Abstract

The reduction of the signaling load associated with IP mobility management is one of the significant challenges to IP mobility support protocols. Hierarchical Mobile IPv6 (HMIPv6) aims to reduce the number of the signaling messages in the backbone networks, and improve handoff performance by reducing handoff latency. However, this does not imply any change to the periodic binding update (BU) to the home agent (HA) and the correspondent node (CN), and now a mobile node (MN) additionally should send it to the mobility anchor point (MAP). Moreover, the MAP should tunnel the received packets to be routed to the MN. These facts mean that the reduction of the BU messages in the backbone networks can be achieved at the expense of the increase in the signaling bandwidth consumption within a MAP domain. On the other hand, it is observed that an MN may habitually stay for a relatively long time or spend on using much Internet in a specific cell (hereafter, home cell) covering its home, office or laboratory, etc. Thus, considering the preceding facts and observation, HMIPv6 may not be favorable especially during a home cell residence time in terms of signaling bandwidth consumption. To overcome these drawbacks of HMIPv6, we propose a history-based auxiliary mobility management strategy (H-HMIPv6) to enable an MN to selectively switch its mobility management protocols according to whether it is currently in its home cell or not in HMIPv6 networks. The operation of H-HMIPv6 is almost the same as that of HMIPv6 except either when an MN enters/leaves its home cell or while it stays in its home cell. Once an MN knows using its history that it enters its home cell, it behaves as if it operates in Mobile IPv6 (MIPv6), not in HMIPv6, until it leaves its home cell; No periodic BU messages to the MAP and no packet tunneling occur during the MN's home cell residence time. The numerical results indicate that compared with HMIPv6, H-HMIPv6 has apparent potential to reduce the signaling bandwidth consumption and the MAP blocking probability.

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