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Energy efficient duty cycle design based on quantum immune clonal evolutionary algorithm in body area networks

机译:人体局域网中基于量子免疫克隆进化算法的节能占空比设计

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摘要

Duty cycle design is an important topic in body area networks. As small sensors are equipped with the limited power source, the extension of network lifetime is generally achieved by reducing the network energy consumption, for instance through duty cycle schemes. However, the duty cycle design is a highly complex NP-hard problem and its computational complexity is too high with exhaustive search algorithm for practical implementation. In order to extend the network lifetime, we proposed a novel quantum immune clonal evolutionary algorithm (QICEA) for duty cycle design while maintaining full coverage in the monitoring area. The QICEA is tested, and a performance comparison is made with simulated annealing (SA) and genetic algorithm (GA). Simulation results show that compared to the SA and the GA, the proposed QICEA can extending the lifetime of body area networks and enhancing the energy efficiency effectively.
机译:占空比设计是人体局域网中的重要主题。由于小型传感器配备有受限的电源,因此通常通过减少网络能耗(例如通过占空比方案)来延长网络寿命。然而,占空比设计是一个非常复杂的NP难题,对于穷举搜索算法而言,其计算复杂度过高,无法实现。为了延长网络寿命,我们提出了一种用于占空比设计的新型量子免疫克隆进化算法(QICEA),同时保持了监控区域的全覆盖。测试了QICEA,并使用模拟退火(SA)和遗传算法(GA)进行了性能比较。仿真结果表明,与SA和GA相比,提出的QICEA可以延长人体局域网的寿命,并有效地提高能源效率。

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