This grant provides funding for creating and analyzing mathematical models of large-scale wireless sensor networks (WSNs). A WSN is a collection of sensing devices linked via a wireless transmission medium for the purpose of sensing and conveying information about objects, their surroundings, and their interactions, without human intervention. When the information is time sensitive, the network?s performance capabilities are critical to meeting quality-of-service guarantees. However, assessing network performance is difficult because the location of the data is generally not known a priori, or it may not exist in the network at all, sensors have limited energy reserves and fail when these reserves are exhausted, sensors may fail due a harsh operating environment, and communication channel quality may vary with time, impacting the timely delivery of critical data. These characteristics distinguish sensor networks from other communication networks and significantly complicate the task of modeling and predicting their performance over time. If successful, the results of this research will lead to fundamental principles, effective algorithms and optimization schemes that will enhance the design, analysis, control and realization of WSNs. Using a queueing network-based model, specific performance parameters will be investigated including the network energy expenditure, average time required to respond to queries and the query success rate (the proportion of queries that are answered on time). The sensitivity of the network?s performance to query deadline distributions, sensor failures and the network?s environment will also be assessed. Finally, optimization of the network?s parameters will be investigated to ensure resilience in various operating environments.
