Optimize Multiple Mobile Elements Touring in Wireless Sensor Networks

Integrating mobility into WSNs can significantly reduce the energy consumption of sensor nodes. However, this may lead to unacceptable data collection latency at the same time. In our previous work, we alleviated the problem under the assumption of a mobile base station (BS). In this paper, we discuss how the problem can be solved when the BS itself is not capable of moving, but it can instead employ some mobile elements (MEs). The data collection latency is mainly determined by the longest tour of the MEs in this case. Each ME should be assigned a similar workload to reduce the latency. Furthermore, the total length of the tours should be minimized to decrease the working cost of MEs. We propose three methods to solve the problem with these two-fold objectives. In the first two methods, we cluster the network according to some criteria, and then construct the data collection tour for each ME. We apply a heuristic operator based on the genetic algorithm in the third method, whose fitness function is defined according to the two-fold objectives. These methods are evaluated by comprehensive experiments. The results show that the genetic method can provide us more steady solutions in term of data collection latency. We also compare the mobile BS model and the multiple MEs model, whose results show that the latter can get us better solutions when the number of MEs gets larger.