOS, each station contends for the channel with a certain access probability. If a contention is successful, the station measures the channel conditions and transmits in case the channel quality is above a certain threshold. Otherwise, the station does not use the transmission opportunity, allowing all stations to recontend. A key challenge with DOS is to design a distributed algorithm that optimally adjusts the access probability and the threshold of each station. To address this challenge, in this paper we first compute the configuration of these two parameters that jointly optimizes throughput performance in terms of proportional fairness. Then, we propose an adaptive algorithm based on control theory that converges to the desired point of operation. Finally, we conduct a control theoretic analysis of the algorithm to find a setting for its parameters that provides a good tradeoff between stability and speed of convergence. Simulation results validate the design of the proposed algorithm and confirm its advantages over previous proposals.

Supporting voice traffic in existing WLANs results extremely inefficient, given the large overheads of the protocol operation and the need to prioritize this traffic over, e.g., bulky transfers. In this paper we propose a simple scheme to improve the efficiency of WLANs when voice traffic is present. The mechanism is based on piggybacking voice frames over the acknowledgments, which reduces both frame overheads and time spent in contentions. We evaluate its performance in a large-scale testbed consisting on 33 commercial off-the-shelf devices. The experimental results show dramatic performance improvements in both voice-only and mixed voice-and-data scenarios.

The EDCA mechanism of the IEEE 802.11 standard has been designed to support, among others, video traffic. This mechanism relies on a number of parameters whose configuration is left open by the standard. Although there are some recommended values for these parameters, they are fixed independent of the WLAN conditions, which results in suboptimal performance. Following this observation, a number of approaches in the literature have been devised to set the EDCA parameters based on an estimation of the WLAN conditions. However, these previous approaches are based on heuristics and hence do not guarantee optimized performance. In this article we propose a novel algorithm to adjust the EDCA parameters to carry video traffic which, in contrast to previous approaches, is sustained on mathematical foundations that guarantee optimal performance. In particular, our approach builds upon (i) an analytical model of the WLAN performance under video traffic, used to derive the optimal point of operation of EDCA, and (ii) a control theoretic designed mechanism which drives the WLAN to this point of operation. Via extensive simulations, we show that the proposed approach performs optimally and substantially outperforms the standard recommended configuration as well as previous adaptive proposals.

In this paper we investigate the case of IEEE 802.11-based WLANs and first show that, given the existing diversity of power consumption figures among mobile devices, performing a fair allocation of resources among devices is challenging. We then propose a criterion to objectively balance between the most energy-efficient configuration (where all resources are given to the single most energy efficient device) and the throughput-optimal allocation (where all devices evenly share the resources regardless of their power consumption). We derive a closed-form expression for the optimal configuration of the WLANs with respect to the energy-efficiency criterion. We validate our analysis through simulations, and show that our approach betters the prevalent allocation schemes discussed in literature in terms of energy efficiency, while maintaining the notion of fairness among competing devices.

Building vehicular networks in roads and highways is a challenging research topic with a large number of applications ranging from traffic jams and car collisions prevention to efficient route planning. The analysis of the distance between vehicles in roads is a key factor in, e.g., designing vehicular networks protocols or planning a supporting infrastructure to improve vehicular connectivity. This work proposes a Gaussian-exponential mixture model to characterize the time distance between vehicles in a highway lane, based on measurements collected at different locations in several highways of the city of Madrid, in Spain. The model arises from the observed behavior that some vehicles travel very close together, like in a burst mode, showing Gaussian inter-arrival times, while other vehicles are somehow isolated, showing exponentially distributed inter-arrival times. The experiments show that such a Gaussian-exponential mixture model accurately characterizes inter-vehicle times observed from real traces.

The optimal configuration of the contention parameters of a WLAN depends on the network conditions in terms of number of stations and the traffic they generate. Following this observation, a considerable effort in the literature has been devoted to the design of distributed algorithms that optimally configure the WLAN parameters based on current conditions. In this paper, we propose a novel algorithm that, in contrast to previous proposals which are mostly based on heuristics, is sustained by mathematical foundations from multivariable control theory. A key advantage of the algorithm over existing approaches is that it is compliant with the 802.11 standard and can be implemented with current wireless cards without introducing any changes into the hardware or firmware. We study the performance of our proposal by means of theoretical analysis, simulations, and a real implementation. Results show that the algorithm substantially outperforms previous approaches in terms of throughput and delay.

Even though current mesh networks are mostly WiFi-based, future networks are expected to be highly heterogeneous. Motivated by this expectation, CARMEN (CARrier grade MEsh Networks) project focuses on developing a heterogeneous mesh backhaul to provide carrier-grade (voice, video and data) services. This demo presents resource management and abstraction in CARMEN architecture, which allow meeting the challenges of heterogeneous radio access.

