Mobility Management Challenges Research Articles

MADM-based network selection and handover management in heterogeneous network: A comprehensive comparative analysis

As radio access technologies, processing speeds, and multimode interfaces of low-powered portable devices continue to advance, the future of wireless communication is envisioned to offer pervasive network coverage, high data rates, and a wide spectrum of services while maintaining high mobility. High data rates, wide range of services, huge connectivity, capacity, and good geographic coverage are being provided by the ultra-dense deployment of small base stations (BSs) in heterogeneous wireless networks (HWN). But dense deployment of small BSs, high mobility, network heterogeneity, imbalanced traffic, and dynamic user preferences lead to frequent handover. Network overhead, excessive energy consumption, and a decrease in service quality and user satisfaction can be due to frequent handover. So, handover management is one of the crucial challenges in the implementation of 5G and beyond in HWNs for ensuring seamless connectivity, energy efficiency, and the required quality of services and experiences. The effectiveness of handover decisions in HWNs relies on the implementation of a suitable network selection mechanism. Multi-attribute decision-making (MADM) is being used to model and analyze appropriate network selection complexities by considering a broad spectrum of intricate and conflicting decision criteria for efficient handover decisions in HWN. This article extensively explores, compares, and analyzes vital MADM techniques utilized for modeling appropriate network selection strategies in terms of algorithmic strategies, cardinality, types and significance of decision attributes, and network utilities. This article also examines, analyzes, and recognizes the recent mobility management challenges and trends in utilizing MADM strategies to tackle network selection issues in high-speed HWNs.

A Framework to Address Mobility Management Challenges in Emerging Networks

The key enablers for emerging cellular networks such as densification, concurrent operation at multiple bands and harnessing mmWave spectrum give birth to a peculiar set of new network management challenges. One such key challenge is the user mobility management. In this article, we identify the key issues that render current mobility management paradigm inadequate for delivering the expected Quality of Experience (QoE) and resource efficiency in emerging and future cellular networks. Together, these challenges call for paradigm shift in the way mobility is managed in cellular networks. We present an Advanced Mobility Management and Utilization Framework (A-MMUF) that can enable this paradigm shift by transforming mobility management from being a reactive to a proactive process. The core idea of A-MMUF is to build upon Mobility Prediction Models (MPMs) to predict various attributes of user mobility and traffic patterns such as next candidate cell for handover (HO), time of HO, future cell loads. These predictions are then leveraged to not only improve HO process for better QoE and less signaling overhead, but also to enable proactive automation to further maximize network performance in terms of energy and spectrum efficiency. However, understandably, the gains offered by the A-MMUF hinge on the accuracy of the MPMs, which may vary, not only with the choice of underlying machine learning technique, but also with the volume, variety, and fidelity of the training data. We analyze the potential gains of A-MMUF through three case studies: namely proactive HO, proactive Mobility Load Balancing (P-MLB), and proactive Energy Savings (P-ES). In addition to demonstrating significant gains in all three case studies, the results provide useful insights into the agility vs accuracy tradeoff that can be leveraged for choosing optimal machine learning models for practical deployment of A-MMUF.

Intelligent Beam Blockage Prediction for Seamless Connectivity in Vision-Aided Next-Generation Wireless Networks

The upsurge in wireless devices and real-time service demands force the move to a higher frequency spectrum. Millimetre-wave (mmWave) and terahertz (THz) bands combined with the beamforming technology offer significant performance enhancements for future wireless networks. Unfortunately, shrinking cell coverage and severe penetration loss experienced at higher spectrum render mobility management a critical issue in high-frequency wireless networks, especially optimizing beam blockages and frequent handover (HO). Mobility management challenges have become prevalent in city centres and urban areas. To address this, we propose a novel mechanism driven by exploiting wireless signals and on-road surveillance systems to intelligently predict possible blockages in advance and perform timely HO. This paper employs computer vision (CV) to determine obstacles and users’ location and speed. In addition, this study introduces a new HO event, called block event (BLK), defined by the presence of a blocking object and a user moving towards the blocked area. Moreover, the multivariate regression technique predicts the remaining time until the user reaches the blocked area, hence determining best HO decision. Compared to conventional wireless networks without blockage prediction, simulation results show that our BLK detection and proactive HO algorithm achieves 40% improvement in maintaining user connectivity and the required quality of experience (QoE).

