A New Way to Model the Wireless Sensor Network Maintenance Job

Abstract

For the maintenance of an urban wireless sensor network, the staff’s travel route greatly affects the whole network’s response time. Every time the network reports an error, the staff needs to find the best route to minimize the time spent on the way to the error point. The difficulty of the problem is that although the entire network fails, the error point remains unclear. In this paper, the staff’s route planning is modeled as an NP-complete problem, MWLP (Minimum Weighted Latency Problem). It is a problem of finding the best route for a moving agent to satisfy multiple customers’ different demands as much as possible. To solve the problem, we propose a heuristic algorithm which borrows the idea from a biological computing model called P_system. In the proposed algorithm, different classic heuristics work as separate “membranes” to accomplish their own jobs. They also collaborate under some mechanism to search for a better result. We designed the cell’s structure to balance the different heuristics’ time consumption and searching capacity. With this design, all the heuristics can cooperate properly in the proposed heuristic algorithm. To enhance the algorithm’s efficiency, we also introduced a way to run it in parallel. The numerical experiments show that the proposed algorithm is very competitive compared with classic heuristic algorithms and helps eliminate the whole network delay as well.