TY - GEN
T1 - Understanding the capacity region of the greedy maximal scheduling algorithm in multi-hop wireless networks
AU - Joo, Changhee
AU - Lin, Xiaojun
AU - Shroff, Ness B.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=51349140934&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM.2007.165
DO - 10.1109/INFOCOM.2007.165
M3 - Conference contribution
AN - SCOPUS:51349140934
SN - 9781424420261
T3 - Proceedings - IEEE INFOCOM
SP - 1777
EP - 1785
BT - INFOCOM 2008
T2 - INFOCOM 2008: 27th IEEE Communications Society Conference on Computer Communications
Y2 - 13 April 2008 through 18 April 2008
ER -