Network Mobility Management Challenges, Directions, and Solutions: An Architectural Perspective

Efficient mobility management solutions are essential to provide users with seamless connectivity and session continuity during movement. However, user mobility was not envisaged as one of the early Internet’s use cases due to the early adoption of destination based routing and the assumption that end-nodes are static. This has become a critical hinder for providing efficient mobility support. This paper presents the challenges, drivers, and solutions that aim to overcome the drawbacks of current mobility management approaches. Furthermore, it introduces a promising solution that builds on emerging path-based forwarding architectures that identify network links rather than end nodes. Delivery path information is stored inside the packet while forwarding is achieved by performing a simple set membership test rather than the current destination-based routing approach. Mobility management in these architectures simply requires partial recomputation of the delivery path allowing for efficient mobility support over an optimal path. Evaluation results show significant cost savings in terms of delivery paths and end-to-end packet delay when using a path forwarding architecture.

Inter-PLMN Mobility Management Challenges for Supporting Cross-Border Connected and Automated Mobility (CAM) Over 5G

As the first 5G networks are being deployed across the world, new services enabled by the superior performance of 5G in terms of throughput, latency and reliability are emerging. Connected and Automated Mobility (CAM) services are perhaps among the most demanding applications that 5G networks will have to support and their deployment, performance and potential for improvement has been well investigated over the past few years. However, CAM operation in multi-operator environments and the inevitable inter-PLMN handover caused by the inherent mobility of CAM services have not been studied in length. Moreover, the multiple domains, multi-vendor components and inherent high mobility of the cross-border vehicular environment, introduce multiple challenges in terms of network management and dynamic slicing, making Zero-touch network and Service Management (ZSM) solutions an attractive alternative for these environments. The work presented in this study attempts to analyse the requirements for cross-border CAM operation for the five main CAM use cases selected by 3GPP, based on input from key European stakeholders (Network Operators, vendors, Automotive Manufacturers etc.). A detailed analysis and categorization into four categories of the main challenges for cross-border CAM service provisioning is performed, namely Telecommunication, Application, Security/Privacy and Regulatory issues, while potential solutions based on existing and upcoming technological enablers are discussed for each of them. The role of standardization and relevant regulatory and administrative bodies is analysed, leading to insights regarding the most promising future research directions in the field of cross-border CAM services.

Mobility Management in 5G-enabled Vehicular Networks

Over the past few years, the next generation of vehicular networks is envisioned to play an essential part in autonomous driving, traffic management, and infotainment applications. The next generation of intelligent vehicular networks enabled by 5G systems will integrate various heterogeneous wireless techniques to enable time-sensitive services with guaranteed quality of service and ultimate bandwidth usage. However, to allow the dense diversity of wireless technologies, seamless and reliable wireless communication protocols need to be thoroughly investigated in vehicular networks environment. Henceforth, efficient mobility management protocols that mitigate the challenges of vehicles’ mobility is essential to support massive data loads throughout various applications. In this article, we review different mobility management protocols and their ability to address issues related to 5G-enabled vehicular networks within the related works. First, we provide a broad view of existing models of vehicular networks and their applicability to the next generation of wireless networks. Next, we propose a classification of several vehicular network models that suit the 5G wireless network, followed by a thorough discussion of the mobility management challenges in each of these network models that need to be addressed and then discuss each of their benefits and drawbacks accordingly.