Although the EDCA access mechanism of the 802.11e standard supports legacy DCF stations, the presence of DCF stations in the WLAN jeopardizes the provisioning of the service guarantees committed to the EDCA stations. The reason is that DCF stations compete with Contention Windows (CWs) that are predefined and cannot be modified, and as a result, the impact of the DCF stations on the service received by the EDCA stations cannot be controlled. In this paper, we address the problem of providing throughput guarantees to EDCA stations in a WLAN in which EDCA and DCF stations coexist. To this aim, we propose a technique that, implemented at the Access Point (AP), mitigates the impact of DCF stations on EDCA by skipping with a certain probability the Ack reply to a frame from a DCF station. When missing the Ack, the DCF station increases its CW, and thus, our technique allows us to have some control over the CWs of the legacy DCF stations. In our approach, the probability of skipping an Ack frame is dynamically adjusted by means of an adaptive algorithm. This algorithm is based on a widely used controller from classical control theory, namely a Proportional Controller. In order to find an adequate configuration of the controller, we conduct a control-theoretic analysis of the system. Simulation results show that the proposed approach is effective in providing throughput guarantees to EDCA stations in presence of DCF stations.

Recent measurement studies have analyzed WLAN performance by means of wireless sniffers that passively capture transmitted frames. Also, for relatively large (enterprise) WLAN scenarios, previous work has investigated multi-sniffer deployments with devices placed far apart in order to capture all traffic in the network (even frames transmitted simultaneously by different nodes at non-interfering locations). However, for both these single- and multi-sniffer scenarios, little attention has been given to the fidelity of an individual device, i.e., the ability of a given sniffer to capture all frames that could have been captured by a more faithful device. We assess this fidelity (a term we make precise in this paper) by running controlled experiments inside an anechoic chamber and analyzing the similarities and differences between the trace file from the device under study and those of additional "shadow" devices placed in its close proximity. Our results show that fidelity varies significantly across sniffers, both quantitatively and qualitatively, and that performance may also depend on the nature of the experiment under study and on slight changes of the sniffer position.

When there is no wired connectivity, wireless mesh networks (WMNs) can provide Internet access with lower cost and greater flexibility than traditional approaches. This has motivated the design of new protocols and algorithms for WMNs, and recently the deployment of experimental prototypes. In this paper we add to these previous works with the performance evaluation of a first CARMEN deployment, with the following distinguishing features: i) it is an indoor deployment, ii) it is used by real users to connect to the Internet, and iii) it is built using off-the-shelf hardware. The results show that mesh technology can provide users with a satisfactory Internet experience, and motives further research along this line.

In this paper we first present a model to analyze the average and standard deviation of the delay in a 802.11e EDCA WLAN under voice traffic. Next, based on this model, we compute the optimal configuration of the EDCA parameters. Specifically, with our optimal configuration we aim at admitting as many voice calls as possible while meeting a given quality criterion for the average delay and its typical deviation. Simulation results confirm the effectiveness of our optimal configuration.

As stateful flow-aware services are becoming commonplace, distributed router architectures have to quickly assign packets being forwarded to service-specialized processors in order to balance flow processing and state among them. Moreover, packets belonging to the same flow must be always assigned to the same CPU, even if some of the service processors become unavailable. This paper presents two novel fast robust hashing algorithms for persistent flow-to-CPU mapping, that require less hashing operations per packet than previous robust hash algorithms, thus being able to fulfill all the above requirements to implement flow-aware services at wire-speed.

Abstract — To this date, many works have been conducted to study the throughput and delay performance of WLANs under saturated conditions and to obtain the configuration that provides optimal performance under these conditions. From these previous works, however, it remains unclear whether this configuration is also appropriate for a WLAN operating under nonsaturation conditions. In this paper we present solid argu-ments which demonstrate that the optimal configuration resulting from saturation is also appropriate for a WLAN operating under nonsaturation conditions. Specifically, we show (via analysis and simulation) that a WLAN configured differently suffers from a number of performance anomalies when operating with finite sending rates. This is an important result for the configuration of WLAN parameters. I.

The service quality experienced by a user with the EDCA mechanism of the upcoming 802.11e standard depends on a number of configurable parameters, namely CWmin, CWmax, AIFS and TXOP_limit. WLAN stations are supposed to use the parameter configurations that the access point (AP) of the WLAN distributes with the beacon frames. However, a user can maliciously configure the parameters of his WLAN station in order to obtain a better service. In this paper, we address the issue of detecting malicious parameter configurations of EDCA. The AIFS and TXOP_limit parameters are relatively easy to control because of their deterministic nature. Given the capture effect, the CWmaxparameter may be unused by some users. Therefore, the key challenge lies in detecting if the CWminparameter of a station is well configured. The main contribution of this paper is the proposal of an algorithm to detect malicious CWminconfigurations. We show that, for an optimally configured WLAN, our algorithm is effective in avoiding that a user can substantially benefit from maliciously configuring his WLAN station without being detected