A Group Handover Scheme for Supporting Drone Services in IoT-Based 5G Network Architectures
Abstract and Figures
Next generation mobile networks are expected to integrate multiple drones organized in Flying Ad Hoc Networks (FANETs) to support demanding and diverse services. The highly mobile drones should always be connected to the network in order to satisfy the strict requirements of upcoming applications. As the number of drones increases, they burden the network with the management of signaling and continuous monitoring of the drones during data transmission. Therefore, designing transmission mechanisms for fifth-generation (5G) drone-aided networks and using clustering algorithms for their grouping is of paramount importance. In this paper, a clustering and selection algorithm of the cluster head is proposed together with an efficient Group Handover (GHO) scheme that details how the respective Point of Access (PoA) groups will be clustered. Subsequently, for each cluster, the PoA elects a Cluster Head (CH), which is responsible for manipulating the mobility of the cluster by orchestrating the handover initiation (HO initiation), the network selection, and the handover execution (HO execution) processes. Moreover, the members of the cluster are informed about the impending HO from the CH. As a result, they establish new uplink and downlink communication channels to exchange data packets. In order to evaluate the proposed HO scheme, extensive simulations are carried out for a next-generation drone network architecture that supports Internet of Things (IoT) and multimedia services. This architecture relies on IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs) as well as Long-Term Evolution Advanced (LTE-A) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). Furthermore, the proposed scheme is also evaluated in a real-world scenario using a testbed deployed in a controlled laboratory environment. Both simulation and real-world experimental results verify that the proposed scheme outperforms existing HO algorithms.
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... The appropriate studies of current warfare UAV technologies regarding connectivity management, handover problems, and security features guide the proposed article to implement RHCRB through stabilized components. Skondras et al. [14] discussed fifthgeneration (5G) services in the Internet of Things (IoT) and drone technology improvements in handover mechanisms. The article on drone technology improvements mentions the group handover solutions since the development of swarm UAVs direct the future IoT industries. ...
... In addition, the proposed RHCRB validates node-level and link-level attributes (traffic conditions, retransmissions etc.) (Eqs. (14) and (15)) for initiating data transmission or control packet transmission. An attacker involved into this transmission link via M FR transmitted from unauthorized interfaces shall be detected as suspicious events in each node. ...
... Secondly, attacker fails to satisfy node-level and link-level characteristics of legitimate UAVs (Eqs. (14) and (15)). Data communication and handovers are executed in a secured perimeter in this confidential and authenticated UAV environment. ...
Aerial warfare systems in various countries highly expect Swarm Unmanned Aerial Vehicles (UAVs) and Flying Adhoc Networks (FANETs) for defense stability. However, swarm UAVs face many challenges, like security breaches, malfunctions, link failures, and handover failures. UAVs can easily malfunction by external threats to create data loss, theft, signal jamming, misrouting, false handover, and location spoofing. Failures in UAV handover principles make overall gradual downtime in FANET. Against these issues, existing UAV protection mechanisms deliver location monitoring mechanisms (graphs and trees), multi-link handover mechanisms, and distributed authentication principles. However, the implantation of recent-day techniques may fail against migrating attacker events executed in electronic warfare systems. The existing security methods need improvements for protecting Multi-UAV layers effectively through end-to-end security principles. For this purpose, a new Reactive Handover Coordination System with Regenerative Blockchain (RHCRB) Principles is proposed that takes novel high-security features specially made for swarm UAVs. The proposed RHCRB implements more crucial distributed functions in each UAV on demand. The executed operations of RHCRB comprise trusted location monitoring schemes (internal and cooperative UAV movements), dynamic location-based cost magnitude calculations, regenerative blockchain principles (authentication of each UAV and active edges), confidential link management principles, secure handover coordination, and on-demand topology management principles. The technical aspects of RHCRB build lightweight and shielded handover principles against airfield vulnerabilities. The proposed model suggests implementing an entirely protected handover environment from node localization to handover events. The inspired technical aspects of RHCRB contribute to the swarm UAV environment through confidentiality using Advanced Encryption Standard (AES) and distributed authentication (blockchain-based node and edge management) principles to engage protected handover practices. The experimental section of this article has been tested using testbed in FlyNetSim tool for implementing RHCRB and notable recent security techniques such as the Internet of Vehicles with Decentralized Blockchains (IoV-DB), Group Handover for Internet of Defense (GH-IoD), and Handover and Optimized Security Principles for UAVs (HOOPOE). The results obtained by this system show RHCRB's 8% to 14% of betterment than existing techniques through various measures.
