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移动Agent系统通信效率的分析与优化 被引量:9

Analysis and Optimization of Communication Efficiency in a Mobile Agent System
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摘要 通信效率是影响移动Agent系统运行效率的重要因素之一 ,如何提高通信效率仍是一个有待解决的问题 提出移动Agent系统通信效率优化模型LCEOM LCEOM具有以下优点 :①全面考虑了影响通信效率的主要因素 ;②能够描述移动Agent的通信任务 ;③能够定量地分析通信开销 ;④能够规划出通信开销最小的通信方案 ;⑤采用压缩和缓冲存储技术进一步提高远程通信的效率 实验表明 ,在一定条件下 ,LCEOM模型优于现有方法 。 Communication efficiency is one of the most important factors affecting the performance of a mobile agent system How to improve the communication efficiency of a mobile agent system is still an open issue to be solved A communication efficiency optimization model named LCEOM is proposed in this paper The model has five primary advantages First, it fully takes into account the factors that will affect the communication efficiency Second, it can specify the communication task of mobile agent Third, it can make quantitative analysis of communication cost Fourth, it can plan out an optimal communication scheme to minimize the communication cost Fifth, it adopts the technologies such as compression and cache in order to improve the remote communication efficiency It is shown by experiments that LCEOM is superior to other methods and can effectively improve the communication efficiency of a mobile agent system in certain conditions
出处 《计算机研究与发展》 EI CSCD 北大核心 2004年第4期531-538,共8页 Journal of Computer Research and Development
基金 国家"八六三"高技术研究发展计划基金项目 (2 0 0 1AA115 160 )
关键词 移动AGENT系统 移动AGENT 通信效率 mobile agent system mobile agent communication efficiency
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参考文献10

  • 1[1]Simple agent communication protocol. Bond University, Brisbane, Queensland, Australia, 1999. http://www.davidreilly.com/sacp/
  • 2[2]J Baumann, F Hohl, N Radouniklis. Communication concepts for mobile agents. In: K Rothermel ed. Proc of the 1st Int'l Workshop on Mobile Agents 97. Berlin: Springer, 1997. 123~135
  • 3[3]Y Labrou, T Finin, Y Peng. Agent communication languages: The current landscape. IEEE Intelligent Systems, 1999, 14(2): 45~52
  • 4[4]L Ismail, D Hagimont. A performance evaluation of the mobile agent paradigm. ACM SIGPLAN Notices, 1999, 34(10): 306~313
  • 5[5]G Samaras, M Dikaiakos, C Spyrou et al. Mobile agent platforms for web databases: A qualitative and quantitative assessment. In: D B Lange, D S Milojicic eds. Proc of the 1st Int'l Symp on Agent Systems and Applications and the Third Int'l Symp on Mobile Agents. New York: IEEE Computer Society Press, 1999. 50~64
  • 6[6]M Dikaiakos, G Samaras. Quantitative performance analysis of mobile agent systems: A hierarchical approach. University of Cyprus, Tech Rep: TR-00-2, 2000
  • 7[7]C Stefano, H Heikki, K Oskari.Performance enhancing proxies for Java2 RMI over slow wireless links. In: Proc of the 2nd Int'l Conf on the Practical Application of Java. London: The Practical Application Company, 2000. 76~89
  • 8[8]M Straer, M Schwehm. A performance model for mobile agent systems. In: Proc of the Int'l Conf on Parallel and Distributed Processing Techniques and Applications. Las Vegas: Computer Science Research, Education and Applications (CSREA) Press, 1998.1132~1140
  • 9[9]H Heikki, L Heimo, R Kimmo. Mobile agent communication in wireless networks. In: Proc of European Wireless'99. Berlin: VDE-Verlag, 1999. 211~216
  • 10[11]D B Lange, M Oshima. Programming and Deploy Java Mobile Agents with Aglets. Reading, MA: Addison-Wesley, 1998

同被引文献44

  • 1肖波,张增茂.基于移动Agent技术的网络管理[J].中央民族大学学报(自然科学版),2004,13(3):240-245. 被引量:1
  • 2黄晓宇,李磊,李东.基于多Agent系统的DCS模型[J].计算机工程与设计,2004,25(8):1384-1387. 被引量:3
  • 3曹军海,熊光楞,徐宗昌.分布式多Agent仿真系统的控制结构研究[J].系统仿真学报,2005,17(3):627-630. 被引量:7
  • 4石俊萍,李必云.基于工作流的管理系统开发模型[J].吉首大学学报(自然科学版),2010,31(6):49-52. 被引量:3
  • 5樊昌信.一种发展中的新移动通信方式——平流层通信研发概况[J].现代电子技术,2005,28(19):1-3. 被引量:20
  • 6Contreras J, Losi A, Russo M, etal. DistOpt: A distributed optimization software modeling and evaluation framework [J]. Journal of Parallel and Distributed Computing, 2000, 60 (6) : 741-763
  • 7Horst R, Pardalos P M. Handbook of Global Optimization[M]. Netherlands: Kluwer Academic Publishers, 2002: 65- 85
  • 8Wu Q, Rao N S V, Jacob B, et al. On computing mobile agent routes for data fusion in distributed sensor networks[J]. IEEE Trans on Knowledge and Data Engineering, 2004, 16(6): 740-753
  • 9Pragnesh Jay Modi, Wei- Min Shen, Milind Tambe, et al. ADOPT: Asynchronous distributed constraint optimization with quality guarantees [J]. Artificial Intelligence, 2005, 16 (1/2) : 149-180
  • 10Anton Chechetka, Katia Sycara. A decentralized variable ordering method for distributed constraint optimization [C]// Proc of the 4th Int Joint Conf on Autonomous agents and multiagent systems. New York: ACM, 2005:1307-1322

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