Green Wave Sleep Scheduling Algorithm in Wireless Network

Abstract

The nodes in a wireless network to sleep periodically can save energy, it also incurs higher latency and lower throughput. We consider the problem of designing optimal sleep schedules in wireless networks, and show that finding sleep schedules that can minimize the latency over a given subset of source-destination pairs is NP-hard. We proposed green-wave sleep-scheduling (GWSS)—inspired by synchronized traffic lights—for scheduling sleep-wake slots and routing data on dutycycling wireless adhoc networks. We also derive a latency lower bound given by d + O(1/p) for any sleep schedule with a required active rate (i.e., the fraction of active slots of each node) p, and the shortest path length d. We offer a novel solution to optimal sleep scheduling using green-wave sleep scheduling (GWSS), inspired by coordinated traffic lights, which is shown to meet our latency lower bound (hence is latency-optimal) for topologies such as the line, grid, ring, torus and tree networks, under light traffic. For high traffic loads, we propose non-interfering GWSS, which can achieve the maximum throughput scaling law given by T(n,p) = ¿(p/¿n) bits/sec on a grid network of size n, with a latency scaling law D(n,p) = O(¿n) + O(1/p).