期刊文献+

一种基于免疫-蚁群算法的Ad hoc网络QoS路由算法 被引量:3

A QoS Routing Algorithm Based on AIA-ACA Algorithm
下载PDF
导出
摘要 由于Ad hoc网络的动态性和处理能力不强等因素,使得之前的启发式算法和近似算法在解决Qos路由问题中存在很大的局限性.针对Ad hoc网络QoS路由的上述研究现状提出了一种基于免疫-蚁群算法的QoS路由算法.该算法前过程利用人工免疫算法(Artificial Immune Algorithm,AIA)快速寻求较优的可行解,在此基础上算法后过程采用蚁群算法(Ant Colony Algorithm,ACA),利用前过程中人工免疫算法获得的较优可行解,进一步提高求解效率.该算法结合了人工免疫算法与蚁群算法二者的优点,具有并行度高,全局寻优,快速收敛等特点.实验证实,这种算法是行之有效的. Because of the factors of Ad hoc network's dynamic and insufficient handling approximate algorithm was limited in the solution of Qos routing problem . Against the ability, the use of heuristic algorithm and situation above, a QoS routing algorithm based on AIA-ACA was presented in this article . First, AIA algorithm was used to search for the optional solution fast,and then ACA algorithm was used to give the more optional solution effectively. This algorithm combined the advantages of Artificial Immune Algorithm(AIA) and Ant Colony Algorithm(ACA) and boasted a number of attractive features, including distributed,optimized in whole space and convergence swift. Experiments improved that it worked well.
作者 卢苇 邵逊
出处 《厦门大学学报(自然科学版)》 CAS CSCD 北大核心 2007年第4期510-513,共4页 Journal of Xiamen University:Natural Science
关键词 免疫算法 蚁群算法 QOS路由 AIA ACA QoS rooting
  • 相关文献

参考文献8

二级参考文献26

  • 1Marco Dorigo, Gambardella, Luca Maria. Ant colonies for the traveling salesman problem. Biosystems, 1997, 43(2): 73~81.
  • 2Marco Dorigo, Gambardelh, Luca Maria. Ant colony system: A cooperative learning approach to the traveling salesaum problem. IEEE Trans on Evolutionary Computation, 1997, 1(1) : 53~66.
  • 3Marco Dorigo, Eric Bonabeau, Theranlaz Guy. Ant algorithms and stigmergy. Future Generation Computer System, 2000, 16(8) : 851~871.
  • 4Thomas Stutzle, Holger H Hoos et al. MAX-MIN ant system. Future Generation Computer System, 2000, 16(8) : 889~914.
  • 5Marcus Randall, Andrew Lewis. A parallel implementation of ant colony optimization. Journal of Parallel and Distributed Computing, 2002, 62(9): 1421~1432.
  • 6Dorigo M,Gambardella L M. Ant Golony System: A Cooperative Learning Approach to the Traveling Salemaan Problem[J]. IEEE Transactions on Evolutionary Computation, 1997,1(1);53-66.
  • 7Dorigo M, Maniezzo V, Colony A. The Ant System; Optimization by a colony of cooperating agents [ J ]. IEEE Transactions on Systems,Man,and Cybermetrics, 1996,26( 1 ) : 1 - 13.
  • 8Hofmeyr S A, Forrest S. Immunity by Design: An Artificial Immune System[A]. Proc of GECCO'99[C]. San Francisco: Morgan Kaufmann Publishers, 1999.1289~1296.
  • 9Gibert C J, Routen T W. Associative Memory in an Immune Based System[A]. Proc the 12th National Conf on Artificial Intelligence[C]. Seattle: IEEE Press, 1994.852~857.
  • 10TOH C -K. Maximum battery life routing to support ubiquitous mobile computing in wireless ad hoe networks [ J ].IEEE Communications Magazine, 2001,39:138-147.

共引文献390

同被引文献46

引证文献3

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部