Abstract: To satisfy the high data demands in future cellular networks, an ultra-densification approach is introduced to shrink the coverage of base station (BS) and improve the frequency reuse. The gain in capacity is expected but at the expense of increased interference, frequent handovers (HOs), increased HO failure (HOF) rates, increased HO delays, increase in ping pong rate, high energy consumption, increased overheads due to frequent HO, high packet losses and bad user experience mostly in high-speed user equipment (UE) scenarios. This paper presents the general concepts of radio access mobility in cellular networks with possible challenges and current research focus. In this article, we provide an overview of HO management in long-term evolution (LTE) and 5G new radio (NR) to highlight the main differences in basic HO scenarios. A detailed literature survey on radio access mobility in LTE, heterogeneous networks (HetNets) and NR is provided. In addition, this paper suggests HO management challenges and enhancing techniques with a discussion on the key points that need to be considered in formulating an efficient HO scheme.

Abstract: 5G mobile networks provide additional benefits in terms of lower latency, higher data rates, and more coverage, in comparison to 4G networks, and they are also coming close to standardization. For example, 5G has a new level of data transfer and processing speed that assures users are not disconnected when they move from one cell to another; thus, supporting faster connection. However, it comes with its own technical challenges relating to resource management, authentication handover and user privacy protection. In 5G, the frequent displacement of the users among the cells as a result of repeated authentication handovers often lead to a delay, contradicting the 5G objectives. In this paper, we propose a new authentication approach that utilizes blockchain and software defined networking (SDN) techniques to remove the re-authentication in repeated handover among heterogeneous cells. The proposed approach is designed to assure the low delay, appropriate for the 5G network in which users can be replaced with the least delay among heterogeneous cells using their public and private keys provided by the devised blockchain component while protecting their privacy. In our comparison between Proof-of-Work (POW)-based and network-based models, the delay of our authentication handover was shown to be less than 1ms. Also, our approach demonstrated less signaling overhead and energy consumption compared to peer models.

Abstract: Mobile users across edge networks require seamless migration of offloading services. Edge computing platforms must smoothly support these service transfers and keep pace with user movements around the network. However, live migration of offloading services in the wide area network poses significant service handoff challenges in the edge computing environment. In this paper, we propose an edge computing platform architecture which supports seamless migration of offloading services while also keeping the moving mobile user “in service” with its nearest edge server. We identify a critical problem in the state-of-the-art tool for Docker container migration. Based on our systematic study of the Docker container storage system, we propose to leverage the layered nature of the storage system to reduce file system synchronization overhead, without dependence on the distributed file system. In contrast to the state-of-the-art service handoff method in the edge environment, our system yields a 80 percent (56 percent) reduction in handoff time under 5 Mbps (20 Mbps) network bandwidth conditions.

Abstract: In a low earth orbit (LEO) satellite network, handover management across satellite spot beams needs to be addressed to decrease handover times while using network resources efficiently since the speed of LEO satellites is much higher than that of mobile nodes. In this paper, we propose a novel satellite handover strategy based on the potential game for mobile terminals in a LEO satellite communication network. To continue communication with the counterpart, the user has to switch among the covered LEO satellites. In a software-defined satellite network (SDSN) architecture, the satellite handover can be viewed as a bipartite graph. To balance the satellite network workload, we propose a terminal random-access algorithm based on the target of userspace maximization. The simulated handover conducted on a typical LEO satellite network, Iridium, corroborates the effectiveness of the proposed handover strategy.

