Scalable Energy-Aware Dynamic Task Allocation

A. Bokar, M. Bozyigit, C. Sener
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引用次数: 12

Abstract

Battery energy limitation is one of the main challenges in the mobile ad hoc networks. Several hardware and software based techniques have been proposed in this field. Energy aware task scheduling is one of the software methods where the scheduling policy aims at optimizing the energy. Most of the previous work have achieved significant energy savings for individual mobile nodes but did not consider overall network lifetime and scalability. In this paper, we propose a Scalable Energy Aware Dynamic Task Allocation technique (SEADTA) for prolonging the network lifetime. In our model, the network lifetime is divided into many rounds. At the beginning of each round a new energy aware clustering algorithm is executed in order to arrange the network nodes in a parent-child structure. Based on the proposed technique, selected parents a reused in the remote allocation such that minimum residual energy is maximized at the end of each round. The results of our simulation showed that our proposed scheme makes a significant improvement in the network life time while simultaneously minimizing the energy consumption and time delay for each task.
可扩展的能量感知动态任务分配
电池能量限制是移动自组织网络面临的主要挑战之一。在这一领域已经提出了几种基于硬件和软件的技术。能量感知任务调度是一种以能量优化为目标的调度策略。以前的大多数工作都实现了单个移动节点的显著节能,但没有考虑整体网络寿命和可扩展性。在本文中,我们提出了一种可扩展的能量感知动态任务分配技术(SEADTA)来延长网络生命周期。在我们的模型中,网络生命周期被分成许多轮。在每轮开始时,执行一种新的能量感知聚类算法,以便将网络节点排列成父子结构。基于所提出的技术,所选择的父母在远程分配中被重用,使得每轮结束时的剩余能量最小最大化。仿真结果表明,我们提出的方案在显著提高网络生存时间的同时,最大限度地降低了每个任务的能耗和时延。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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