Abstract

Fifth-Generation (5G) vehicular networks support novel services with increased Quality of Service (QoS) requirements. Vehicular users need to be continuously connected to networks that fulfil the constraints of their services. Thus, the implementation of optimal Handover (HO) mechanisms for 5G vehicular architectures is deemed necessary. This work describes a scheme for performing HOs in 5G vehicular networks using the functionalities of the Media-Independent Handover (MIH) and Fast Proxy Mobile IPv6 (FPMIP) standards. The scheme supports both predictive and reactive HO scenarios. A velocity and alternative network monitoring process prepares each vehicle for both HO cases. In the case of predictive HO, each time the satisfaction grade of the vehicular user drops below a predefined threshold, the HO is initiated. On the other hand, in the case of reactive HO, the vehicle loses the connectivity with its serving network and connects to the available network that has obtained the higher ranking from the network selection process. Furthermore, the HO implementation is based on an improved version of the FPMIPv6 protocol. For the evaluation of the described methodology, a 5G vehicular network architecture was simulated. In this architecture, multiple network access technologies coexist, while the experimental results showed that the proposed scheme outperformed existing HO methods.

Highlights

  • Fifth-generation (5G) vehicular networks have emerged rapidly

  • This paper describes a methodology for supporting Handovers (HOs) on 5G vehicular networks

  • The vehicle’s velocity is considered in order for unnecessary HOs to short-range cells to be avoided, since a vehicle that moves with high velocity will remain for a short time period inside their coverage area; HO initiation is performed by taking into consideration the user satisfaction, which is estimated using both the Signal-to-Noise-plus-Interference (SINR) and the perceived Quality of Service (QoS) parameters, due to the fact that users that perceive a good SINR may not be satisfied by the QoS that they perceive from their current networks; Network selection takes into consideration contradictory criteria for different application types and users’ Service Level Agreements (SLAs) to satisfy the requirements of demanding services; The HO scheme applies an improved version of the Media Independent Handover (MIH) framework and the Fast Proxy Mobile IPv6 (FPMIPv6) protocol

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Summary

Introduction

Fifth-generation (5G) vehicular networks have emerged rapidly. In a typical 5G vehicular network architecture, vehicular equipment includes On-Board Units (OBUs) [1]. The HO management services, namely the velocity and alternative network monitoring, the HO initiation, the network selection, and the HO execution are performed at the Fog and the Cloud infrastructures to reduce the workload at the vehicle; Both predictive and reactive HOs modes are supported for the mobility transfer; The vehicle’s velocity is considered in order for unnecessary HOs to short-range cells (such as Femtocells) to be avoided, since a vehicle that moves with high velocity will remain for a short time period inside their coverage area; HO initiation is performed by taking into consideration the user satisfaction, which is estimated using both the Signal-to-Noise-plus-Interference (SINR) and the perceived Quality of Service (QoS) parameters, due to the fact that users that perceive a good SINR may not be satisfied by the QoS that they perceive from their current networks; Network selection takes into consideration contradictory criteria for different application types and users’ SLAs to satisfy the requirements of demanding services; The HO scheme applies an improved version of the MIH framework and the FPMIPv6 protocol.

Related Work
Preliminaries
The Interval-Valued Icosagonal Fuzzy Numbers
The Equalized Universe Method
The Icosagonal Fuzzy Analytic Network Process
The Mamdani Icosagonal Fuzzy Inference System
The Dynamic Icosagonal Fuzzy TOPSIS with Adaptive Criteria Weights
The Proposed Mobility Management Scheme
Velocity and Alternative Network Monitoring
HO Initiation
Network Selection
HO Execution
Proposed Predictive HO Scheme
Proposed Reactive HO Scheme
The Computational Complexity of the Proposed Scheme
Simulation Setup and Results
Study of a Simulation Snapshot
Twenty-Four-Hour Evaluation Results
6.Conclusions
Full Text
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