Abstract
In sensor networks (SNs), how to allocate the limited resources so as to optimize data gathering and network utility is an important and challenging task. This chapter introduces a hybrid event-time-driven communication and updating scheme, with which sensor network optimization problems can be solved. A distributed hybrid driven optimization algorithm based on the coordinate descent method is presented. The proposed optimization algorithm differs from the existing ones since the hybrid driven scheme allows more choices of actuation time, resulting a tradeoff between communications and computation performance. Applying the proposed algorithm, each sensor node is driven in a hybrid event time manner, which removes the requirement of strict time synchronization. The convergence and optimality of the proposed algorithm are analyzed, and verified by simulation examples. The developed results also show the tradeoff between communications and computation performance.
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