Abstract: Driven by the increasing number of connected vehicles and related services, powerful communication and computation capabilities are needed for vehicular communications, especially for real-time and safety-related applications. A cellular network consists of radio access technologies, including the current long-term evolution (LTE), the LTE advanced, and the forthcoming 5th generation mobile communication systems. It covers large areas and has the ability to provide high data rate and low latency communication services to mobile users. It is considered the most promising access technology to support real-time vehicular communications. Meanwhile, fog is an emerging architecture for computing, storage, and networking, in which fog nodes can be deployed at base stations to deliver cloud services close to vehicular users. In fog computing-enabled cellular networks, mobility is one of the most critical challenges for vehicular communications to maintain the service continuity and to satisfy the stringent service requirements, especially when the computing and storage resources are limited at the fog nodes. Service migration, relocating services from one fog server to another in a dynamic manner, has been proposed as an effective solution to the mobility problem. To support service migration, both computation and communication techniques need to be considered. Given the importance of protocol design to support the mobility of the vehicles and maintain high network performance, in this paper, we investigate the service migration in the fog computing-enabled cellular networks. We propose a quality-of-service aware scheme based on the existing handover procedures to support the real-time vehicular services. A case study based on a realistic vehicle mobility pattern for Luxembourg scenario is carried out, where the proposed scheme, as well as the benchmarks, are compared by analyzing latency and reliability as well as migration cost.

Abstract: This paper studies handover skipping, which enables handovers between two non-adjacent access points (APs), in light fidelity (LiFi) networks. LiFi is an emerging wireless communication technology, which operates in a way similar to wireless fidelity (WiFi) but uses light waves as a medium. Compared with WiFi, LiFi has a relatively shorter range with a single AP. This could possibly cause more frequent handovers, and thus, handover skipping techniques are required. Conventional handover skipping methods rely on information about the user's trajectory, which is not ready to use at the AP. In this paper, a novel handover skipping scheme based on the reference signal received power (RSRP) is proposed. The new approach combines the value of RSRP and its rate of change to determine the handover target. Since RSRP is already used in the current handover schemes, the proposed method does not require additional feedback. The results show that compared with the standard handover scheme and the conventional handover skipping method, the proposed method can reduce handover rate by up to 29% and 17% and improve throughput by up to 66% and 26%, respectively.

Abstract: Mobile edge computing (MEC) in cyber-physical systems (CPSs) with massive resource-constrained edge computing node (ECN) faces new challenges in security provisioning. The traditional centralized security authentication schemes with low performance are no longer applied for MEC in CPS. Due to the mobility of ECN, it is extraordinarily practical for ECN to establish a security association with another AP once leaving the service area of its current AP. In this paper, we represent the related research and propose a novel and efficient software-defined networking (SDN)-based handover authentication scheme for MEC in CPS (SHAS). An authentication handover module (AHM) in the SDN controller is applied for key distribution and authentication management. Before ECN handovers, the AHM distributes a key to the current serving AP for ECN further handover. Whenever a handover happens, target AP requests the AHM for the one-time session key (OSK) to authenticate the ECN. The target AP and ECN can proceed with the 3-way handshake protocol by the OSK to achieve mutual authentication and secret key confidentiality. Using the logical derivation of Burrows, Abadi, and Needham and formal verification by automated validation of Internet security protocols and applications (AVISPAs), proposed SHAS scheme can get mutual authentication and secret key confidentiality with a strong anti-attack ability. The simulation results show that the SHAS scheme has the characteristics of lower computational delay and less communication resources. Finally, the practical demonstration of our scheme is done using the widely accepted NS-3 simulation.

Abstract: The rapid popularization of multimode terminals that simultaneously run multiple services (such as browsing web pages during a video session) has brought a decent amount of attention to the network selection problem of multimode terminals. However, most network selection algorithms proposed for vertical handoff are only suitable for terminals running a single service. This paper proposes a network selection algorithm for multiservice multimode terminals in heterogeneous wireless networks. The algorithm considers user preferences, network attributes, and service characteristics. Entropy and fuzzy analytic hierarchy process (FAHP) are used to calculate the objective weights of the network attributes and the weights determined by the service characteristics, respectively. The comprehensive weights of network attributes are obtained by combining the user preferences and service priority. At the same time, different utility functions are used to calculate the utility values of the network attributes for multiservice. Finally, the simple additive weighting (SAW) method is used to synthesize the utility values and the comprehensives weights, while the most appropriate network is selected by a technique for order preference by similarity to an ideal solution (TOPSIS) and a threshold. The simulation results show that the proposed algorithm can accurately select the most appropriate network by considering different factors. Compared to the existing two MMT network selection algorithms, it can reduce the number of vertical handovers and obtain better user experience while satisfying user’s preferences and service’s requirements, thus solving the multiservice multimode terminals network selection problem.

