一种无线传感器网络二维目标覆盖的改进方法

针对二维目标覆盖问题,提出了一种新的量子退火算法,设计了相应的系统模型,并给出了覆盖优化的目标函数。因为以往的启发式算法存在运行停滞等问题,所以为量子退火算法设计了全新的解集生成方式、量子旋转门、量子位测量方法和量子位状态更新方法,加快了算法的收敛速度。将基于量子退火算法的方法与粒子群算法、蚁群算法进行了仿真比较。仿真结果显示,相比粒子群算法与蚁群算法,该量子退火算法能够有效地提升解的质量,检出的目标数有较大幅度的提高。

Improved method for 2D target coverage in wireless sensor networks

Two-dimensional target coverage is a key issue in wireless sensor networks. A good coverage algorithm can effectively improve the monitoring effect of wireless sensor networks. Aiming at the two-dimensional target coverage problem, a new quantum annealing algorithm is proposed, and the corresponding system model is designed. The objective function of coverage optimization is also given. Aiming at the problem of running stagnation in the past heuristic algorithms, a new solution set generation method, quantum revolving gate, qubit measurement method and qubit state update method are designed for the quantum annealing algorithm, which accelerates the convergence speed of the algorithm. The method based on the quantum annealing algorithm is compared with particle swarm optimization and ant colony optimization. Simulation results show that compared with the particle swarm optimization algorithm and the ant colony optimization, the proposed algorithm can effectively improve the quality of the solution, with the number of detected targets greatly improved.