Spatial fairness in linear random-access networks

Performance Evaluation(2012)

Cited 21|Views0
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Abstract
Random-access networks may exhibit severe unfairness in throughput, in the sense that some nodes receive consistently higher throughput than others. Recent studies show that this unfairness is due to local differences in the neighborhood structure: nodes with fewer neighbors receive better access. We study the unfairness in saturated linear networks, and adapt the random-access CSMA protocol to remove the unfairness completely, by choosing the activation rates of nodes as a specific function of the number of neighbors. We then investigate the consequences of this choice of activation rates on the network-average saturated throughput, and we show that these rates perform well in non-saturated settings.
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Key words
non-saturated setting,linear network,local difference,higher throughput,fewer neighbor,better access,csma,activation rate,random-access,spatial fairness,neighborhood structure,wireless networks,random-access network,loss networks,linear random-access network,throughput,markov processes,severe unfairness,loss network,markov process,wireless network,random access
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