A New 2-Phase Optimization-Based Guaranteed Connected Target Coverage for Wireless Sensor Networks

Relying on a limited power source, WSNs present one of their most challenging concerns as energy consumption. In addition, coverage and connectivity are important quality of service metrics in the networks. In this paper, the problem of connected target coverage (CTC) with an optimistic view of energy usage is investigated. A new 2-phase optimization method is proposed that provides full target coverage and connectivity with the user throughout network lifetime. In the first phase of the algorithm, sensors are organized into maximum achievable disjoint cover sets (CSs) using a new multi-objective integer linear programming (ILP) model. Set of remaining nodes that could not be formed into an independent CS, are allocated to the existing CSs as a subset of potential cluster heads (CHs) i.e., for every active CS, CHs are chosen from its potential CH subset. In the second phase, the algorithm activates CSs one after another to gather information from targets and forward them to the user in a hierarchical manner via a modified multi-objective mixed integer linear programming (MILP) model. Both of the ILP and MILP models are solved using branch-and-bound method. The solutions of the optimization models are solved to optimality. The superiority of the proposed method is proven through numerous experiments in different scenarios compared with two of the most related works.