Abstract: Resource management in emerging dense heterogeneous network environments (DenseNets) is a challenging issue. The employment of multicast transmissions in this scenario has potential to address the problems. On one hand, the large number of smart user mobile devices and user expectations for high-quality rich media services has determined a growing demand for network resources; in DenseNets, mobile users have to make the choice in terms of the network to connect to, in order to balance energy saving and delivery performance. On the other hand, the proliferation of user accesses to the existing and future network infrastructure will bring along with it the operators need for optimizing the radio resource usage. This paper proposes a hybrid unicast-multicast utility-based network selection algorithm (HUMANS), which offers the additional option of selecting multicast transmissions in the network selection process during video delivery. By serving users with good channel conditions via unicast transmissions and users with poor channel quality conditions via multicast, HUMANS allows outperforming other solutions in terms of outage percentage and average quality of transmission, in both low- and high-density scenarios. Most importantly, at the same time it guarantees operators a more efficient resource utilization.

Abstract: Handover scheme will have significant effects on the data stream stability and signaling exchanging costs in low earth orbit (LEO) mobile satellite network. We propose a multi-attribute decision handover scheme to reduce handover frequency and enhance data stream stability. Three influence factors: receiving signal strength, remaining service time and satellites’ idle channels will be taken into consideration comprehensively and made the handover decision by multi-attribute decision algorithm. Numerical simulations performed for the typical mobile satellite network, viz. Iridium, show that the new scheme could achieve reduction of handover frequency, lower average channel utilization variance and higher average signal strength compared to other three schemes.

Abstract: 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.

Abstract: This work presents an experimental performance study on the wireless communication of a quadrocopter connected to an LTE-Advanced network. Measurements of TCP traffic analyze how the received power level, signal-to-interference ratio, and throughput depend on the flight height. An average throughput of 20 Mb/s in the downlink and 40 Mb/s in the uplink is achieved at 150 m. We also show how the number of line-of-sight links to base stations rises with height and leads to an increased handover rate.

Abstract: Cognitive radio is an innovative technology in the field of wireless communication systems, aimed at significantly improving the use of the radio spectrum while allowing secondary users to access the spectral band opportunistically. Spectrum management mechanism ensures the transmission of data by controlling the efficiency of operation between the primary and secondary networks. The main task of spectrum management is to ensure that secondary users benefit from the spectrum without interfering with primary users. This paper deals with some of the important characteristics of spectrum mobility in the cognitive radio networks. The new management approaches of the mobility and the connection are designed to reduce the latency and loss of information during spectrum handoff, a list of channel safeguard is maintained in this effect, but the maintenance and update are a challenge. In this paper, we describe the reasons and mechanisms of spectrum handoff. Protocols have been developed to illustrate this handoff mechanism. We also make a comparison between the different methods of spectrum handoff. The simulation results obtained confirm that the protocols developed and the proposed method performed better than the pure reactive handoff method.

Abstract: The huge development in the number of Vehicle factories have resulted in many people having lost their life due to accident, which has made vehicular Ad-hoc networks (VANETs) hot topic to enable improved communication between vehicles aimed at reducing the loss of life. The main challenge in this area is vehicle mobility, which has direct effect on network stability. Thus, most previous studies that discussed clustering focused on cluster formation, cluster-head selection and the stability of cluster to reduce the impact of mobility in the network, with little attention given to the clusters when passing from base-station to neighbor base-station. Therefore, this study focused on handover problem that occurs after cluster formation and cluster-head election during cluster passing from base station to base station, known as overlapping area. As the cluster in an overlapping area receives two signals from different base stations, the signal arriving at the cluster becomes weak due to interference between two frequencies resulting in loss of cluster information in the overlapping area. In this study, proposed a novel method named Intelligent Cluster-Head (ICH), which is a controller on two clusters that are used to change uplink between clusters to solve the handover problem in the overlapping area. The proposed method was evaluated with VMaSC-1hop method. The proposed method achieved percentage of packet loss up to 0.8%, percentage of packet delivery ratio (PDR) 99%, percentage of number of disconnected links 0.12% and percentage of network efficiency 99% in the cells edge.

