Hierarchical power management in disruption tolerant networks using traffic-aware optimization

Recent efforts in Disruption Tolerant Networks (DTNs) have shown that mobility can be a powerful means for delivering messages in highly-challenged environments. DTNs are wireless mobile networks that are particularly useful in sparse environments where the density of nodes is insufficient to support direct end-to-end communication. Unfortunately, many mobility scenarios depend on untethered devices with limited energy supplies. Without careful management, depleted energy supplies will degrade network connectivity and counteract the robustness gained by mobility. A primary concern is the energy consumed by wireless communication, and in particular the energy consumed in searching for other nodes to communicate with. In this paper we examine a hierarchical radio architecture in which nodes are equipped with two complementary radios: a long-range, high-power radio and a short-range, low-power radio. In this architecture energy can be conserved by using the low-power radio to discover communication opportunities with other nodes and waking the high-power radio to undertake data transmission. We develop a generalized power management framework for controlling the wake-up intervals of the two radios. In addition, we show how to incorporate knowledge of the traffic load, and we devise approximation algorithms to control the sleep/wake-up cycling to provide maximum energy conservation while discovering enough communication opportunities to handle that load. We evaluate our schemes through simulation under various mobility scenarios. Our results show that our generalized power management scheme can tune wake-up intervals of the two radios to balance energy efficiency and delivery performance. Also, when traffic load can be predicted, our approximation algorithms reduce energy consumption from 60% to 99% compared to no power management.