Node localization is a key issue in wireless sensor networks (WSN) area, and distance vector hop (DV-Hop) algorithm is widely adopted in WSN localization. Existing DV-Hop based algorithms employ all anchor nodes to localize the unknown node. However there is a large error of the estimated distance from the unknown node to some anchor nodes, which also results in the final unknown node localization error large. To improve the localization accuracy, we propose an improved DV-Hop algorithm based on dynamic anchor node set (DANS IDV-Hop). Differently to the existing DV-Hop based algorithms which apply total anchor nodes, DANS IDV-Hop utilizes part of anchor nodes to participate in localization. Firstly, the selection of anchor nodes is abstracted into a combinatorial optimization problem. For selecting appropriate anchor nodes, a novel binary particle coding scheme and fitness function are designed. Subsequently, the binary particle swarm optimization (BPSO) algorithm is applied to construct the dynamic anchor node set (DANS), and the localization is carried out on the DANS. Finally, the continuous particle swarm optimization (PSO) algorithm is utilized to further optimize the unknown node coordinates. Simulation results show that DANS IDV-Hop has excellent localization accuracy than that of the original DV-Hop and other DV-Hop based improved algorithms.

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The current integrated scheduling algorithm ignores the influence of the pre-process on the post-process when solving the multi-device-process integrated scheduling problem, which leads to the problem of poor tightness between serial processes and low parallelism between parallel processes. This paper points out that there is no restriction of scheduling sequence between adjacent parallel processes on the same processing device, and the scheduling sequence between parallel processes on the same device can be flexibly processed to optimize the scheduling results, on the basis of the current algorithm scheduling scheme, this paper proposes the application of multi-device adjacent parallel process interchange strategy and multi-device adjacent parallel process interchange adjustment strategy, which avoid the influence of the pre-process on the post-process, improves the compactness of the serial process and the parallelism of the parallel process, and optimizes the scheduling results.

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