The Medium Access Control protocol of Power Line Communication networks (defined in Homeplug and IEEE 1901 standards) has received relatively modest attention from the research community. As a consequence, there is only one analytical model that complies with the standardised MAC procedures and considers unsaturated conditions. We identify two important limitations of the existing analytical model: high computational expense and predicted results just prior to the predicted saturation point do not correspond to long-term network performance. In this work, we present a simplification of the previously defined analytical model of Homeplug MAC able to substantially reduce its complexity and demonstrate that the previous performance results just before predicted saturation correspond to a transitory phase. We determine that the causes of previous misprediction are common analytical assumptions and the potential occurrence of a transitory phase, that we show to be of extremely long duration under certain circumstances. We also provide techniques, both analytical and experimental, to correctly predict long-term behaviour and analyse the effect of specific Homeplug IEEE 1901 features on the magnitude of misprediction errors. Our simplified analysis is then used to model the priority resolution scheme defined in Homeplug IEEE 1901. We show that previous tendencies found in simulations and in an off-the-shelf testbed are correctly captured in our framework. We also show that resorting to the traffic differentiation provided by the different contention parameters alone solves the starvation faced by lower-access category traffic.
Two other analytic models of Homeplug exist in the literature ( @cite_25 and @cite_8 ). However, they model mechanisms that differ from the original standardised Homeplug procedure. In @cite_25 , the value of the contention window is fixed for all backoff stages, while in @cite_8 the backoff stage is incremented every time a new packet is overheard (thus having @math ). These new approaches obviously lead to a simplified analysis, as one of the dimensions of the Markov Chain is removed. However, the flexibility the standard provides by allowing to tune both the @math and @math is not captured by these frameworks.
@cite_25 @cite_8
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This paper analyzes the optimum constant contention window (CW) for the HomePlug 1.0 and AV CSMA CA MAC. A discrete time, homogenous Markov chain, with the state specified by both the backoff counter (BC) and deferral counter (DC), is used to model a single node contending for transmission. The structure of the Markov chain admits a generalized expression for the stationary state probability mass function (pmf) associated with each state. The recursively defined state pmfs can be analytically reduced to a single expression relating the probability p, of the node finding the medium idle, the maximum window size W, the maximum deferral counter size, and the number of nodes n. Optimizing the MAC efficiency provides a target value for p, which can be attained with the proper selection of W and. It is shown that an optimal contention window size can be chosen based on a linear relationship with the number of nodes. This study investigates replication of data in a novel streaming architecture consisting of ad-hoc networks of wireless devices. One application of these devices is home-to-home (H2O) entertainment systems where a device collaborates with others to provide each household with on-demand access to a large selection of audio and video clips. These devices are configured with a substantial amount of storage and may cache several clips for future use. A contribution of this study is a technique to compute the number of replicas for a clip based on the square-root of the product of bandwidth required to display clips and their frequency of access , i.e., where . We provide a proof to show this strategy is near optimal when the objective is to maximize the number of simultaneous displays in the system with string and grid (both symmetric and asymmetric) topologies. We say “near optimal” because values of less than 0.5 may be more optimum. In addition, we use analytical and simulation studies to demonstrate its superiority when compared with other alternatives. A second contribution is an analytical model to estimate the theoretical upper bound on the number of simultaneous displays supported by an arbitrary grid topology of H2O devices. This analytical model is useful during capacity planning because it estimates the capabilities of a H2O configuration by considering: the size of an underlying repository, the number of nodes in a H2O cloud, the representative grid topology for this cloud, and the expected available network bandwidth and storage capacity of each device. It shows that one may control the ratio of repository size to the storage capacity of participating nodes in order to enhance system performance. We validate this analytical model with a simulation study and quantify its tradeoffs. Link-layer fairness models that have been proposed for wireline and packet cellular networks cannot be generalized for shared channel wireless networks because of the unique characteristics of the wireless channel, such as location-dependent contention, inherent conflict between optimizing channel utilization and achieving fairness, and the absence of any centralized control. In this paper, we propose a general analytical framework that captures the unique characteristics of shared wireless channels and allows the modeling of a large class of system-wide fairness models via the specification of per-flow utility functions. We show that system-wide fairness can be achieved without explicit global coordination so long as each node executes a contention resolution algorithm that is designed to optimize its local utility function. We present a general mechanism for translating a given fairness model in our framework into a corresponding contention resolution algorithm . Using this translation, we derive the backoff algorithm for achieving proportional fairness in wireless shared channels, and compare the fairness properties of this algorithm with both the ideal proportional fairness objective, and state-of-the-art backoff-based contention resolution algorithms. We believe that the two aspects of the proposed framework, i.e. the ability to specify arbitrary fairness models via local utility functions, and the ability to automatically generate local contention resolution mechanisms in response to a given utility function, together provide the path for achieving flexible service differentiation in future shared channel wireless networks. In this paper, we focus on the Markov model of IEEE 802.11 distributed coordination function with power saving mode. The throughput evaluation is based on the model, with the comparison with the simulation result for validation. Furthermore, we notice that after each beacon transmission, there're more stations in contention than usual. Excessive contention results in high collision probability and low throughput. To solve this problem, we propose a downlink access scheme which can be used in both the basic access scheme and the access scheme with RTS CTS. This novel scheme enables AP to constrain the number of stations in contention to be an optimal value. Simulation results prove the performance improvement declared. The proposed scheme can be extended for multi-rate or multi-service WLANs.