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An autonomic framework for reliable multicast: A game theoretical approach based on social psychology

Published:30 November 2009Publication History
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Abstract

A major challenge in wireless terrestrial networks is to provide large-scale reliable multicast and broadcast services. The main problem limiting the scalability of such networks is feedback implosion, a problem arising when a large number of users transmit their feedback messages through the network, occupying a significant portion of system resources.

Inspired by social psychology, specifically from the bystander effect phenomenon, an autonomic framework for large-scale reliable multicast services is presented. The self-configuring and self-optimizing procedures of the proposed autonomic scheme are modeled using game theory. Through appropriate modeling and simulations of the proposed scheme carried out to evaluate its performance, it is found that the new approach suppresses feedback messages very effectively, while at the same time, it does not degrade the timely data transfer.

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  1. An autonomic framework for reliable multicast: A game theoretical approach based on social psychology

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                        Bernard Kuc

                        Most studies on game theory make for interesting reading. There is something intuitively appealing about a theory that inspires curiosity and attempts to apply it to every known problem. The authors apply game theory by having mobile devices attempt to maximize their utility by refraining from sending feedback messages to a multicast source. This not only reduces power consumption on the device, but also prevents the flooding of the network when great masses of multicast subscribers respond at the same time. The principle is simple. If a mobile subscriber does not send a reply, it saves power, but risks not receiving a retransmission. The more subscribers there are, the more likely it is that another subscriber will send the reply. Since this scheme is only valid within a small range of subscribers and packet-loss scenarios, the authors run three additional algorithms. The first one is a backup mechanism that uses a randomized timer to deal with cases where there are so many subscribers, each subscriber assumes someone else will send the reply?in fact, no one does. In the second, an adaptive overlay algorithm at the multicast source monitors the number of subscribers and feedback messages, and then overrides the subscriber algorithm with the third one?a plain probabilistic transmission algorithm?when too many replies are sent. Figure 9 presents the simulated results for a worldwide interoperability for microwave access (WiMAX) network: the benefits provided by the utility maximization algorithm are small and occur only over a limited range, once the other three algorithms are added to the mix. For readers, this is the paper's most useful information. Online Computing Reviews Service

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