| Summary: | This paper presents an optimization framework to maximize the lifetime of wireless sensor networks for structural health monitoring with and without energy harvesting. We develop a mathematical model and formulate the problem as a large-scale mixed integer non-linear programming problem. We also propose a solution based on the Branch-and-Bound algorithm augmented with reducing the search space. The proposed strategy builds up the optimal route from each source to the sink node by providing the best set of hops in each route and the optimal power allocation of each sensor node. To reduce the computational complexity, we propose heuristic routing algorithms. In this heuristic algorithm, the power levels are selected from the optimal predefined values, the problem is formulated by an integer non-linear programming, and the Branch-and-Bound reduced space algorithm is used to solve the problem. Moreover, we propose two sub-optimal algorithms to reduce the computation complexity. In the first algorithm, after selecting the optimal transmission power levels from a predefined value, a genetic algorithm is used to solve the integer non-linear problem. In the second sub-optimal algorithm, we solve the problem by decoupling the optimal power allocation scheme from the optimal route selection. Therefore, the problem is formulated by an integer non-linear programming, which is solved using the Branch-and-Bound space-reduced method with reduced binary variables (i.e., reduced complexity), and after the optimum route selection, the optimal power is allocated for each node. The numerical results reveal that the presented algorithm can prolong the network lifetime significantly compared with the existing schemes. Moreover, we mathematically formulate the adaptive energy harvesting period to increase the network lifetime with the possibility to approach infinity. Finally, the minimum harvesting period to have infinite lifetime is obtained.
|
|---|
