In hybrid wireless sensor networks composed of both static and mobile sensor nodes, the random deployment of stationary nodes may cause coverage holes in the sensing field. Hence, mobile sensor nodes are added after the initial deployment to overcome the coverage holes problem. To achieve optimal coverage, an efficient algorithm should be employed to find the best positions of the additional mobile nodes. This paper presents a genetic algorithm that searches for an optimal or near optimal solution to the coverage holes problem. The proposed algorithm determines the minimum number and the best locations of the mobile nodes that need to be added after the initial deployment of the stationary nodes. The performance of the genetic algorithm was evaluated using several metrics, and the simulation results demonstrated that the proposed algorithm can optimize the network coverage in terms of the overall coverage ratio and the number of additional mobile nodes.
In this paper, the performance of JPEG image compression and transmission using TinyOS-based Imote2 wireless sensor network platform is experimentally evaluated via a newly developed testbed. This testbed supports multihop sensor networks based on the Imote2 platform equipped with the Imote2 Multimedia Sensor Board. In addition, a standard JPEG library is embedded into the Imote2 platform to provide in-node image compression. The processing and transmission times, power consumption, and peak-signal-to-noise ratio performance metrics measurements are reported. The results show that the processing requirements are less than those of the transmission. According to the results, a tradeoff between the image quality and the energy and delay costs may be obtained.
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