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Fast handover solution for network-based distributed mobility management in intelligent transportation systems

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Abstract

The current IP mobility protocols are called centralized mobility management (CMM) solutions, in which all data traffic and management signaling messages must be forwarded to an anchor entity. In some vehicle scenarios, vehicles may move as a group from one roadside unit to another (i.e., after traffic lights or traffic jams). This causes data traffic and exchanged mobility messages to peak at the anchor entity and, consequently, affects the network performance. A new design paradigm aimed at addressing the anchor entity issue is called distributed mobility management (DMM); it is an IETF proposal that is still being actively discussed by the IETF DMM working group. Nevertheless, network-based DMM is designed based on the well-known network-based CMM protocol Proxy Mobile IPv6 (PMIPv6). There is no significant difference between network-based DMM and PMIPv6 in terms of handover latency and packet loss. Because vehicles change their roadside unit frequently in this context, the IP addresses of mobile users (MUs) require fast IP handover management to configure a new IP address without disrupting ongoing sessions. Thus, this paper proposes the Fast handover for network-based DMM (FDMM) based on the Fast Handover for PMIPv6 (PFMIPv6). Several modifications to PFMIPv6 are required to adapt this protocol to DMM. This paper specifies the necessary extensions to support the scenario in which an MU has old IP flows and hence has multiple anchor entities. In addition, the analytic expressions required to evaluate and compare the handover performance of the proposed FDMM and the IETF network-based DMM have been derived. The numerical results show that FDMM outperforms the IETF network-based DMM in terms of handover latency, session recovery and packet loss at the cost of some extra signaling.

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Balfaqih, M., Ismail, M., Nordin, R. et al. Fast handover solution for network-based distributed mobility management in intelligent transportation systems. Telecommun Syst 64, 325–346 (2017). https://doi.org/10.1007/s11235-016-0178-y

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