Mohammad Hamdan, Hisham A. Shehadeh, Qusai Y. Obeidat
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引用次数: 4
Abstract
The most challenges of Wireless Body Area Network (WBAN) are energy consumption because its works using limited resource like battery and end-to-end delay because it is used to transmit real time parameters of patients' health status like Electrocardiogram (ECG). In this paper we present and discuss the modeling of a multi objective problem. The first objective is the minimization of the end to end delay; the second objective is maximization of the energy efficiency of the network depending on packets payload size. We use jMetal to test the problem using three genetic algorithms (NSGA-II, SPEA-II and OMOPSO) and we compare between them.
无线体域网络(Wireless Body Area Network, WBAN)面临的最大挑战是能量消耗,因为它使用有限的电池等资源来工作,而且由于它用于传输心电图(ECG)等患者健康状态的实时参数,因此端到端延迟。本文提出并讨论了多目标问题的建模方法。第一个目标是最小化端到端延迟;第二个目标是根据数据包的有效负载大小最大化网络的能源效率。我们使用jMetal使用三种遗传算法(NSGA-II, SPEA-II和OMOPSO)来测试问题,并在它们之间进行比较。