Local pooling conditions for joint routing and scheduling

A major challenge in the design and operation of wireless networks is to jointly route packets and schedule transmissions to efficiently share the common spectrum among links in the same area. Due to the lack of central control in wireless networks, these algorithms have to be decentralized. It was recently shown that distributed (greedy) algorithms can usually guarantee only fractional throughput. It was also recently shown that if a set of conditions regarding the network topology (known as Local Pooling) is satisfied, simple distributed maximal weight (greedy) scheduling algorithms achieve 100% throughput. In this paper, we focus on networks in which packets have to undergo multihop routing and derive multihop local pooling conditions for that setting. In networks satisfying these conditions, a backpressure-based joint routing and scheduling algorithm employing maximal weight scheduling achieves 100% throughput.