Alberto Lopez Toledo

Adaptive Optimization of IEEE 802.11 DCF Based on Bayesian Estimation of the Number of Competing Terminals

The performance of the distributed coordination function (DCF) of the IEEE 802.11 protocol has been shown to heavily depend on the number of terminals accessing the distributed medium. The DCF uses a carrier sense multiple access scheme with collision avoidance (CSMA/CA), where the backoff parameters are fixed and determined by the standard. While those parameters were chosen to provide a good protocol performance, they fail to provide an optimum utilization of the channel in many scenarios. In particular, under heavy load scenarios, the utilization of the medium can drop tenfold. Most of the optimization mechanisms proposed in the literature are based on adapting the DCF backoff parameters to the estimate of the number of competing terminals in the network. However, existing estimation algorithms are either inaccurate or too complex. In this paper, we propose an enhanced version of the IEEE 802.11 DCF that employs an adaptive estimator of the number of competing terminals based on sequential Monte Carlo methods. The algorithm uses a Bayesian approach, optimizing the backoff parameters of the DCF based on the predictive distribution of the number of competing terminals. We show that our algorithm is simple yet highly accurate even at small time scales. We implement our proposed new DCF in the ns-2 simulator and show that it outperforms existing methods. We also show that its accuracy can be used to improve the results of the protocol even when the terminals are not in saturation mode. Moreover, we show that there exists a Nash equilibrium strategy that prevents rogue terminals from changing their parameters for their own benefit, making the algorithm safely applicable in a complete distributed fashion

Robust detection of selfish misbehavior in wireless networks

The CSMA/CA protocols are designed under the assumption that all participant nodes would abide to the protocol rules. This is of particular importance in distributed protocols such as the IEEE 802.11 distributed coordinating function (DCF), in which nodes control their own backoff parameters. In this work, we propose a method to detect selfish misbehaving terminals that may deliberately modify its backoff window to gain unfair access to the network resources. We develop nonparametric batch and sequential detectors based on the Kolmogorov-Smirnov (K-S) statistics that do not require any modification on the existing CSMA/CA protocols, and we apply it to detect misbehaviors in an IEEE 802.11 DCF network using the ns-2 simulator. We compare the performance of the proposed detectors with the optimum detectors with perfect information about the misbehavior strategy, for both the batch case (based on the Neyman-Pearson test), and the sequential case (based on Walds sequential probability ratio test). We show that the proposed nonparametric detectors have a performance comparable to the optimum detectors for the majority of misbehaviors (the more severe) without any knowledge of the misbehavior strategies.

Secure network coding for multi-resolution wireless video streaming

Emerging practical schemes indicate that algebraic mixing of different packets by means of random linear network coding can increase the throughput and robustness of streaming services over wireless networks. However, concerns with the security of wireless video, in particular when only some of the users are entitled to the highest quality, have uncovered the need for a network coding scheme capable of ensuring different levels of confidentiality under stringent complexity requirements. We show that the triple goal of hierarchical fidelity levels, robustness against wireless packet loss and efficient security can be achieved by exploiting the algebraic structure of network coding. The key idea is to limit the encryption operations to a critical set of network coding coefficients in combination with multi-resolution video coding. Our contributions include an information-theoretic security analysis of the proposed scheme, a basic system architecture for hierarchical wireless video with network coding and simulation results.

Fair WLAN backhaul aggregation

Aggregating multiple 802.11 Access Point (AP) backhauls using a single-radio WLAN card has been considered as a way of bypassing the backhaul capacity limit. However, current AP aggregation solutions greedily maximize the individual station throughput without taking fairness into account. This can lead to grossly unfair throughput distributions, which can discourage user participation and severely limit commercial deployability. Motivated by this problem, we present THEMIS, a single-radio station that performs multi-AP backhaul aggregation in a fair and distributed way, without requiring any change in the network. We implement THEMIS on commodity hardware, evaluate it extensively through controlled experimental tests, and validate it in a deployment spanning 3 floors of a multistory building. THEMIS is being used in a commercial trial by a major broadband provider to its customers.

Batch and Sequential Bayesian Estimators of the Number of Active Terminals in an IEEE 802.11 Network

The performance of the IEEE 802.11 protocol based on the distributed coordination function (DCF) has been shown to be dependent on the number of competing terminals and the backoff parameters. Better performance can be expected if the parameters are adapted to the number of active users. In this paper we develop both off-line and online Bayesian signal processing algorithms to estimate the number of competing terminals. The estimation is based on the observed use of the channel and the number of competing terminals is modeled as a Markov chain with unknown transition matrix. The off-line estimator makes use of the Gibbs sampler whereas the first online estimator is based on the sequential Monte Carlo (SMC) technique. A deterministic variant of the SMC estimator is then developed, which is simpler to implement and offers superior performance. Finally a novel approximate maximum a posteriori (MAP) algorithm for hidden Markov models (HMM) with unknown transition matrix is proposed. Realistic IEEE 802.11 simulations using the ns-2 network simulator are provided to demonstrate the excellent performance of the proposed estimators

