Abstract
Wireless sensor networks (WSNs) have been used extensively in a range of applications, which realizes data acquisition, processing, transmission, and analysis in an interesting area. Harsh surroundings and their inherent vulnerability often mean that these networks suffer from simultaneous node failure possibly causing the network to become partitioned into multiple disjointed segments. This in turn can prevent the gathering of data from the sensors and subsequent transmission to the sink, causing the whole network to fail. In this paper, a strategy is presented for restoring multi-objective optimization connectivity of these segments using mobile data collectors (MDCs), by considering the segments as collections of sensor nodes and not as some representative node. Different from existing uses of MDCs for restoration, the delay in data collection and task balance is considered, and the network connectivity and data acquisition path optimization problem are transformed into an improved multi-travelling salesman problem (iMTSP). An improved multi-objective optimization genetic algorithm for solving the optimal collection data collector position and moving paths is proposed, which introduces virtual segments and hierarchical chromosome structure, improved population diversity, and custom coding and decoding. The simulation results show that the proposed method can effectively solve the iMTSP of the Pareto optimal solution and can provide a new strategy for connectivity-restoring technology in WSNs. Compared with NSGA-II, the diversity of the proposed gene algorithm represents a clear improvement.
Highlights
Wireless sensor networks (WSNs) consist of spatially distributed autonomous sensors that monitor certain events and phenomena cooperatively in an area of interest
We propose the use of mobile data collectors (MDCs) to restore network connectivity, which have the function of data acquisition and are mobile, providing more computing, communications, and storage capacity than general sensor nodes
Recovery strategy using MDCs The gist of our proposed algorithm lies in converting the connection recovery problem into improved multi-travelling salesman problem (iMTSP), by introducing virtual segments and hierarchical chromosomes and adopting a multi-objective optimization genetic algorithm to solve the optimal solutions of iMTSP
Summary
Wireless sensor networks (WSNs) consist of spatially distributed autonomous sensors that monitor certain events and phenomena cooperatively in an area of interest. They have been used extensively in a range of applications, including battlefield surveillance, industrial monitoring, environmental protection, and machine health monitoring. Limited resources and harsh environments often mean that sensors are prone to failure or damage Do these failures cause a loss of coverage of the monitored. The main contributions of our proposed restoration strategy can be summarized as follows: (1) it takes account of the constituting nodes of a segment, the shortest moving path, and the moving task balance of MDCs, as such the problem is closer to a real application environment.
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