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We consider a wireless sensor network whose main function is to detectcertain infrequent alarm events, and to forward alarm packets to a basestation, using geographical forwarding. The nodes know their locations, andthey sleep-wake cycle, waking up periodically but not synchronously. In thissituation, when a node has a packet to forward to the sink, there is atrade-off between how long this node waits for a suitable neighbor to wake upand the progress the packet makes towards the sink once it is forwarded to thisneighbr. Hence, in choosing a relay node, we consider the problem of minimizingaverage delay subject to a constraint on the average progress. By constraintrelaxation, involving a Lagrange multiplier, we formulate this next hop relayselection problem as a Markov decision process (MDP). The exact optimalsolution (BF (Best Forward)) can be found, but is computationally intensive.Next, we consider a mathematically simplified model for which the optimalpolicy (SF (Simplified Forward)) turns out to be a simple one-step-look-aheadrule. Simulations show that SF is very close in performance to BF, even forreasonably small node density. We then study the end-to-end performance of SFin comparison with two extremal policies: Max Forward (MF), which makes themaximum possible progress per hop and thus reduces network energy consumption,and First Forward (FF), which forwards the packet to the first node to wake up,and thus tends to make end-to-end forwarding delays small. We find that, withappropriate choice of one hop average progress constraint, SF can be tuned toprovide a favorable trade-off between end-to-end packet delay and the number ofhops in the forwarding path.

Tunable locally-optimal geographical forwarding in wireless sensor networks with sleep-wake cycling nodes