... The appropriate studies of current warfare UAV technologies regarding connectivity management, handover problems, and security features guide the proposed article to implement RHCRB through stabilized components. Skondras et al. [15] discuss fifth-generation (5G) services in the Internet of Things (IoT) and drone technology improvements in handover mechanisms. The article on drone technology improvements mentions the group handover solutions since the development of swarm UAVs direct the future IoT industries. ...
... As equation (14) mentioned, attribute validation function is called to extract and verify node's internal identification entries such as internet address, hardware address, residual energy, neighbor details, etc. Similarly, equation (15) shows the observation and validations of link properties on-demand basis. The proofs of both node and link properties are necessary to ensure the node's legitimacy at initial phase. ...
Aerial warfare systems in various countries highly expect Swarm Unmanned Aerial Vehicles (UAVs) and Flying Adhoc Networks (FANETs) for defense stability. However, swarm UAVs face many challenges, like security breaches, malfunctions, link failures, and handover failures. UAVs can easily malfunction by external threats to create data loss, theft, signal jamming, misrouting, false handover, and location spoofing. Failures in UAV handover principles make overall gradual downtime in FANET. Against these issues, existing UAV protection mechanisms deliver location monitoring mechanisms (graphs and trees), multi-link handover mechanisms, and distributed authentication principles. Anyhow, the implantation of recent-day techniques may fail against migrating attacker events executed in electronic warfare systems. The methods need improvements in protecting Multi-UAV layers through end-to-end security principles. On the research problem, the proposed Reactive Handover Coordination System with Regenerative Blockchain Principles (RHCRB) takes novel high-security features specially made for swarm UAVs. RHCRB implements more crucial distributed functions in each UAV on demand. The executed operations of RHCRB comprise trusted location monitoring schemes (internal and cooperative UAV movements), dynamic location-based cost magnitude calculations, regenerative blockchain principles (authentication of each UAV and active edges), confidential link management principles, secure handover coordination, and on-demand topology management principles. The technical aspects of RHCRB build lightweight and shielded handover principles against airfield vulnerabilities. The proposed model suggests implementing an entirely protected handover environment from node localization to handover events. The inspired technical aspects of RHCRB contribute to the swarm UAV environment through confidential (Advanced Encryption Standard (AES)) and distributed authentication (blockchain-based node and edge management) principles to engage protected handover practices. The experimental section of this article has the testbed in FlyNetSim tool for implementing RHCRB and notable recent security techniques such as the Internet of Vehicles with Decentralized Blockchains (IoV-DB), Group Handover for Internet of Defense (GH-IoD), and Handover and Optimized Security Principles for UAVs (HOOPOE). The results show RHCRB's 8–14% of betterment than existing techniques through various measures.
Several sensor nodes are used in Wireless Sensor Networks (WSNs). A multi-level clustering-based multi-trust model is introduced in WSN. The model’s main intent is to compute trust value for performing secure transmission. Initially, to verify vulnerability, the watchdog counter provides the required trust output. Further, this is intended to build a multi-level trust clustering process. Here, multi-trust is carried out by energy trust, communication trust, and data trust. Hence, multi-trust is compared with a threshold value. Once the trust value is generated, it is given for processing the cluster groups. Due to more multi-trusting, it creates multi-level clustering for security level enhancement. After the cluster group is formed, the major aspect of CH is optimally obtained with a Modified Exploration-based Pelican Optimization Algorithm (ME-POA). Finally, performance is carried out in multi-objective functions, where parameters are defined as distance, delay, energy, and multi-trust. Thus, with the determination of optimal results, the proposed multi-level clustering proves that it offers secure data transmission over WSN.
