Optimal QoS-aware Sleep/Wake Scheduling for Time-Synchronized Sensor Networks

Yan Wu, Sonia Fahmy, Ness Shroff
2006 2006 40th Annual Conference on Information Sciences and Systems  
We study sleep/wake scheduling for low-duty cycle sensor networks. Our work is different from most previous works in that we explicitly consider the effect of synchronization error in the design of the sleep/wake scheduling algorithm. Prior work on sleep/wake scheduling has either assumed that an underlying synchronization protocol can provide perfect synchronization, or assumed an upper bound on the clock disagreement, and used it as a guard time. However, for a widely used synchronization
more » ... me we show that its error is non-negligible, and and using a conservative guard time is energy wasteful. We thus conclude that the design of any sleep/wake scheduling algorithm must take into account the impact of the synchronization error, and study the optimal sleep/wake scheduling scheme with consideration of the synchronization error. Our work includes two parts. In the first part, we show that there is an inherent trade-off between energy consumption and message delivery performance (defined as the message capture probability in this work). We formulate an optimization problem to minimize the expected energy consumption, with the constraint that the message capture probability should be no less than a threshold. In the first part, we assume the threshold is already given. We find that the problem is non-convex, thus cannot be directly solved by conventional convex optimization techniques. By investigating the unique * -Yan Wu and Sonia Fahmy are also with the † -This research has been sponsored in part by NSF grants ANI-0238294 (CAREER) and ANI-0207728, an Indiana 21st century grant, and a Tellabs foundation fellowship. structure of the problem, we transform the non-convex problem into a convex equivalent, and solve it using an efficient search method. Simulation results show that our scheme significantly outperforms schemes that do not intelligently consider the synchronization error. Next in the second part, we remove the assumption that the capture probability threshold is already given, and study how to decide it to meet the Quality of Services (QoS) requirement of the application. We observe that in many sensor network applications, a group of sensors collaborate to perform common task(s). Therefore, the QoS is usually not decided by the performance of any individual node, but by the collective performance of all the related nodes. To achieve the collective performance with minimum energy consumption, intuitively we should provide differentiated services for the nodes and favor more important ones. We thus formulate an optimization problem, which aims to set the capture probability threshold for messages from each individual node such that the expected energy consumption is minimized, and still the collective performance is guaranteed. The problem turns out to be non-convex and hard to solve exactly. Therefore, we use approximation techniques to obtain a suboptimal solution that approximates the optimum. Simulations show that our approximate solution significantly outperforms a scheme without differentiated treatment of the nodes.
doi:10.1109/ciss.2006.286599 fatcat:36wbse7isjfcvfq6ghtnv4bzba