基于离散多目标优化粒子群算法的多移动代理协作规划

史霄波; 张引; 赵杉; 肖登明

doi:10.11959/j.issn.1000-436x.2016113

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基于离散多目标优化粒子群算法的多移动代理协作规划

学术论文 | 更新时间：2024-06-05

- 基于离散多目标优化粒子群算法的多移动代理协作规划
- Discrete multi-objective optimization of particle swarm optimizer algorithm for multi-agents collaborative planning
- 通信学报 2016年37卷第6期页码：29-37
- 作者机构：
  
  1. 河南师范大学计算机与信息工程学院，河南新乡 453007
  2. 华中科技大学计算机科学与技术学院，湖北武汉 430074
  3. 智慧商务与物联网技术河南省工程实验室，河南新乡 453007
  4. 中南财经政法大学信息与安全工程学院，湖北武汉 430073
- 作者简介：
  
  [ "史霄波（1972-），女，河南焦作人，河南师范大学副教授，华中科技大学博士生，主要研究方向为无线传感器网络、机器学习、智能医疗等。" ]
  [ "张引（1986-），男，江西九江人，中南财经政法大学讲师，主要研究方向为数据挖掘、推荐系统、智能服务等。" ]
  [ "赵杉（1993-），男，安徽宿州人，华中科技大学硕士生，主要研究方向为大数据、云平台等。" ]
  [ "肖登明（1989-），男，湖北仙桃人，华中科技大学硕士生，主要研究方向为云计算、大数据分析、数据挖掘。" ]
- 基金信息：
  
  河南省重点科技攻关基金资助项目(132102210483);河南省重点科技攻关基金资助项目(102102210178);河南省基础与前沿技术研究基金资助项目(122300410344);河南省教育厅自然科学研究计划基金资助项目(2008A520013)
- DOI：10.11959/j.issn.1000-436x.2016113
  中图分类号： TP393
- 网络出版日期：2016-06，
  
  纸质出版日期：2016-06-25
- 稿件说明：
移动端阅览
史霄波, 张引, 赵杉, 等. 基于离散多目标优化粒子群算法的多移动代理协作规划[J]. 通信学报, 2016,37(6):29-37.

Xiao-bo SHI, Yin ZHANG, Shan ZHAO, et al. Discrete multi-objective optimization of particle swarm optimizer algorithm for multi-agents collaborative planning[J]. Journal on communications, 2016, 37(6): 29-37.
史霄波, 张引, 赵杉, 等. 基于离散多目标优化粒子群算法的多移动代理协作规划[J]. 通信学报, 2016,37(6):29-37. DOI： 10.11959/j.issn.1000-436x.2016113.

Xiao-bo SHI, Yin ZHANG, Shan ZHAO, et al. Discrete multi-objective optimization of particle swarm optimizer algorithm for multi-agents collaborative planning[J]. Journal on communications, 2016, 37(6): 29-37. DOI： 10.11959/j.issn.1000-436x.2016113.

摘要

无线传感器网络中多移动代理协作能快速高效地完成感知数据汇聚任务，但是随着移动代理访问数据源节点数的增加，移动代理携带的数据分组会逐渐增大，导致传感器节点能量负载不均衡，部分数据源节点能耗过快，网络生存期缩短。目前，针对该问题所设计的能耗均衡算法，多以降低多移动代理总能耗为目标，却未充分考虑部分数据源节点能量消耗过快对网络生存期造成的影响。提出离散多目标优化粒子群算法，以网络的总能耗和移动代理负载均衡作为适应度函数，在多移动代理协作路径规划中寻求近似最优解。通过仿真实验验证，所提出的多移动代理协作路径规划，在网络总能耗和网络生存期方面的性能优于同类其他算法。

Abstract

Although multiple mobile agents(MA)collaboration can quickly and efficiently complete data aggregation in wireless sensor network

the MA carrying data packages extensively increase along with a raise in the number of data source nodes accessed by MA

which causes unbalanced energy load of sensor nodes

high energy consumption of partial source nodes

and shortened lifetime of networks.The existing related works mainly focus on the objective of decreasing total energy consumption of multiple MA

without considering that rapidly energy consumption of partial source nodes has a negative effect on networks lifetime.Therefore

discrete multi-objective optimization of particle swarm algorithm was proposed

which used the total network energy consumption and mobile agent load balancing as fitness function for the approximate optimal itinerary plan in multiple mobile agent collaboration.Furthermore

the simulation result of the proposed algorithm is better than the similar algorithm in total energy consumption and network lifetime.

关键词

Keywords

references

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