Analyzing the Performance of Greedy Maximal Scheduling via Local Pooling and Graph Theory

—Efficient operation of wireless networks and switches requires using simple (and in some cases distributed) scheduling algorithms. In general, simple greedy algorithms (known as Greedy Maximal Scheduling - GMS) are guaranteed to achieve only a fraction of the maximum possible throughput (e.g., 50% throughput in switches). However, it was recently shown that in networks in which the Local Pooling conditions are satisfied, GMS achieves 100% throughput. Moreover, in networks in which the σLocal Pooling conditions hold, GMS achieves σ% throughput. In this paper, we focus on identifying the specific network topologies that satisfy these conditions. In particular, we provide the first characterization of all the network graphs in which Local Pooling holds under primary interference constraints (in these networks GMS achieves 100% throughput). This leads to a polynomial time algorithm for identifying Local Pooling-satisfying graphs. Moreover, by using similar graph theoretical method...

• Type: Journal
• Year: 2010
• Where: INFOCOM
• Authors: Berk Birand, Maria Chudnovsky, Bernard Ries, Paul D. Seymour, Gil Zussman, Yori Zwols
• Keywords: Algorithms, Communications, INFOCOM 2010, Pooling Conditions, Throughput