Handover with Buffering for Distributed Mobility Management in Software Defined Mobile Networks

Distributed Mobility Management (DMM) is a mobility management solution, where the mobility anchors are distributed instead of being centralized. The use of DMM can be applied in cloud-based (virtualized) Long Term Evolution (LTE) mobile network environments to (1) provide session continuity to users across personal, local, and wide area networks without interruption and (2) support traffic redirection when a virtualized LTE entity like a virtualized Packet Data Network Gateway (P-GW) running on an virtualization platform is migrated to another virtualization platform and the on-going sessions supported by this P-GW need to be maintained. In this paper we argue that the enabling technology that can efficiently be used for supporting DMM in virtualized LTE systems is the Software Defined Networking (SDN)/OpenFlow technology.

Cellular networking has entered the paradigm of next generation networking, Software Defined Mobile Networking (SDMN) and Cloud Radio Access Networks (CRAN). This paradigm shift has compelled to improve future cellular networks by making them more efficient and smart. The improved, future cellular networks could have a profound impact on the commercial and research segments in terms of capital expenditure and operational expenditure by presenting a unified robust technology for data connectivity. In future, 5G cellular networks will be progressed with LTE that will facilitate this technological transformation. Future 5G demands reliance on more flexible and dynamic technologies such as static Radio Access Networks (RAN), otherwise resources will be depleting and will be unable to meet the surging demands including wireless transmission connectivity and providing an efficient network bandwidth. To address this problem, the paper presents a study exploring the amalgamation of Software Defined Network (SDN) and cloud computing achieve Cloud RAN or RAN-as-a-Service (RANaaS). This helps to overcome the problems associated with handling enormous matrix of connecting devices and nodes. This paper explores existing research geared towards the deployment of 5G networks through Remote Radio Heads (RRH) and Virtual Base Stations (VBSs) backed by SDN. Furthermore, this research survey is an effort to unearth the security implications and challenges of CRAN while adopting LTE and SDMN services in CRAN based 5G networks. The security challenges of conventional wireless networks are framed to emphasize on the need to migrate from traditional RAN to CRAN. Subsequently the possible mitigation techniques are also discussed. Furthermore, the role of SDN and its security artifacts are also explored to embed security within the CRAN architecture.

Currently, various efforts are being performed on specifying distributed mobility management (DMM) for IPv6 mobile networks. DMM is expected to eliminate the limitations of the current IPv6 mobility protocols and to cope with the rapid increase in mobile data traffic. In current DMM approaches, the mobility anchoring is distributed at the access router level and the mobile node changes dynamically the mobility anchor for new sessions. Although such approaches avoid any network bottleneck and allow optimal routing in most cases, they lack reachability support since the mobile node has no permanent IPv6 address. In this paper, we consider one of the DMM approaches, dynamic mobility anchoring, and study the usage of session initiation protocol (SIP) for providing reachability support. After defining different SIP-based location update modes, we carry out a comparative cost analysis considering new performance metrics related to the processing loads at each network entity. We consider the location update loads on the location server as well as the context, signaling, and tunneling loads on a mobility anchor. We investigate the different modes in several scenarios, allowing the mobile network operator to adopt the preferred mode depending on their architecture.

During these last few years, mobile data traffic has been strongly growing while the voice traffic decreases (fixed and mobile), This new reality pushes operators to invest in a new next generation of mobile network (Mobile Cloud Computing, 5G) to enhance their competitivity and provide more innovative marketing products and services to the end user. But they were facing a major obstacle: the computer networks management is too complex and difficult. The research community proposes Software Defined Mobile Networks (SDMNs) as a solution to provide more flexibility and to ease the management of the next-generation mobile networks especially Mobile Cloud Computing (MCC). This new solution offers a huge advantage to the mobile operators and enables innovation through network programmability. SDMN provides several benefits including, network and service customized, improved operations and better performance, but there are some security issues that need to be taken care of. This paper describes the emergence of SDMN as an important new networking technology, discusses the different problems related to security issue. We propose a framework to secure the different levels in SDMN architecture with an implementation of our framework. A simulation has been done of some main threats such as DDoS attack and malware infection.

Research on future 5G networks has geared up in the past couple of years, and among many other, seamless mobility is considered as a cornerstone of 5G networks. Lately, many mobility solutions have been put forward, among them are Software Defined Networking (SDN) based Proxy Mobile IPv6 (PMIPv6) and Distributed Mobility Management (DMM). SDN-PMIP advocates the benefits of control and data plane separation, but poses major limitation in terms of mobility support across multiple domains. DMM takes care of inter-domain handovers through on demand mobility feature, but has limitations like excessive control signaling, tunneling overheads and inefficient routing. This paper presents a comprehensive solution to provide mobility across multiple domains in SDN-PMIP by utilizing the on demand mobility feature of DMM. Concept of on demand mobility is to provide mobility support to only those mobile nodes which require it, by exploiting the IPv6 mandatory feature of supporting multiple prefixes. In our proposed solution, controllers in multiple SDN-PMIP domains communicate with each other in distributed manner to facilitate seamless inter-domain mobility. The proposed solution also introduces a new optimized routing concept which resolves the triangular routing issue faced by various inter-domain mobility solutions. Analytical modeling based performance evaluation in terms of handover delay, transmission delay and tunnel usage, shows that the proposed solution achieves substantial improvements over previous works.

