Martin Zubeldia

Overcoming performance pitfalls in rate-diverse high speed WLANs

Recent developments on the IEEE 802.11 family of standards promise significant increases in speed by incorporating multiple enhancements at the physical layer. These high modulation speeds apply to the data portion of the transmitted frames, while headers must remain at lower speeds; this has motivated the use of frame aggregation to increase data payloads in the newer standards. However, this simple method may still utterly fail to deliver the promised speeds, due to a series of cross-layer effects involving the transport and multiple access layers: the downward equalization of throughputs imposed by TCP under physical rate diversity, the excessive impact of the TCP ACK stream, or the unreasonable fraction of access opportunities taken by uplink flows when competing with the more numerous downlink connections. A first contribution of this paper is to demonstrate these impediments and isolate their causes through a series of experiments with the ns3 packet simulator, on the 802.11n and 802.11ac protocol versions.Our analysis leads us to propose a desirable resource allocation for situations of rate-diverse competition, and an architecture for control at the access-point to achieve it. Our implementation is compatible with the standard, involving a combination of known techniques: packet aggregation, multiple queues with TCP-ACK isolation, and control of the MAC contention window. The main contribution here is to provide a practical, comprehensive solution that imposes the desired efficiency and fairness model addressing all the previously indicated limitations. We demonstrate analytically and through extensive simulation that our method is able to provide significant enhancements in performance under a variety of traffic conditions.

Neighbor selection for proportional fairness in P2P networks

This paper analyzes reciprocation strategies in peer-to-peer networks from the point of view of the resulting resource allocation. Our stated aim is to achieve through decentralized interactions a weighted proportionally fair allocation. We analyze the desirable properties of such allocation, as well as an ideal proportional reciprocity algorithm to achieve it, using tools of convex optimization. We then seek suitable approximations to the ideal allocation which impose practical constraints on the problem: numbers of open connections per peer, with transport layer-induced bandwidth sharing, and the need of random exploration of the peer-to-peer swarm. Our solution in terms of a Gibbs sampler dynamics characterized by a suitable energy function is implemented in simulation, comparing favorably with a number of alternatives.

Proportional fairness in heterogeneous peer-to-peer networks through reciprocity and Gibbs sampling

This paper studies peer-to-peer networks with the objective of imposing a proportionally fair allocation of peer upload capacity. We begin with a tutorial review on the feasibility of achieving these allocations with idealized assumptions on connectivity and rate control, as well as a distributed algorithm based on peer reciprocity that can achieve it. To impose some of the constraints of real networks (limited number of connections, with bandwidth imposed by lower layers) we introduce an energy function that measures the deviations from ideal reciprocity, and analyze methods to minimize this energy in a decentralized way. To avoid combinatoric difficulties, as well as to enable new peer exploration, we use a Gibbs sampler approach, in which a Markov chain is designed with stationary distribution determined by our energy function. This proposal is implemented and tested in simulation, and results are compared with other existing and proposed P2P exchange systems.

Trading off efficiency and reciprocity in wireless peer-to-peer file sharing

This paper considers the problem of allocating exchange rates in peer-to-peer dissemination, which must consider the dual objectives of throughput efficiency and reciprocity between peers, the latter essential to cooperation incentives. This question has been studied in prior research for wired networks under an upload constraint, where the focus is on achieving reciprocity through decentralized peer interactions. We consider here a wireless network substrate, for which link capacities are non-uniform according to the peering choice, and exchanges may be subject to interference. A convex optimization problem is formulated that trades off efficiency and reciprocity, and various schemes are investigated to achieve a decentralized solution.

Dynamics of heterogeneous peer-to-peer networks

The most tractable models of population dynamics in peer-to-peer file sharing systems apply to a single class of peers with homogeneous network access parameters. When upload bandwidths are heterogeneous, reciprocity mechanisms lead to non-uniform download rates and a more complex multi-class dynamics. We consider first a model where mutual download bandwidths are allocated in proportion to the upload speed, plus a uniformly distributed server component. For an ordinary differential equation model of the multi-class peer populations, we characterize the equilibrium and establish its global stability, invoking results from monotone systems. We also analyze a partial differential equation model that tracks download progress of the populations; we establish the local asymptotic stability of the equilibrium. Finally, we extend the ODE model to include a mix of proportional and uniform bandwidth allocation, which better describes the mechanisms of BitTorrent systems; again we characterize equilibrium configurations and give a partial result on local stability.

Averting speed inefficiency in rate-diverse WiFi networks through queueing and aggregation

IEEE 802.11n, the latest version of the widely used standard for wireless LANs, promises significant increases in speed by incorporating multiple enhancements at the physical layer. In this paper we demonstrate that, on the contrary, the straightforward deployment of 802.11n in conjunction with TCP over a simple, single access-point network, can dramatically underachieve the promised speeds. Part of the deficiency is due to overheads and can be improved by the technique of packet aggregation present in the standard. However more subtle problems are identified, in particular the downward equalization of throughputs that occurs under physical rate diversity, or the unreasonable portion of resources taken by uplink flows when competing with the more numerous downlink connections. These difficulties are demonstrated and their causes explained through a sequence of experiments with the ns3 packet simulator. Our analysis leads us to propose a desirable resource allocation for these situations of competition, and an architecture for control in the access-point to achieve it. Our solution involves a combination of packet aggregation, multiple queues and TCPACK isolation, compatible with the standard and where all the control resides at the AP. We demonstrate analytically and through extensive simulation that our method is able to provide significant enhancements in performance under a variety of traffic conditions.

Delay Scaling in Many-Sources Wireless Networks without Queue State Information

We examine a canonical scenario where several wireless data sources generate sporadic delay-sensitive messages that need to be transmitted to a common access point. The access point operates in a time-slotted fashion, and can instruct the various sources in each slot with what probability to transmit a message, if they have any. When several sources transmit simultaneously, the access point can detect a collision, but is unable to infer the identities of the sources involved. While the access point can use the channel activity observations to obtain estimates of the queue states at the various sources, it does not have any explicit queue length information otherwise. We explore the achievable delay performance in a regime where the number of sources n grows large while the relative load remains fixed. We establish that, under any medium access algorithm without queue state information, the average delay must be at least of the order of n slots when the load exceeds some threshold lambda* < 1. This demonstrates that bounded delay can only be achieved if a positive fraction of the system capacity is sacrificed. Furthermore, we introduce a scalable Two-Phase algorithm which achieves a delay upper bounded uniformly in n when the load is below e -1 , and a delay of the order of n slots when the load is between e -1 and 1. Additionally, this algorithm provides robustness against correlated source activity.

Reciprocity and Efficiency in Peer Exchange of Wireless Nodes Through Convex Optimization

This paper considers the allocation of exchange rates in a network of wireless nodes which engage in peer-to-peer dissemination. Here, in addition to the desirable throughput efficiency, it is important to ensure a level of rate reciprocity between peers, an issue that has been studied before only for wired networks. For the wireless substrate efficiency and reciprocity may be in conflict, due to the non-uniform link capacities of different peering choices, and the possible interference between them. We use convex optimization to formulate a relevant tradeoff, measuring reciprocity through a Kullback-Leibler divergence between sent and received rates. We propose decentralized methods which involve peer-to-peer interactions, and are shown to converge to the corresponding tradeoff point. Illustrative simulations are provided.