Drones have attracted extensive attention for their environmental, civil, and military applications. Because of their low cost and flexibility in deployment, drones with communication capabilities are expected to play key important roles in Fifth Generation (5G), Sixth Generation (6G) mobile networks, and beyond. 6G and 5G are intended to be a full-coverage network capable of providing ubiquitous connections for space, air, ground, and underwater applications. Drones can provide airborne communication in a variety of cases, including as Aerial Base Stations (ABSs) for ground users, relays to link isolated nodes, and mobile users in wireless networks. However, variables such as the drone’s free-space propagation behavior at high altitudes and its exposure to antenna sidelobes can contribute to radio environment alterations. These differences may render existing mobility models and techniques as inefficient for connected drone applications. Therefore, drone connections may experience significant issues due to limited power, packet loss, high network congestion, and/or high movement speeds. More issues, such as frequent handovers, may emerge due to erroneous transmissions from limited coverage areas in drone networks. Therefore, the deployments of drones in future mobile networks, including 5G and 6G networks, will face a critical technical issue related to mobility and handover processes due to the main differences in drones’ characterizations. Therefore, drone networks require more efficient mobility and handover techniques to continuously maintain stable and reliable connection. More advanced mobility techniques and system reconfiguration are essential, in addition to an alternative framework to handle data transmission. This paper reviews numerous studies on handover management for connected drones in mobile communication networks. The work contributes to providing a more focused review of drone networks, mobility management for drones, and related works in the literature. The main challenges facing the implementation of connected drones are highlighted, especially those related to mobility management, in more detail. The analysis and discussion of this study indicates that, by adopting intelligent handover schemes that utilizing machine learning, deep learning, and automatic robust processes, the handover problems and related issues can be reduced significantly as compared to traditional techniques.
Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.
Best‐effort service model of traditional routing is gradually hard to meet the personalized demands under the rapid development of network technologies (e.g. 5G and IPv6). Therefore, service customization should be considered. In this work, a service customized routing mechanism based on deep learning in IPv6 network is proposed, which includes deep learning‐based service customization module, reliability evaluation module, and routing calculation module. The first module uses neural network to learn the complex service customization function, which can quickly output win‐win customized service strategies based on user demands. The second module can quantify the reliability of service routing paths, where not only the link status of IPv6 Neighbor Unreachable Detection (NUD) is considered, but also propose link performance weights to ensure the reliability of differentiated service performance. The third module uses the gray wolf optimization algorithm to calculate an optimal routing path to forward services with the customized strategies as the constraints and the maximum reliability and minimum cost as the goal. Finally, the mechanism is tested on the IPv6 Source Address Validation Improvement (SAVI) platform, which can reduce the execution time by 12.25% and improve the average routing reliability, user and ISP satisfaction by 9.0%, 40.45% and 7.4%, respectively.
Drones have evolved significantly in recent years, acquiring greater autonomy and carrier capacity. Therefore, drones can play a substantial role in civil medicine, especially in emergency situations or for the detection and monitoring of disease spread, such as during the COVID-19 pandemic. The aim of this paper is to present the real possibilities of using drones in field rescue operations, as well as in nonsegregated airspace, in order to obtain solutions for monitoring activities and aerial work in support of the public health system in crisis situations. The particularity of our conceptual system is the use of a “swarm” of fast drones for aerial reconnaissance that operate in conjunction, thus optimizing both the search and identification time while also increasing the information area and the operability of the system. We also included a drone with an RF relay, which was connected to a hub drone. If needed, a carrier drone with medical supplies or portable devices can be integrated, which can also offer two-way audio and video communication capabilities. All of these are controlled from a mobile command center, in real time, connected also to the national dispatch center to shorten the travel time to the patient, provide support with basic but life-saving equipment, and offer the opportunity to access remote or difficult-to-reach places. In conclusion, the use of drones for medical purposes brings many advantages, such as quick help, shortened travel time to the patient, support with basic but life-saving equipment, and the opportunity to access remote or difficult-to-reach places.