Abstract: Mobile Edge Computing (MEC) and Network Slicing techniques have a potential to augment 5G-IoT network services. Telecommunication operators use a diverse set of radio access technologies to provide services for users. Mobility management is one such service that needs attention for new 5G deployments. The QoS requirements in 5G networks are user specific. Network slicing along with MEC has been promoted as a key enabler for such on-demand service schemes. This paper focuses on radio resource access across heterogeneous networks for mobile roaming users. A unified service architecture is proposed enabling seamless handover between a 5G (New Generation Core) service and a 4G (Evolved Packet Core) service via the network slicing paradigm. An identifier-locator (I-L) concept that allows active source-IP sessions is used to handle the seamless hand-over. Signaling costs, service disruptions and other resource reservation requirements are considered in the evaluation to assure that profit for mobile edge operators is achieved. Simulation experiments are considered to provide performance comparisons against the state-of-the-art Distributed Mobility Management Protocol (DMM).

Abstract: Recently, handover execution has still been damaging 5G latency requirement due to having three states in virtual evolved packet core (vEPC). Here, the desired end-to-end delay (e2eDelay) should be less than 4 m/sec without any mobility interruption on an enhanced mobile broadband (eMBB) service of vEPC. To handle this requirement, we need to focus on the Markov model of e2eDelay. It can be measured by the concatenation of edge and core delays in the downlink eMBB service from a remote source to a mobile user. Here, edge delay is directly affected by the core network via a decreased packet delivery ratio to edge under huge-traffic intensity background. Therefore, target eNodeB decision by considering only edge network can be misleading. To overcome this, we jointly consider edge and core delays, which are differently affected by each handover states: 1) preparation, 2) execution, and 3) completion. The joint consideration of edge and core can be only handled with a novel cost-effective software-defined ultra-dense network (SDUN) framework by dynamically removing state 2). It triggers handover via network-centric monitoring; and then, it predetermines optimal TeNB with a proposed optimization formula and shortest core path according to traffic intensities of OpenFlow switches. Here, SDUN controller is cost-efficient by the proposed parallel runnable algorithms: parallel edge delay optimization and parallel shortest delay path. In the performance evaluation SDUN is first emulated for a specific eMBB traffic, i.e., QUIC based HTTP/3 video content traffic with 1080p resolution, and second simulated in system-level on MATLAB. It meets 5G requirements as follows: SDUN decreases core delay 7.16 m/sec per a UE under huge-traffic intensity and keeps edge delay under 5G requirement with 20% more delivery ratio than conventional one. Moreover, the cost of SDUN controller is analyzed as O(k4log2(k)) and the cost efficiency is observed as the 50% increased scalability level with the acceptable 8% extra virtual memory usage.

Abstract: In order to reduce the handover cost due to network densification, this letter proposes an anchor-based multi-connectivity (MC) architecture and derives compact expressions of handover probabilities (HOPs) through stochastic geometry analysis in user-centric network (UCN). For MC a given user connects with multiple access points (APs), and the best one is chosen as a handover anchor to provide control-plane, which reduces the handover rate. Moreover, HOPs are quantified for a typical user moving with a random direction and a fixed speed in an irregular UCN with APs modeled as a Poisson point process. The simulation and analytical results show that the HOP in control-plane achieves a decrease of more than 40% over the traditional handover scheme in the LTE system.

