A Comparative Analysis on the Signaling Load of Mobile IPv6 and Hierarchical Mobile IPv6: Analytical Approach*This research was supported by University IT Research Center Project.

  • Authors:

  • Ki-Sik Kong;Moonbae Song;Kwangjin Park;Chong-Sun Hwang

  • Affiliations:

  • The authors are with the Department of Computer Science and Engineering, Korea University, Seoul, Korea. E-mail: kskong@disys.korea.ac.kr;The authors are with the Department of Computer Science and Engineering, Korea University, Seoul, Korea. E-mail: kskong@disys.korea.ac.kr;The authors are with the Department of Computer Science and Engineering, Korea University, Seoul, Korea. E-mail: kskong@disys.korea.ac.kr;The authors are with the Department of Computer Science and Engineering, Korea University, Seoul, Korea. E-mail: kskong@disys.korea.ac.kr

  • Venue:
  • IEICE - Transactions on Information and Systems
  • Year:
  • 2006

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Abstract

This paper presents a novel analytical approach to evaluate the signaling load of Mobile IPv6 (MIPv6) and Hierarchical Mobile IPv6 (HMIPv6). Previous analytical approaches for IP mobility management have not provided a complete and general framework for the performance analysis; no consideration of either periodic binding refresh cost or extra packet tunneling cost from the viewpoint of IP mobility management, and no in-depth investigation with respect to various system parameters. In this paper, according to the proposed analytical approach, we derive the location update costs (i.e., the sum of binding update costs and binding refresh costs), packet tunneling costs, inside-domain signaling costs, outside-domain signaling costs, and total signaling costs, which are generated by a mobile node (MN) during its average domain residence time in case MIPv6 or HMIPv6 is deployed under the same network architecture, respectively. Moreover, based on these derived costs, we evaluate the impacts of various system parameters on the signaling costs generated by an MN in MIPv6 and HMIPv6. The aim of this paper is not to determine which protocol performs better, but evaluate the performance that can be expected for each protocol under the various conditions, broaden our deep understanding of the various parameters that may influence the performance, and provide insight for the deployment of the two protocols.