A sensor is a small electronic device which has the ability to sense, compute and communicate either with other sensors or directly with a base station (sink). In a wireless sensor network (WSN), the sensors monitor a region and transmit the collected data packets through routes to the sinks. In this study, we propose a mixed-integer linear programming (MILP) model to maximize the number of time periods that a WSN carries out the desired tasks with limited energy and budget. Our sink and sensor placement, scheduling, routing with connected coverage (SP SRC) model is the first in the literature that combines the decisions for the locations of sinks and sensors, activity schedules of the deployed sensors, and data flow routes from each active sensor to its assigned sink for connected coverage of the network over a finite planning horizon. The problem is NP-hard and difficult to solve even for small instances. Assuming that the sink locations are known, we develop heuristics which construct a feasible solution of the problem by gradually satisfying the constraints. Then, we introduce search heuristics to determine the locations of the sinks to maximize the network lifetime. Computational experiments reveal that our heuristic methods can find near optimal solutions in an acceptable amount of time compared to the commercial solver CPLEX 12.7.0.
Recent research as in REF has developed a heuristic to improve the network life time, by determining the locations of sinks.
Sensor and Sink Placement, Scheduling and Routing Algorithms for Connected Coverage of Wireless Sensor Networks
ArXiv
ArXiv
Computer Science Engineering