吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (2): 471-477.doi: 10.13229/j.cnki.jdxbgxb201402031

• 论文 • 上一篇    下一篇

多目标协作的自适应移动锚点选择

陶铭1,2, 袁华强1, 俞鹤伟2, 潘晓衡1   

  1. 1. 东莞理工学院 工程技术研究院, 广东 东莞 523808;
    2. 华南理工大学 计算机科学与工程学院, 广州 510006
  • 收稿日期:2012-10-29 出版日期:2014-02-01 发布日期:2014-02-01
  • 作者简介:陶铭（1986- ），男，高级工程师，博士研究生.研究方向：下一代移动互联网关键技术. E-mail：ming.tao@mail.scut.edu.cn
  • 基金资助:

    国家自然科学基金项目（61170216，61300198）；广东省自然科学基金项目（S2013040016582）；中央高校基本科研业务费专项项目（2014ZB0029）.

Adaptive mobile anchor point selection with multi-objective cooperation

TAO Ming1,2, YUAN Hua-qiang1, YU He-wei2, PAN Xiao-heng1   

  1. 1. Engineering & Technology Institute, Dongguan University of Technology, Dongguan 523808, China;
    2. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China
  • Received:2012-10-29 Online:2014-02-01 Published:2014-02-01

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摘要：

对移动终端的行为特性（主要包括移动特性及服务特性）进行分析建模，确定总体性能目标，然后综合考虑上层可达移动锚点（MAP）间的负载均衡，提出了一种多目标协作的自适应MAP选择策略（A-MAP）。基于NS-2网络仿真平台，考虑具有不同移动速率的移动终端的比例配置，设计了一组实验场景，并选择了3种典型的MAP选择方案作为比较对象。通过调整会话到达率验证了A-MAP方案在系统开销、负载均衡以及平均切换时延方面均有较好的性能表现。

关键词: 计算机应用, 移动锚点, 行为特性, 多目标协作

Abstract:

In HMIPv6 networks with multi-level MAP architecture, it remains a significant challenge to select an optimal serving MAP for the mobile terminal to optimize the whole network performance. By analyzing and modeling the behavior characteristics of the mobile terminals, mainly including the mobility characteristics and the service characteristics, the overall performance objective is determined. Then, an adaptive MAP selection strategy with multi-objective cooperation is proposed (A-MAP), in which the load balancing among the available upper-layer MAPs is comprehensively taken into account. Considering the proportional allocation of mobile terminals with different velocities, a set of experimental scenarios is elaborately designed based on the NS-2 network simulation platform, and three typical MAP selection strategies are selected for the comparison. The performance efficiency of the proposed A-MAP on system cost, load balancing, and average handover latency is verified by adjusting the session arrival rate.

Key words: computer application, mobile anchor point(MAP), behavioral characteristics, multi-objective cooperation

中图分类号: 

  • TP393

[1] Soliman H, Castelluccia C, Elmalki K, et al. Hierarchical mobile IPv6 (HMIPv6) mobility management[EB/OL].[2012-07-22].https:[C]//tools.ietf.org/html/rfc4140.

[2] Dutta N, Misra I S. Mathematical modeling of hierarchical mobile IPv6 based network architecture in search of optimal performance[C]//Proc of IEEE ADCOM, Guwahati, Assam, 2007.

[3] He W, Chen I R, Wang D C. DMAP-FR: dynamic mobility anchor points for mobility, service and failure recovery management in mobile ipv6 systems[J]. Wireless Personal Communications, 2012, 62(3): 479-496.

[4] Natalizio E, Scicchitano A, Marano S. Mobility anchor point selection based on user mobility in HMIPv6 integrated with fast handover mechanism[C]//Proc of IEEE WCNC, New Orleans, LA USA, 2005.

[5] Pack S, Nam M, Kwon T, et al. An adaptive mobility anchor point selection scheme in Hierarchical Mobile IPv6 networks[J]. Computer Communications, 2005, 29(16): 3066-3078.

[6] Lagrange X, Godlewski P. Teletraffic analysis of a hierarchical cellular network[C]//Proc of IEEE VTC, Chicago, Illinois, USA, 1995.

[7] 刘银龙, 曾志民, 夏海轮, 等. 基于指针推进策略的分级移动IPv6优化[J]. 吉林大学学报:工学版, 2011, 41(3): 811-816. Liu Yin-long, Zeng Zhi-min, Xia Hai-lun, et al. Performance optimization for hierarchical mobile IPv6 based on pointer forwarding scheme[J]. Journal of Jilin University (Engineering and Technology Edition), 2011, 41(3): 811-816.

[8] 张瀚文, 张玉军, 马超, 等. 基于主动过载预防的MIPv6家乡代理负载均衡[J]. 软件学报, 2009(9): 2511-2519. Zhang Han-wen, Zhang Yu-jun, Ma Chao, et al. Load balancing for home agents in MIPv6 based on active overhead prevention[J]. Journal of Software, 2009(9): 2511-2519.

[9] Baek J, Fischer J, Chen H H. On a moving direction pattern based MAP selection model for HMIPv6 networks[J]. Computer Communications, 2011, 34(2): 150-158.

[10] Purushothaman I, Roy S. FastScan: a handover scheme for voice over IEEE 802.11 WLANs[J]. Wireless Networks, 2010, 6(7): 2049-2063.
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