Accurately Predicting Residual Energy Levels in MANETs

To support energy-efficient routing, accurate state information about energy level should be available. But due to bandwidth constraints, communication costs, high loss rate and the dynamic topology of MANETs, collecting and maintaining up-to-date state information is a non-trivial task. In this work, we use Optimized Link State Routing (OLSR) as the underlying routing protocol and focus on residual energy level as QoS metric, which has been used for routing decisions in many energy-efficient routing protocol proposals. Our experiments show that nodes have at best imprecise state information, especially under high traffic rates. We propose and evaluate two additional techniques to reduce inaccuracies and compare them against the basic OLSR protocol. These techniques show significant improvements in accuracy levels. In particular, a technique we call Smart Prediction achieves highly accurate perceived residual energy levels under all traffic loads, mobility scenarios, and radio models.