Augmented Node Placement Model in -WSN Through Multiobjective Approach

In Wireless Sensor Network (WSN), coverage and connectivity are the vital challenges in target-based region. The linear objective is to find positions cover complete target nodes between each sensor for data forwarding towards base station given a grid with points potential placement position. this paper, multiobjective problem on WSN (t-WSN) derived, which minimizes number of deployed nodes, maximizes cost sensing range. An Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) incorporated tackle efficiently. Multiobjective problems intended solve different objectives simultaneously. Bio-inspired algorithms address NP-hard most effectively recent years. NSGA-II, sorting preserves better solution simultaneously using dominance relation. diversity maintenance phase, density estimation crowd comparison two components that balance exploration exploitation phase algorithm. Performance NSGA-II evaluated terms performance indicators Overall Non-dominated Vector Generation (ONGV) Spacing (SP). simulation results show proposed method performs outperforms existing aspects model.