Energy Efficient Search in Sensor Networks Using Simple Random Walks with Level Biased Steps

Abstract

Random walk is one of the widely used techniques for information discovery in unstructured networks like Ad hoc Wireless Networks (AWNs) and Wireless Sensor Networks (WSNs). In a Random walk, instead of taking all steps uniform randomly, our idea is to modify Random walk to take some level biased steps to improve its energy efficiency and latency which are important design parameters in WSNs. The level of a node is defined as the minimum number of hops required for a packet to reach the sink node from that node. We propose two walk based search protocols viz., Several Short Random Walks (SSRW) search and Random Walk with Level Biased Jumps (RWLBJ) search, that use a combination of uniform random and level biased steps for energy efficient search in WSNs. The idea is that the biased steps in the proposed protocols decrease the correlation among visited sensor nodes which increases the node coverage of the protocols. We show by theoretical analysis that using biased steps in Random walks increases their efficiency in terms of energy consumption and latency of search. We also show by extensive simulations that SSRW and RWLBJ are better choices compared to that of pure Random walk in terms of the energy consumption and latency of search.