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Register a new userApproximate Aggregate Utility Maximization in Multi-Hop Wireless Networks using Distributed Greedy Scheduling
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Added by
Albert Sunny
Publication date
2011
fields
Informatics Engineering
and research's language is
English
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In this paper, we study the performance of greedy scheduling in multihop wireless networks, where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. The dual can be solved optimally, only with the knowledge of the maximal independent sets in the network. But computation of maximal independent sets is known to be NP-hard. Motivated by this, we propose a distributed greedy heuristic to address the problem of link scheduling. We evaluate the effect of the distributed greedy heuristic on aggregate utility maximization in detail, for the case of an arbitrary graph. We provide some insights into the factors affecting aggregate utility maximization in a network, by providing bounds on the same. We give simulation results for the approximate aggregate utility maximization achieved under distributed implementation of the greedy heuristic and find them close to the maximum aggregate utility obtained using optimal scheduling.
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Control of multihop Wireless networks in a distributed manner while providing end-to-end delay requirements for different flows, is a challenging problem. Using the notions of Draining Time and Discrete Review from the theory of fluid limits of queues, an algorithm that meets delay requirements to various flows in a network is constructed. The algorithm involves an optimization which is implemented in a cyclic distributed manner across nodes by using the technique of iterative gradient ascent, with minimal information exchange between nodes. The algorithm uses time varying weights to give priority to flows. The performance of the algorithm is studied in a network with interference modelled by independent sets.
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