Distributed Weighted Node Shortest Path Routing for Wireless Sensor Networks

Routing in Wireless Sensor Networks contains challenges, including limited energy constraints, network density, wireless channel errors. Different approaches exist in literature to overcome these challenges, such as data centric, location based and hierarchical routing. Most routing protocols in Wireless Sensor Networks are dealing with energy efficiency and network lifetime. In this paper, we present a shortest path routing algorithm based on Chandy-Misra’s distributed shortest path algorithm regarding both node weight and edge weight. X percent of edge’s weight and (100 - X) percent of node’s weight form a total cost between neighbor and source node which is used in order to generate the shortest paths and construct a spanning tree. Variation of X percent, node weight and edge weight provide resilience for shaping needed paths and change the spanning tree’s structure. When at least one node is close to critical energy level or a fault occurs, the routing algorithm is re-executed and new paths are generated. In order to obtain energy efficient paths, high network lifetime and finding out the overheads, we analyze the simulation results by assigning the battery level to node weight, communication cost to edge weight and %10, %30, %60 and %80 to X separately.