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Abstract
The WSN consists of hundreds or thousands of distributed wireless sensors at certain area. One of the network lifetime maximization methods depends on organizing densely sensors in groups which work in a sequential manner. The network lifetime is calculated as the summation of groups lifetime periods. In this thesis, we address the WSN lifetime problem by investigating a mul- tiobjective optimization problem, the first objective is to find the maximum number of covers. The second objective considers the problem of wasted energy at sensors, we minimize the wasted energy in the critical sensors, and this is achieved by defining a new objective, the Difference Factor (DF). We compare our choice for the second objective with other choices in the litera- ture such as minimizing the overlapping and minimizing the variance between the cover sensors lifetime. Based on the results, we show that the second objective selection has great influences on the WSN lifetime, the convergence speed of the number of covers, and the network scalability. This optimization problem is addressed using an algorithm based on Non-dominated Sorting Genetic Algorithm{u2013}II (NSGA-II).