Latency Minimizing Tasking for Information Processing Systems

Real-time cyber-physical systems and information processing clusters require system designers to consider the total latency involved in collecting and aggregating data. For example, applications such as wild-fire monitoring require data to be presented to users in a timely manner. However, most models and algorithms for sensor networks have focused on alternative metrics such as energy efficiency. In this paper, we present a new model of sensor network aggregation that focuses on total latency. Our model is flexible and enables users to configure varying transmission and computation time on a node-by-node basis, and thus enables the simulation of complex computational phenomena. In addition, we present results from three tasking algorithms that trade-off local communication for overall latency performance. These algorithms are evaluated in simulated networks of up to 200 nodes.