Software Defined Mobility Management for Mobile Internet

Bi, Jun; You, Wang

doi:10.1002/9781118900253.ch15

Cited by 1 publication

(1 citation statement)

References 21 publications

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“…The SDN controller (CTR), with a central view of the mobility domain, has thus been utilized for various mobility-related functions in several SDN-based DMM solutions. An SDN-based DMM solution in the work of Bi and Wang 32 suggests the binding information for an MN to be stored at CTR in the form of flow bindings. These bindings are installed in the underlying forwarding entities and are updated as the MN performs a handoff.…”

Section: Sdn-based Dmmmentioning

confidence: 99%

A flexible IPv6 mobility management architecture for SDN‐based 5G mobile networks

Sajjad

Jayalath

Bernardos

2019

Trans Emerging Tel Tech

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With the advent of increasingly diverse services, applications, and use cases, the 5G mobility environment is expected to be highly heterogeneous. The distributed mobility management (DMM) is emerging as a promising approach for 5G, which provides decentralized handover and traffic management at the edge of the network. However, in order to meet the disparate mobility needs, the DMM process requires flexible design considerations. This paper presents a novel mobile node (MN) centered, software-defined networking (SDN)-based flexible mobility management architecture, named adaptive multimode mobility management (A3M), which can adaptively operate in multiple modes. The proposed A3M architecture incorporates a novel handover mode selection phase among the traditional handover phases during which a suitable mode of handover operation is evaluated. This makes the A3M handover process adaptable to the varying mobility requirements of the MN and enables it to provide differentiated handover management for MNs with different mobility profiles. The performance analysis of A3M shows that it offers optimal handover performance in terms of primary handover performance metrics such as session disruption delay, packet losses, and signaling costs, compared to the popular network-based DMM approaches.

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Section: Sdn-based Dmmmentioning

confidence: 99%