[1]韩波,郑凯.基于能量模型的多权值分簇算法[J].计算机技术与发展,2019,29(02):7-12.[doi:10．3969/j．issn．1673－629X．2019．02．002]
　HAN Bo,ZHENG Kai.A Multi－weighted Clustering Algorithm Based on Energy Model[J].,2019,29(02):7-12.[doi:10．3969/j．issn．1673－629X．2019．02．002]
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基于能量模型的多权值分簇算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年02期
页码:
7-12
栏目:
智能、算法、系统工程
出版日期:
2019-02-10

文章信息/Info

Title:
A Multi－weighted Clustering Algorithm Based on Energy Model
文章编号:
1673－629X(2019)02－0007－06
作者:
韩波; 郑凯
华东师范大学 计算机科学与软件工程学院，上海 200062
Author(s):
HAN Bo; ZHENG Kai
School of Computer Science and Software Engineering，East China Normal University，Shanghai 200062，China
关键词:
移动自组织网络; 能量模型; 多权值; 分簇算法; 簇头节点
Keywords:
MANET; energy model; multi－weight; clustering algorithm; cluster head
分类号:
TP393
DOI:
10．3969/j．issn．1673－629X．2019．02．002
摘要:
分簇被广泛用于移动自组织网络以提高其稳定性和效率，并减小控制信息的开销。现有的分簇策略均有其局限性。对此，提出了一种基于能量模型的多权值分簇算法，称为 Energy－AOW(EAOW)。该算法根据节点的能量模型，分析节点能量消耗的组成部分，在选举簇头时，综合考虑节点度数、节点传输功率、节点移动性、节点能量和节点处理能力等关键参数，形成节点的组合权值，分别选取组合权值最大和次大的节点担任簇头节点和候选簇头节点。在完成簇头选举后，依次进行簇结构的初始化、建立和维护。当节点移动或变化导致簇结构失效时，再根据上述策略重新选举。仿真试验表明，使用 EAOW 算法选举的综合性能最优的节点担任簇头明显地降低了节点整体的能量消耗，提高了网络的生存时间。同时候选簇头节点的设置也缩短了节点成簇时间并提高了网络的稳定性。
Abstract:
Clustering is widely used in mobile ad－hoc networks (MANET) to improve their stability and efficiency with reduction of the cost of information control． Existing clustering strategies have their limitations． Therefore，we propose a multi－weighted clustering algorithm based on energy model，called Energy－AOW (EAOW)． The algorithm analyzes the components of the energy consumption of nodes using its energy model，and makes a comprehensive consideration on the key indicators such as node degrees，node transmission power，node mobility，node energy and processing capacity when electing the cluster head． Meanwhile，the combined weights of the nodes are formed，and the node with the maximum combined weight is selected as the cluster head and the suboptimal one is marked as the candidate cluster heads． After the election of the cluster head，the initialization，establishment and maintenance of the cluster structure are carried out in turn． When the cluster structure is collapsed because of nodes moving or changing，the new election will begin using above strategy． The simulation shows that the EAOW algorithm selects the nodes with the best comprehensive performance as the cluster heads， which significantly reduces the overall energy consumption and improves the network lifetime． At the same time，the setting of candidate cluster heads also shortens the time of clustering and improves the stability of the network．

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更新日期/Last Update: 2019-02-10