Survey of Geographical Packet Forwarding In Wireless Sensor Networks Using Sleep Wake Pattern

In wireless sensor networks nodes follows sleepwake cycling policy. If a node wants to forward the packet to another node, it has to select a node from available nodes. Each relay is associated with a reward that gives the benefit of forwarding the packet using that relay. We have to develop a solution to this local problem, if that solution is adopted by every node, it should provide a reasonable heuristic for the end-to-end forwarding problem. Relay selection problem comprises a forwarding node has to select relays which follows asynchronous sleep wake cycling policy. At each relay wake-up instant the forwarder can choose to probe a relay to learn its reward value, based on this it can forward the packet or it can wait for other relays to wake up. The source objective is to select a relay so as to minimize a combination of waiting-delay, reward and probing cost. We formulate this relay selection problem as a Partially Observable Markov Decision Process (POMDP) and obtain some interesting structural results on the optimal policy. We also conduct simulation experiments and gain valuable insights into the performance of our local forwarding-solution. We can formulate this next problem as a Markov decision process (MDP). The exact optimal solution Best Forward can be found, but is not a better solution. Next we consider Simple Forward policy; Simulations show that SF performance is very close to the performance of BF, even for reasonably small node density. We then consider the end-to-end performance of SF in comparison with two external policies: Max Forward (MF) and First Forward (FF), and an end-to-end delay minimizing policy proposed by Kim et al (distributed bellman ford algorithm).