Insomnia in the access: or how to curb access network related energy consumption

Access networks include modems, home gateways, and DSL Access Multiplexers (DSLAMs), and are responsible for 70-80% of total network-based energy consumption. In this paper, we take an in-depth look at the problem of greening access networks, identify root problems, and propose practical solutions for their user- and ISP-parts. On the user side, the combination of continuous light traffic and lack of alternative paths condemns gateways to being powered most of the time despite having Sleep-on-Idle (SoI) capabilities. To address this, we introduce Broadband Hitch-Hiking (BH2), that takes advantage of the overlap of wireless networks to aggregate user traffic in as few gateways as possible. In current urban settings BH2 can power off 65-90% of gateways. Powering off gateways permits the remaining ones to synchronize at higher speeds due to reduced crosstalk from having fewer active lines. Our tests reveal speedup up to 25%. On the ISP side, we propose introducing simple inexpensive switches at the distribution frame for batching active lines to a subset of cards letting the remaining ones sleep. Overall, our results show an 80% energy savings margin in access networks. The combination of B2 and switching gets close to this margin, saving 66% on average.

Robust Detection of MAC Layer Denial-of-Service Attacks in CSMA/CA Wireless Networks

Carrier-sensing multiple-access with collision avoidance (CSMA/CA)-based networks, such as those using the IEEE 802.11 distributed coordination function protocol, have experienced widespread deployment due to their ease of implementation. The terminals accessing these networks are not owned or controlled by the network operators (such as in the case of cellular networks) and, thus, terminals may not abide by the protocol rules in order to gain unfair access to the network (selfish misbehavior), or simply to disturb the network operations (denial-of-service attack). This paper presents a robust nonparametric detection mechanism for the CSMA/CA media-access control layer denial-of-service attacks that does not require any modification to the existing protocols. This technique, based on the -truncated sequential Kolmogorov-Smirnov statistics, monitors the successful transmissions and the collisions of the terminals in the network, and determines how ldquoexplainablerdquo the collisions are given for such observations. We show that the distribution of the explainability of the collisions is very sensitive to changes in the network, even with a changing number of competing terminals, making it an excellent candidate to serve as a jamming attack indicator. Ns-2 simulation results show that the proposed method has a very short detection latency and high detection accuracy.

Multipath TCP with Network Coding for Wireless Mesh Networks

In wireless multihop networks, techniques such as multipath, local retransmissions and network coding have been successfully used to increase throughput and reduce losses. However, while these techniques improve forwarding performance for UDP, they often introduce side effects such as packet reordering and delay that heavily affect TCP traffic. In this paper we introduce CoMP, a network coding multipath forwarding scheme that improves the reliability and the performance of TCP sessions in wireless mesh networks. CoMP exploits the wireless mesh path diversity using network coding, performs congestion control and uses a credit-based method to control the rate at which linear combinations are transmitted. CoMP uses a simple algorithm to estimate losses and to send redundant linear combinations in order to maintain the decoding delay at a minimum and to prevent TCP timeouts and retransmissions. We evaluate CoMP through extensive simulations and compare it to state-of-the-art protocols. We show that CoMP not only achieves a higher throughput, but also is more efficient than existing protocols, making TCP sessions feasible for wireless mesh networks even under heavy losses.

TCP performance over wireless MIMO channels with ARQ and packet combining

Multiple-input multiple-output (MIMO) wireless communication systems that employ multiple transmit and receive antennas can provide very high-rate data transmissions without increase in bandwidth or transmit power. For this reason, MIMO technologies are considered as a key ingredient in the next generation wireless systems, where provision of reliable data services for TCP/IP applications such as wireless multimedia or Internet is of extreme importance. However, while the performance of TCP has been extensively studied over different wireless links, little attention has been paid to the impact of MIMO systems on TCP. This paper provides an investigation on the performance of modern TCP systems when used over wireless channels that employ MIMO technologies. In particular, we focus on two representative categories of MIMO systems, namely, the BLAST systems and the space-time block coding (STBC) systems, and how the ARQ and packet combining techniques impact on the overall TCP performance. We show that, from the TCP throughput standpoint, a more reliable channel may be preferred over a higher spectral efficient but less reliable channel, especially under low SNR conditions. We also study the effect of antenna correlation on the TCP throughput under various conditions.

Efficient Multipath in Sensor Networks using Diffusion and Network Coding

In this paper we propose to employ the use of network coding to achieve an adaptive equivalent solution to the construction of disjoint multipath routes from a source to a destination. It exploits both the low cost mesh-topology construction, such as those obtained by diffusion algorithms, and the capacity achieving capability of linear network coding. We present a simple randomized network coding scheme that can be efficiently employed in sensor networks, solving two of its main problems: knowledge of the underlying network capacity and rate control. Our solution easily adapts to the changing conditions of the network and it can be used by the sinks to increase or decrease capacity and reliability on demand.