Abstract: Future millimeter-wave networks will support very high densities of devices and access points. This vastly increases the overhead required for access point selection and beam training. Fortunately, the quasi-optical properties of millimeter-wave channels make location-based network optimization a highly promising technique to reduce control overhead in such millimeter-wave WLANs. In this paper, we extract channel state information from off-the-shelf routers, we use it to design a high accuracy location system, and then show how location information enables the optimization of network operations. The resulting scheme, named LEAP, can predict blockage, optimize access point association, and select the most suitable antenna beam patterns while significantly reducing the beam training overhead. We show that compared to standard state-of-the-art 802.11ad systems, LEAP’s location driven management greatly improves network performance and link stability.

Abstract: This paper proposed a novel deep learning-based relay selection scheme in millimeter wave (mmWave) Device-to-Device (D2D) communication underlying the fifth generation (5G) cellular networks. Relay selection seems to be a promising solution to extend the coverage and solve the blocking problem of mmWave direct communication. In the case of direct path blocking, the base station (BS)/user equipment (UE) has several candidate devices to be selected as a relay. Despite that, conventional scheme when the direct path is blocked, the direct communication link is handover from mmWave to a lower frequency band using a fast session transfer (FST) technique. Such a blocking problem can be solved multi-hop communications by relaying data based on select another device as a relay. Motivated by the importance of selecting the optimal relay which increases reliable connectivity in mmWave communication and expansion of coverage. The proposed deep learning model is developed to overcome the challenges of selected the optimal relay based with low complexity and high efficiency. The proposed scheme considers a deep learning model learns how to predict the best relay for relaying the data in high-reliability communication. The in-depth learning approach is recommended due to its capability in constructing an intelligent model that can take successful decisions and make precise predictions. Simulation results show that the proposed relay selection algorithm outperforms the conventional relay selection in D2D technique in the spectral efficiency and the energy efficiency

Abstract: A target RAN node (3) is configured to: receive, directly from a core network (5), core network context information about a handover of a radio terminal (1) from a first network to the second network; and control communication of the radio terminal (1) based on the core network context information. The target RAN node (3) is further configured to transfer a handover signaling message to a source RAN node on a direct interface (101) in response to receiving the core network context information. The core network context information includes at least one of flow information, slice information, and security-related information. It is thus possible, for example, to provide an inter-RAT handover procedure involving transfer of handover signaling messages on a direct inter-base-station interface.

Abstract: An important aspect of managing multi access point (AP) IEEE 802.11 networks is the support for mobility management by controlling the handover process. Most handover algorithms, residing on the client station (STA), are reactive and take a long time to converge, and thus severely impact Quality of Service (QoS) and Quality of Experience (QoE). Centralized approaches to mobility and handover management are mostly proprietary, reactive and require changes to the client STA. In this paper, we first created an Software-Defined Networking (SDN) modular handover management framework called HuMOR, which can create, validate and evaluate handover algorithms that preserve QoS. Relying on the capabilities of HuMOR, we introduce ABRAHAM, a machine learning backed, proactive, handover algorithm that uses multiple metrics to predict the future state of the network and optimize the load to ensure the preservation of QoS. We compare ABRAHAM to a number of alternative handover algorithms in a comprehensive QoS study, and demonstrate that it outperforms them with an average throughput improvement of up to 139%, while statistical analysis shows that there is significant statistical difference between ABRAHAM and the rest of the algorithms.

Abstract: Perioperative handovers are a complex process that has the potential to lead to patient harm. The lack of standardization among team members present and information provided can lead to failure of communication of vital information. Standardization of the handover process can help mitigate potential errors, but must occur at the local, institutional level. In addition, the process of implementation of the standardized handover process must include measures to ensure sustainability of the initiative. Effective communication is critical to transferring patient care in a way that mitigates harm.

Abstract: In modern mobile networks, we are seeing a huge leap in the uses of traffic by subscribers, so it is becoming increasingly difficult to ensure the proper operation of the network. In this paper, we propose to use an intelligent approach to network management, namely handover management. The main idea is to use neural networks, which, based on knowledge of user mobility, can predict ways of moving a group of subscribers between cells, which provide the maximum effectiveness of the implementation of the handover. From the results, we see that the neural network can predict traffic with an accuracy of more than 90%, and if you use the proper equipment and explore more durable traffic statistics, then this value can be significantly increased.

