Sensor Queries: Algebraic Optimization for Time and Energy

Abstract

Sensor networks naturally apply to a broad range of applications that involve system monitoring and information tracking (e.g., airport security infrastructure, monitoring of children in metropolitan areas, product transition in warehouse networks, fine-grained weather/environmental measurements, etc.). Meanwhile, there are considerable performance deficiencies in applying existing sensornets in the applications that have stringent requirements for efficient mechanisms for querying sensor data and delivering the query result. The amount of data collected from all relevant sensors may be quite large and will require high data transmission rates to satisfy time constraints. It implies that excessive packet collisions can lead to packet losses and retransmissions resulting in significant energy costs and latency. In this paper we provide a formal consideration of a Data Transmission Algebra (DTA) that supports application-driven data interrogation patterns and optimization across multiple network layers. We use a logical framework to specify DTA semantics and to prove its soundness and completeness. Further, we prove that DTA query execution schedules have the key property of being collision-free. Finally, we describe and evaluate an algebraic query optimizer performing collision-aware query scheduling that both improve the response time and reduce the energy consumption.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

“…A noisy optimization problem for neuronal signaling in medical sensor-actuator networks was formulated in [ 189 ], where authors used heuristic algorithm to achieve a tradeoff between signaling latency and signaling robustness. A heuristic algorithm has been proposed in [ 190 ] to solve multi-objective optimization formulation for optimizing sensor queries. The authors have used the multi-objective technique to minimize the response time of queries and energy consumption of the networks.…”