Mobility Management Challenges and Solutions in Mobile Cloud Computing System for Next Generation Networks

As of late, there is a dynamic improvement in the field of mobile computing, and mobile cloud computing (MCC) has been familiar with a potential development for portable administrations. Likewise, the mobile phones and their applications have high framework in the administration at any point and grow more rapidly. Again, MCC is depended upon to deliver on a very basic level increasingly inventive with multi applications. Moreover, Mobile handling incorporates versatile equipments, portable correspondence, cell programming, and right now there are various compact cloud applications. Versatility the board for supporting the area following and area based assistance is a significant issue of savvy city by giving the way to the smooth transportation of individuals and products. The mobility is valuable to contribute the development in both open and private transportation frameworks for keen urban communities. As the information is distributed computing and getting to it with cell phones all the exchanges experience the system so it is powerless against assault. For keeping the utilization of this fundamental apparatus of steady in this development world we are giving a portion of the answers for these difficulties to address in the field of MCC. In this paper, the main challenges faced by the enterprises and their corresponding solutions are discussed with the mobile cloud computing.

A Comparative Analysis of Energy-Efficient and Improved QoS-Driven Task and Resource Scheduling in Mobile Cloud Computing Environment

Mobile Cloud Computing (MCC) is a combination of cloud computing in to a mobile environment. It is refers to an infrastructure where data storage and data processing happen outside of the mobile device. MCC is an computing platform located in clouds, which is accessed over the wireless connection. MCC can significantly enhance the computation capability and saves energy of the smart mobile devices. Some built in defects of mobile devices, such as limited battery energy, insufficient storage; the mobile applications faces many challenges in mobility management, Quality of Service (QoS), energy management and security issues. A task is an application which is running in a mobile device and those tasks will be executed by Virtual Machines (VM) which is known as Resources. The pool of VM in a cloud computing data center needs to manage an efficient task and resource scheduling to maintain efficient energy, QoS and resource utilization. This work investigates comparative analysis of energy efficient and improved QoS-driven Task and Resource scheduling in a MCC environment by using Differential Evolution (DF). The evaluation of these algorithms is based on energy and QoS metrics. Based on the analysis of the simulation result, one of the scheduling will be concluded as best scheduling process in terms of energy and QoS.

Mobility Management for Intro/Inter Domain Handover in Software-Defined Networks

To provide satisfactory Quality of Service (QoS) on the move, efficient mobility management is indispensable to provide mobile users with seamless and ubiquitous wireless connectivity. However, both the conventional centralized mobility architecture and the upcoming distributed mobility management face fundamental challenges such as sub-optimal routing, scalability, and so on. The emerging software-defined networking (SDN) architecture can efficiently manage network operations, and accordingly provides a new direction to address the challenges in mobility management. In this paper, we propose an SDN-based Mobility Management (SDN-MM) scheme to support seamless Intro/Inter domain handover with route optimization. SDN-MM decouples mobility management and packet forwarding functions by installing route optimizing and mobility control logics in an SDN controller, but exempting it from traffic redirecting. In SDN-MM, a comprehensive set of signaling operations are designed in order to provide transparent and efficient mobility support for ongoing sessions in each handover scenario, which prevents packet loss and tunneling overhead, and accordingly provide improved QoS to mobile users. For data communications, an SDN controller in SDN-MM pre-calculates the optimal end-to-end route before a handover, and decides whether to migrate traffic to the route by balancing the performance gain and the signaling overhead, which greatly improves bandwidth resource utilization. Finally, we develop a novel analytical model to evaluate the performance of SDN-MM, including signaling overhead, handover latency, and packet delivery cost. The simulation results have been provided to demonstrate that the proposed SDN-MM can greatly improve handover performance and maintain high resource utilization efficiency as well.

