NDLI: Understanding the Capacity Region of the Greedy Maximal Scheduling Algorithm in Multi-Hop Wireless Networks

Content Provider	IEEE Xplore Digital Library
Author	Changhee Joo Xiaojun Lin Shroff, N.B.
Copyright Year	2008
Description	Author affiliation: Depts. of ECE & CSE, Ohio State Univ., Columbus, OH (Changhee Joo)
Abstract	In this paper, we characterize the performance of an important class of scheduling schemes, called greedy maximal scheduling (GMS), for multi-hop wireless networks. While a lower bound on the throughput performance of GMS is relatively well-known in the simple node-exclusive interference model, it has not been thoroughly explored in the more general K-hop interference model. Moreover, empirical observations suggest that the known bounds are 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. First, 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. Second, we show that the worst-case efficiency ratio of GMS in geometric network graphs is between 1/6 and 1/3.
Starting Page	1103
Ending Page	1111
File Size	283025
Page Count	9
File Format	PDF
ISBN	9781424420254
ISSN	0743166X
DOI	10.1109/INFOCOM.2008.165
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Scheduling algorithm Spread spectrum communication Wireless networks Interference Network topology Throughput Tree graphs Solid modeling Communications Society Peer to peer computing
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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