Randomized binary exponential backoff (BEB) is a popular algorithm for coordinating access to a shared channel. With an operational history exceeding four decades, BEB is currently an important component of several wireless standards. Despite this track record, prior theoretical results indicate that under bursty traffic (1) BEB yields poor makespan and (2) superior algorithms are possible. To date, the degree to which these findings manifest in practice has not been resolved. To address this issue, we examine one of the strongest cases against BEB: @math packets that simultaneously begin contending for the wireless channel. Using Network Simulator 3, we compare against more recent algorithms that are inspired by BEB, but whose makespan guarantees are superior. Surprisingly, we discover that these newer algorithms significantly underperform. Through further investigation, we identify as the culprit a flawed but common abstraction regarding the cost of collisions. Our experimental results are complemented by analytical arguments that the number of collisions -- and not solely makespan -- is an important metric to optimize. We believe that these findings have implications for the design of contention-resolution algorithms.
Under continuous traffic, windowed backoff schemes are examined in @cite_67 with a focus on the tradeoff between throughput and fairness. The authors focus on polynomial backoff and demonstrate via analysis and NS2 (the predecessor to NS3) simulations that quadratic backoff is a good candidate with respect to both metrics.
@cite_67
1965978478 2011228372 2136340918 2107575014
This paper analyzes the worst-case performance of randomized backoff on simple multiple-access channels. Most previous analysis of backoff has assumed a statistical arrival model.For batched arrivals, in which all n packets arrive at time 0, we show the following tight high-probability bounds. Randomized binary exponential backoff has makespan Θ(nlgn), and more generally, for any constant r, r-exponential backoff has makespan Θ(nloglgr n). Quadratic backoff has makespan Θ((n lg n)3 2), and more generally, for r>1, r-polynomial backoff has makespan Θ((n lg n)1+1 r). Thus, for batched inputs, both exponential and polynomial backoff are highly sensitive to backoff constants. We exhibit a monotone superpolynomial subexponential backoff algorithm, called loglog-iterated backoff, that achieves makespan Θ(nlglg n lglglg n). We provide a matching lower bound showing that this strategy is optimal among all monotone backoff algorithms. Of independent interest is that this lower bound was proved with a delay sequence argument.In the adversarial-queuing model, we present the following stability and instability results for exponential backoff and loglog-iterated backoff. Given a (λ,T)-stream, in which at most n=λT packets arrive in any interval of size T, exponential backoff is stable for arrival rates of λ=O(1 lgn) and unstable for arrival rates of λ=Ω(lglgn lgn); loglog-iterated backoff is stable for arrival rates of λ=O(1 (lglgn )) and unstable for arrival rates of λ=Ω(1 lgn). Our instability results show that bursty input is close to being worst-case for exponential backoff and variants and that even small bursts can create instabilities in the channel. In this paper, a unified analytical framework is established to study the stability, throughput, and delay performance of homogeneous buffered IEEE 802.11 networks with Distributed Coordination Function (DCF). Two steady-state operating points are characterized using the limiting probability of successful transmission of Head-of-Line (HOL) packets p given that the network is in unsaturated or saturated conditions. The analysis shows that a buffered IEEE 802.11 DCF network operates at the desired stable point p=pL if it is unsaturated. pL does not vary with backoff parameters, and a stable throughput can be always achieved at pL. If the network becomes saturated, in contrast, it operates at the undesired stable point p=pA, and a stable throughput can be achieved at pA if and only if the backoff parameters are properly selected. The stable regions of the backoff factor q and the initial backoff window size W are derived, and illustrated in cases of the basic access mechanism and the request-to-send clear-to-send (RTS CTS) mechanism. It is shown that the stable regions are significantly enlarged with the RTS CTS mechanism, indicating that networks in the RTS CTS mode are much more robust. Nevertheless, the delay analysis further reveals that lower access delay is incurred in the basic access mode for unsaturated networks. If the network becomes saturated, the delay performance deteriorates regardless of which mode is chosen. Both the first and the second moments of access delay at pA are sensitive to the backoff parameters, and shown to be effectively reduced by enlarging the initial backoff window size W. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users. We present experimental results evaluating fairness of several proposals to change the TCP congestion control algorithm, in support of operation on high bandwidth-delay- product (BDP) network paths. We examine and compare the fairness of New Reno TCP BIC, cubic, hamilton-TCP, highspeed-TCP and Scalable-TCP. We focus on four different views of fairness: TCP-friendliness RTT-fairness, intra- and inter-protocol fairness.