Mobility management is an essential process in mobile networks to ensure a high quality of service (QoS) for mobile user equipment (UE) during their movements. In fifth generation (5G) and beyond (B5G) mobile networks, mobility management becomes more critical due to several key factors, such as the use of Millimeter Wave (mmWave) and Terahertz, a higher number of deployed small cells, massive growth of connected devices, the requirements of a higher data rate, and the necessities for ultra-low latency with high reliability. Therefore, providing robust mobility techniques that enable seamless connections through the UE’s mobility has become critical and challenging. One of the crucial handover (HO) techniques is known as mobility robustness optimization (MRO), which mainly aims to adjust HO control parameters (HCPs) (time-to-trigger (TTT) and handover margin (HOM)). Although this function has been introduced in 4G and developed further in 5G, it must be more efficient with future mobile networks due to several key challenges, as previously illustrated. This paper proposes a Robust Handover Optimization Technique with a Fuzzy Logic Controller (RHOT-FLC). The proposed technique aims to automatically configure HCPs by exploiting the information on Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and UE velocity as input parameters for the proposed technique. The technique is validated through various mobility scenarios in B5G networks. Additionally, it is evaluated using a number of major HO performance metrics, such as HO probability (HOP), HO failure (HOF), HO ping-pong (HOPP), HO latency (HOL), and HO interruption time (HIT). The obtained results have also been compared with other competitive algorithms from the literature. The results show that RHOT-FLC has achieved considerably better performance than other techniques. Furthermore, the RHOT-FLC technique obtains up to 95% HOP reduction, 95.8% in HOF, 97% in HOPP, 94.7% in HOL, and 95% in HIT compared to the competitive algorithms. Overall, RHOT-FLC obtained a substantial improvement of up to 95.5% using the considered HO performance metrics.

Distributed mobility management (DMM) is an attractive approach to address the mobile traffic explosion problem, and thus it is perceived as a promising technology for mobility management in 5G. In this paper, we propose a software-defined networking (SDN) approach for DMM (denoted by SDN-DMM). Unlike the existing approaches for DMM (i.e., network-based or terminal-based), SDN-DMM implements the location and handover management functions at the centralized SDN controller while the packet forwarding function is fully distributed at access routers. Therefore, SDN-DMM can achieve the packet forwarding path optimization and provide significant benefits in terms of network and traffic management.

Vehicular Cloud and autonomous vehicles require a scalable and reliable mobile communication network. LTE and Dedicated Short Range Communication (DSRC) have been trying to fit for such role, yet neither can satisfy all requirement due to inherent architectural limitations. Fortunately the fifth generation mobile network, 5G and Mobile Edge Cloud/Computing (MEC) is around the corner, targeting ultra low packet delay, high reliability, and Gigabit level wireless bandwidth. This paper introduces a unique vehicular MEC architecture where instead of simply off-loading application service to the edge servers on MEC, vehicular communication packets are routed through the MEC network. We discuss in detail how it accommodates vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication with high scalability and guaranteed low packet delay. We also provide an in depth analysis of the pros and cons of our MEC vehicle network design, and address the mobility management issue on edge cloud. Applying distributed mobility management (DMM) operations we are able to make edge cloud IP handoff seamless and transparent. Proof of concept simulations are conducted using NS3.

Handover (HO) is one of the key aspects of next-generation (NG) cellular communication networks that need to be properly managed since it poses multiple threats to quality-of-service (QoS) such as the reduction in the average throughput as well as service interruptions. With the introduction of new enablers for fifth-generation (5G) networks, such as millimetre wave (mm-wave) communications, network densification, Internet of things (IoT), etc., HO management is provisioned to be more challenging as the number of base stations (BSs) per unit area, and the number of connections has been dramatically rising. Considering the stringent requirements that have been newly released in the standards of 5G networks, the level of the challenge is multiplied. To this end, intelligent HO management schemes have been proposed and tested in the literature, paving the way for tackling these challenges more efficiently and effectively. In this survey, we aim at revealing the current status of cellular networks and discussing mobility and HO management in 5G alongside the general characteristics of 5G networks. We provide an extensive tutorial on HO management in 5G networks accompanied by a discussion on machine learning (ML) applications to HO management. A novel taxonomy in terms of the source of data to be utilized in training ML algorithms is produced, where two broad categories are considered; namely, visual data and network data. The state-of-the-art on ML-aided HO management in cellular networks under each category is extensively reviewed with the most recent studies, and the challenges, as well as future research directions, are detailed.

