Online surrogate problem methodology for stochastic discrete resource allocation problems
Journal of Optimization Theory and Applications
Medium access control with coordinated adaptive sleeping for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Simulating the power consumption of large-scale sensor network applications
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
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We address the problem of batching messages generated at nodes of a sensor network for the purpose of reducing communication energy at the expense of added latency. We consider a time-based batching approach. We first develop baseline analytical models based on Markovian assumptions, derive conditions under which batching is profitable, and explicitly determine a batching time that optimizes a performance metric capturing the trade-off between communication energy and message latency. We then provide an on-line performance optimization method based on Smoothed Perturbation Analysis (SPA) for estimating the performance sensitivity with respect to the controllable batching time. We prove that the SPA gradient estimator is unbiased and combine it with a Stochastic Approximation (SA) algorithm for on-line optimization. Numerical results are provided for Poisson and Markov modulated Poisson message arrival processes and illustrate the effectiveness of the message batching scheme.