Performance Evaluation for Local Anchor-Based Dual Connectivity in 5G User-Centric Network

Ultra-dense network (UDN) is considered as one of the most promising techniques in achieving the increasingly explosive growth of data rates for future 5G system. However, a large number of small cells lead to the increased cell edges and the rugged inter-cell interference, which cause frequent handover events and more radio link failure. In this paper, a local anchor-based dual connectivity (DC) architecture is proposed for a user-centric network based on the analysis of mobility management challenges of UDN. Under the proposed architecture, the local anchor acts as the master eNodeB (MeNB) with neighboring small cells acting as slave eNodeBs (SeNBs) to provide DC transmission for user-centric service following each user’s movement. Key procedures for mobility management are correspondingly provided and both the MeNBs and SeNBs are selected from the small cells to investigate the potential of them, which are different from the mobility management methods under the traditional cellular architecture. Performance evaluations are conducted under different parameter configurations to evaluate the maximum potential of the proposed scheme. Simulation results show that in our proposed scheme, the handover failure rate shows a maximum decrease of more than 53% and the average user spectrum efficiency achieves an increase of 5% gains over the current LTE system when the user equipment speed is 3 km/h.

LTE Mobility Enhancements for Evolution into 5G

Network densification is regarded as the dominant driver for wireless evolution into the era of 5G. However, in this context, interference-limited dense small cell deployments are facing technical challenges in mobility management. The recently announced results from an LTE field test conducted in a dense urban area show a handover failure (HOF) rate of over 21%. A major cause of HOFs is the transmission failure of handover command (HO CMD) messages. In this paper, we propose two enhancements to HO performance in LTE networks — radio link failure-proactive HO, which helps with the reliable transmission of HO CMD messages while the user equipment is under a poor radio link condition, and Early Handover Preparation with Ping-Pong Avoidance (EHOPPPA) HO, which assures reliable transmission of HO CMD under a good radio link condition. We analyze the HO performance of EHOPPPA HO theoretically, and perform simulations to compare the performance of the proposed schemes with that of standard LTE HO. We show that they can decrease the HOF rate to nearly zero through an analysis, and based on the simulation results, by over 70%, without increasing the ping-pong probability.

Mobility management challenges in 3GPP heterogeneous networks

In this article we provide a comprehensive review of the handover process in heterogeneous networks (HetNets), and identify technical challenges in mobility management. In this line, we evaluate the mobility performance of HetNets with the 3rd Generation Partnership Project (3GPP) Release-10 range expansion and enhanced inter-cell interference coordination (eICIC) features such as almost blank subframes (ABSFs). Simulation assumptions and parameters of a related study item in 3GPP are used to investigate the impact of various handover parameters on mobility performance. In addition, we propose a mobility-based inter-cell interference coordination (MB-ICIC) scheme, in which picocells configure coordinated resources so that macrocells can schedule their high-mobility UEs in these resources without co-channel interference from picocells. MB-ICIC also benefits low-mobility UEs, since handover parameters can now be more flexibly optimized. Simulations using the 3GPP simulation assumptions are performed to evaluate the performance of MB-ICIC under several scenarios.

Protocol and architecture supports for network mobility with QoS-handover for high-velocity vehicles

The evolution of wireless access technologies has led to a new era of mobile Internet for high-velocity vehicles. Network mobility is particularly suitable for vehicles because it considers the mobility of an entire network. Vehicles perform handover frequently thus efficient handover is essential to meet the QoS requirements for real-time communications. For high-velocity vehicles, the time constraint is even stricter and the Doppler Effect increases the transmission error rate that both add challenges in mobility management. In this paper, we propose a cross-layer hierarchical network mobility framework called Hi-NEMO for all-IP networks. The advantage of Hi-NEMO is no extra triangular route between a mobile network node and the correspondent node. The design is resilient to error-prone transmission, and protocol-supports fast QoS provisioning in the network mobility service domain. Intensive simulation results demonstrate that Hi-NEMO reduces handover latency as well as packet loss, and supports handover requirements in high-velocity vehicles.