Based on the Long Term Evolution (LTE) coverage and capacity limitation for indoor and interference area, femtocells with low power nodes have been proposed and deployed for add more coverage and capacity in mobile data network. For inter working between femtocells and LTE network handover and mobility management are the important key to achieve the best performance. Cell range of femtocells is smaller than macro cells and main propose for applying and using femtocells are increasing up link coverage. Because of femtocells have low coverage area, so probability of frequently active and no -active for these cells has high value. According to this property, number of handover attempt between LTE to femtocells and femtocells to femtocells has been increased, thus percentage successful handover may be affected, and we face degradation in this index. One important and practical solution is to use mobility robustness feature and load balancing for reduce unnecessarily and handover failure. In this paper we consider on a gradient method and cost function based on Mobility Robustness optimization (MRO) and load balancing scheme to improve the handover and mobility management performance. Self-organizing network(SON) is used to enhance the efficiency and reliability. The simulation results show that the proposed scheme with load balancing has better performance than Non-balancing.

The architectural evolution from hierarchical to flatter networks creates new challenges such as single points of failure and bottlenecks, non-optimal routing paths, scalability problems, and long handover delays. The cellular networks have been hierarchical so that they are largely built on centralized functions based on which their handover mechanisms have been built. They need to be redesigned and/or carefully optimized. The mobility extension to Host Identity Protocol (HIP) proxy, mobile HIP Proxy (MHP), provides a seamless and secure handover for the Mobile Host in the hierarchical network. However, the MHP cannot ensure the same handover performance in flatter network because the MHP has also utilized the features offered by the hierarchical architecture. This paper extends the MHP to distributed mobile HIP proxy (DMHP). The performance evaluation of the DMHP in comparison to MHP and other similar mobility solutions demonstrates that DMHP does indeed perform well in the flatter networks. Moreover, the DMHP supports both efficient multi-homing and handover management for many mobile hosts at the same time to the same new point of attachment.

In this chapter, we describe the most important network protocols supporting modern applications in mobile cellular networks, wireless sensor networks (WSN) and mobile ad hoc networks (MANETs). We first focus on the handover procedure in mobile cellular networks and the network failures due this procedure. The current solutions to enable seamless handover in the existing networks technologies are presented. We then present, in the context of WSN, a framework for model-based design and performance analysis of WSN software applications. WSN are often used for applications with strict non-functional requirements. They, thus, require solid modelling approaches for non-functional attributes of WSN software applications. We finally discuss approaches and cross-layer protocols addressing the problems of security, wireless communications, and network topology changes in MANETs before presenting a framework which aims to study both the benefits of increased awareness between software layers on the same node (inter-layer awareness) and between the same layer over different nodes (intra-layer awareness), and the combination of new/existing protocols designed with a cross-layer criterion.

The 5th generation mobile and wireless communication systems are expected to accommodate exploding traffic, increasing number of devices, and heterogeneous applications driven by proliferation of IoT and M2M technologies. The centralized mobility management architecture in a current mobile core network cannot satisfy these emerging requirements. In this paper, we introduce novel architecture of distributed mobility management and an autonomous and adaptive mobility management scheme which distributes mobility management function on nodes in a mobile core network in accordance with mobility characteristics of UEs and a management policy. We adopt a biologically-inspired adaptation algorithm, called attractor selection, to accomplish adaptive selection taking into account multiple objectives. Through simulation experiments, we conrmed that our proposal could accomplish lower delay, higher load balancing, and lower C-plane overhead comparing to other methods including the current standard.

Security risks and countermeasures of adversarial attacks on AI-driven applications in 6G networks: A survey

Distributed Mobility Management (DMM) is a new trend to overcome the limitations of the current IP mobility management protocols raised by the rapid increasing mobile Internet usages. It is based on the idea of flattening the network architecture and providing mobility service when it is necessary. Although DMM outperforms the well known protocol - Proxy Mobile IPv6 (PMIPv6) in terms of optimizing the network resources consumption, the DMM deployment faces several challenges such as complex address and tunnel management, high signaling cost and high handover latency when the number of addresses and tunnels associated with the mobile node increase (e.g., in case of users moving at a high speed). For this reason, we introduce a hybrid centralized-distributed mobility management architecture (H-DMM) for supporting highly mobile users. The numerical results showed that H-DMM can retain the advantages of DMM while limiting its drawback in comparison with PMIPv6 in terms of signaling cost, packet delivery cost, handover latency and end-to-end delay even in case of users with highly mobility features.