QoE-Centric Localized Mobility Management for Future Mobile Networks

TL;DR

This paper proposes a hybrid mobility management scheme for future mobile networks that dynamically chooses between centralized and distributed approaches based on QoE requirements, optimizing resource use and improving user experience.

Contribution

It introduces a novel hybrid mobility management solution with a new routing scheme that adapts to application needs, addressing scalability and efficiency issues in future networks.

Findings

Significant QoE improvements demonstrated through optimization.

Enhanced resource utilization and network congestion reduction.

Effective adaptation between centralized and distributed mobility approaches.

Abstract

Mobility support in future networks will be predominately based on micro mobility protocols. Current proposed schemes such as Hierarchical Mobile IPv6 (HMIPv6) and more importantly Proxy Mobile IPv6 (PMIPv6) provide localized mobility support by electing a node within the network (topologically close to the Access Routers (AR)) to act as mobility anchor. Such schemes can significantly improve handover latency, as well as the end-to-end signalling overhead, but might entail scalability issues, which in some instances, do not fit adequately with the current explosion of mobile Internet traffic, and the evolutionary trend towards flat network architectures. The notion of using Distributed Mobility Management (DMM) allows for decentralization by anchoring nodes at their AR. The idea is that for sessions with duration less than the cell residence time efficient mobility can be supported. However, DMM might be highly suboptimal in instances where nodes perform multiple handovers during the session lifetime. Hence, one approach cannot be effective for all types of applications. In this paper a hybrid mobility management solution, integrated with a new routing scheme, is proposed. The scheme selects the most suitable mobility approach, centralized or distributed, by taking into account the flows' requirement, in terms of Quality of Experience (QoE), and new routing constraints. The results of optimization problem show that the proposed approach can achieve efficient resource utilisation, ease network congestion, and lead to a significant improvement in the QoE.