提出了一种改进的自适应蚁群聚类算法(improved adaptive ant clustering,IAAC)。该算法改进了原来的AM(ant movement)模型,并在此基础上提出了一种网格化的移动策略来改善蚂蚁移动的随机性,使蚂蚁有意识地往模式较多的区域移动,极大地...提出了一种改进的自适应蚁群聚类算法(improved adaptive ant clustering,IAAC)。该算法改进了原来的AM(ant movement)模型,并在此基础上提出了一种网格化的移动策略来改善蚂蚁移动的随机性,使蚂蚁有意识地往模式较多的区域移动,极大地减少了蚂蚁无效的移动,使蚂蚁迅速地找到合适的位置放下模式;并提出了一种自适应调整蚂蚁运动阈值的方法以简化参数的选取,使得算法可以根据当前的聚类情况不断调整阈值,以达到更好的聚类结果。结果表明,该算法具有运行效率高、参数选取简单及自适应性等优点。展开更多
To deeply exploit the mechanisms of ant colony optimization （ACO） applied to develop routing in mobile ad hoe networks （MANETS）,some existing representative ant colony routing protocols were analyzed and compared....To deeply exploit the mechanisms of ant colony optimization （ACO） applied to develop routing in mobile ad hoe networks （MANETS）,some existing representative ant colony routing protocols were analyzed and compared.The analysis results show that every routing protocol has its own characteristics and competitive environment.No routing protocol is better than others in all aspects.Therefore,based on no free lunch theory,ant routing protocols were decomposed into three key components：route discovery,route maintenance （including route refreshing and route failure handling） and data forwarding.Moreover,component based ant routing protocol （CBAR） was proposed.For purpose of analysis,it only maintained basic ant routing process,and it was simple and efficient with a low overhead.Subsequently,different mechanisms used in every component and their effect on performance were analyzed and tested by simulations.Finally,future research strategies and trends were also summarized.展开更多
文摘提出了一种改进的自适应蚁群聚类算法(improved adaptive ant clustering,IAAC)。该算法改进了原来的AM(ant movement)模型,并在此基础上提出了一种网格化的移动策略来改善蚂蚁移动的随机性,使蚂蚁有意识地往模式较多的区域移动,极大地减少了蚂蚁无效的移动,使蚂蚁迅速地找到合适的位置放下模式;并提出了一种自适应调整蚂蚁运动阈值的方法以简化参数的选取,使得算法可以根据当前的聚类情况不断调整阈值,以达到更好的聚类结果。结果表明,该算法具有运行效率高、参数选取简单及自适应性等优点。
基金Project(61225012)supported by the National Science Foundation for Distinguished Young Scholars of ChinaProjects(61070162,71071028,70931001)supported by the National Natural Science Foundation of China+4 种基金Project(20120042130003)supported by the Specialized Research Fund of the Doctoral Program of Higher Education for the Priority Development Areas,ChinaProjects(20100042110025,20110042110024)supported by the Specialized Research Fund for the Doctoral Program of Higher Education,ChinaProject(2012)supported by the Specialized Development Fund for the Internet of Things from the Ministry of Industry and Information Technology of ChinaProject(N110204003)supported by the Fundamental Research Funds for the Central Universities of ChinaProject(L2013001)supported by the Scientific Research Fund of Liaoning Provincial Education Department,China
文摘To deeply exploit the mechanisms of ant colony optimization （ACO） applied to develop routing in mobile ad hoe networks （MANETS）,some existing representative ant colony routing protocols were analyzed and compared.The analysis results show that every routing protocol has its own characteristics and competitive environment.No routing protocol is better than others in all aspects.Therefore,based on no free lunch theory,ant routing protocols were decomposed into three key components：route discovery,route maintenance （including route refreshing and route failure handling） and data forwarding.Moreover,component based ant routing protocol （CBAR） was proposed.For purpose of analysis,it only maintained basic ant routing process,and it was simple and efficient with a low overhead.Subsequently,different mechanisms used in every component and their effect on performance were analyzed and tested by simulations.Finally,future research strategies and trends were also summarized.
