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Joo, Changhee
Learning, Modeling, and Networking
Research Interests
  • Learning, modeling, networking, resource allocation, stochastic optimization, distributed computing, low complexity

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Understanding the capacity region of the Greedy maximal scheduling algorithm in multihop wireless networks

Cited 45 times inthomson ciCited 63 times inthomson ci
Title
Understanding the capacity region of the Greedy maximal scheduling algorithm in multihop wireless networks
Author
Joo, ChangheeLin, XiaojunShroff, Ness B.
Keywords
Capacity region; communication systems; greedy maximal scheduling (GMS); longest queue first; multihop wireless networks
Issue Date
2009-08
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
IEEE-ACM TRANSACTIONS ON NETWORKING, v.17 , no.4, pp.1132 - 1145
Abstract
In this paper, we characterize the performance of an important class of scheduling schemes, called greedy maximal scheduling (GMS), for multihop wireless networks. While a lower bound on the throughput performance of GMS has been well known, empirical observations suggest that it is quite loose and that the performance of GMS is often close to optimal. In this paper, we provide a number of new analytic results characterizing the performance limits of GMS. We first provide an equivalent characterization of the efficiency ratio of GMS through a topological property called the local-pooling factor of the network graph. We then develop an iterative procedure to estimate the local-pooling factor under a large class of network topologies and interference models. We use these results to study the worst-case efficiency ratio of GMS on two classes of network topologies. We show how these results can be applied to tree networks to prove that GMS achieves the full capacity region in tree networks under the K-hop interference model. Then, we show that the worst-case efficiency ratio of GMS in geometric unit-disk graphs is between 1/6 and 1/3.
URI
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DOI
10.1109/TNET.2009.2026276
ISSN
1063-6692
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