Optimal deployment of actors using Simulated Annealing within WSAN

This paper focuses on the automatic placement of actors within wireless sensor-actor networks with the conscious to minimize the cost and maximize the sensor-actor binding ratio. A wireless sensor-actor network (WSAN) comprises of sensors to gather information from their surrounding environment and actors to perform pertinent actions upon the environment, after processing the sensors´ data. The resource-rich actors are deployed to increase the processing and communication capabilities, thereby saving the energy and extending the lifespan of WSAN. We have assumed that sensor nodes are to communicate directly to the respective actors. The actor placement problem is to select a minimal set of actors and their optimal locations within WSAN, keeping in mind the communication requirements between sensors and actors. We have encoded the actor placement problem into the Simulated Annealing (SA) approach, to optimize the total number of actors covering as many sensors as possible subject to cost and performance constraints. Our experimental results demonstrate the feasibility of SA in searching the space of the actor placement problem by maintaining 80% sensor-actor coverage range throughout the experiments with optimal network cost. We also have carried out a sensitivity analysis in the selection of SA parameter, such as the cooling rate (α), to study its effect on the performance.