TSOIA: An efficient node selection algorithm facing the uncertain process for Internet of Things

Perception nodes in Internet of Things are vulnerable to the external environment and the characteristics of them are stochastic and dynamic. In this paper a new optimization algorithm for Internet of Things to support applications which do not need to discrete the solution space has been proposed. The proposed algorithm which is called TSOIA divides perception nodes into three groups to search the global optimal solution. TSOIA algorithm adopts random search, local search and orientation search to adjust the group size and the step length adaptively. In order to show the performance of the TSOIA algorithm, computer simulations have been conducted and the results obtained are compared with that of the two existing search algorithms. The results of comparison show that the proposed algorithm outperforms other search algorithms in terms of search ability, energy consumption and network delay.