Abstract: With the increasing demand for real-time road safety services and infotainment applications on vehicles, the development of an efficient wireless mobile communication became crucial for the content delivery of such services in Intelligent Vehicular Networks (IVN). Mobility management enables mobile hosts to communicate over the Internet from foreign networks. However, vehicles' high mobility and the rapid shifts in network topology affect the performance of traditional mobility management protocols. Hence, raising the challenge for seamless wireless communications over IVN. In this paper, we propose a two-tier Machine Learning-based scheme for handover management in intelligent vehicular networks. In the first tier, we use a recurrent neural network model to predict the receiving signal strength of Access Points (APs), to derive a handover trigger decision. In the second tier, a stochastic Markov model is used to select the next access point by utilizing the vehicle flow projections. The performance of the proposed protocol is evaluated using NS-2 simulator and generated vehicles mobility. Simulation results show that the proposed ML-based model outperformed related work in term of prediction accuracy, while the integration of the handover trigger scheme and the access point selection method improved network performance.

Abstract: Low-power wide-area network (LPWAN) multi-radio access technology (RAT) devices promise enabling Internet of Things (IoT) use-cases that simultaneously require high coverage and data rates, and low energy consumption. For such devices, active probing is usually used for discovering if communication between a mobile terminal (MT) and a base station (BS) or a handover of the MT across LPWAN technologies should be initiated. Because of continuous probing, this procedure increases signaling overhead and energy consumption of the MT. Assuming that the location information of the MT is required for enabling an IoT use-case, this information can potentially also be used for enhancing the discovery and vertical handover procedures in heterogeneous LPWANs. Hence, we propose a location-based mechanism for making discovery and handover decisions in outdoor LPWANs. We do that under the assumption that the location of the MT can be estimated with a certain level of localization errors, while the perfectly accurate location information of the BSs are known to the MT. The mechanism grounds the decisions on the expected SNR between the MT and the BS, which removes the need for continuous probing. If the location information of the MT can be estimated with GPS-like accuracy, we demonstrate that the mechanism can achieve more than 90% correct discovery decisions. We also show that the mechanism is highly accurate in determining if a handover between technologies should be initiated. For an order of magnitude less accurate location information (e.g., for SigFox-based fingerprinting), we show that the mechanism can still make reasonable discovery decisions.

Abstract: Multi-tier cellular networks are a cost-effective solution for capacity enhancement in urban scenarios. In these networks, effective mobility strategies are required to assign users to the most adequate layer. In this paper, a data-driven self-tuning algorithm for traffic steering is proposed to improve the overall Quality of Experience (QoE) in multi-carrier Long Term Evolution (LTE) networks. Traffic steering is achieved by changing Reference Signal Received Quality (RSRQ)-based inter-frequency handover margins. Unlike classical approaches considering cell-aggregated counters to drive the tuning process, the proposed algorithm relies on a novel indicator, derived from connection traces, showing the impact of handovers on user QoE. Method assessment is carried out in a dynamic system-level simulator implementing a real multi-carrier LTE scenario. Results show that the proposed algorithm significantly improves QoE figures obtained with classical load balancing techniques.

Abstract: Internet of Things (IoT) can connect billions of devices and services at anytime, anyplace with diverse applications. Heterogeneous network provides Always Best Connected network between the various technologies. We consider a hybrid network among recent Bluetooth and Wi-Fi technologies to provide the IoT applications. Bluetooth low energy (BLE) works with the minimum amount of power and data rate, sufficient to handle the IoT applications. Wi-Fi Alliance also developed the IEEE 802.11ah which is specifically designed for IoT applications. In this paper, we performed heterogeneous wireless network scenario between the advanced IEEE 802.15.1 (BLE) and IEEE 802.11ah (HaLow) based on Receive Signal Strength as threshold parameter for vertical handover. The simulation results show the Bluetooth versions of Basic Rate, BLE, and Wi-Fi (HaLow) network with the data rate increment after the handover.