Fast Proxy Mobile IPv6 (FPMIPv6) is an extension of the PMIPv6 mobility management deployed as part of the next-generation internet protocol. It allows location-independent routing of IP datagrams, based on local mobility to IPv6 hosts without involvement of stations in the IP address signaling. A mobile node keeps its IP address constant as it moves from link to link, which avoids signaling overhead and latency associated with changing IP address. Even though local mobility requirements hold, it entails security threats such as Mobile Node, Mobile Access Gateway, as well as Local Mobility Anchor impersonation that go beyond those already exist in IPv6. As mobile station keeps moving across different serving networks, its IP remains constant during handover, and location privacy may not also be preserved. Moreover, homogeneous network dependence of PMIPv6 is one of the gaps, which FPMIPv6 could not mitigate. FPMIPv6 does not support heterogeneous network handover, for which numerous researchers have proposed Media Independent Handover (MIH) enabled FPMIPv6 schemes to allow fast handover among heterogeneous networks, but in the absence of security solutions. As a comprehensive solution, we propose a new handover authentication scheme and a key agreement protocol for the ‘MIH-enabled Network Only FPMIPv6’ model. As one of the basic requirements, mobility management should minimize signaling overhead, handover delay and power consumption of the mobile node. The proposed scheme improves wireless link overhead (mobile node overhead) by 6-86% as cell radius, wireless failure probability and number of hop vary. The security of the proposed scheme has also been analyzed under BAN logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and its performance has numerically been evaluated through a pre-determined performance matrix and found to be effective and preferably applicable compared with other schemes.
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.
During the last few years, a wide variety of Internet of Drones (IoD) applications have emerged with numerous heterogeneous aerial and ground network elements interconnected and equipped with advanced sensors, computation resources, and communication units. The evolution of IoD networks presupposes the mitigation of several security and privacy threats. Thus, robust authentication protocols should be implemented in order to attain secure operation within the IoD. However, owing to the inherent features of the IoD and the limitations of Unmanned Aerial Vehicles (UAVs) in terms of energy, computational, and memory resources, designing efficient and lightweight authentication solutions is a non-trivial and complicated process. Recently, the development of authentication mechanisms for the IoD has received unprecedented attention. In this paper, up-to-date research studies on authentication mechanisms for IoD networks are presented. To this end, the adoption of conventional technologies and methods, such as the widely used hash functions, Public Key Infrastructure (PKI), and Elliptic-Curve Cryptography (ECC), is discussed along with emerging technologies, including Mobile Edge Computing (MEC), Machine Learning (ML), and Blockchain. Additionally, this paper provides a review of effective hardware-based solutions for the identification and authentication of network nodes within the IoD that are based on Trusted Platform Modules (TPMs), Hardware Security Modules (HSMs), and Physically Unclonable Functions (PUFs). Finally, future directions in these relevant research topics are given, stimulating further work.
One of the current topics of attention in data analysis is the selection of the best normalization technique in the aggregation process when using Multi-Criteria Decision Making (MCDM) methods for solving decision problems. This is particularly critical in complex collaborative decision-making systems dealing with a large variety of heterogeneous data sources. Using different normalization techniques may result in different rankings of alternatives. So, enhancing the accuracy of the final ranking of alternatives could be achieved by selecting the most proper normalization techniques for each MCDM decision problem. In this direction, several attempts have been carried out, however, the lack of coherence and lack of a robust assessment framework persist. This situation encouraged the authors to propose an assessment framework that is enriched with several metrics for the evaluation of different normalization techniques in MCDM problems with the focus on partner/supplier selection in collaborative networks. As an illustration of the approach, in this work we assess different normalization techniques with the Simple Additive Weighting (SAW) method using metrics from the proposed assessment framework and select the most adequate technique for a small case study that is borrowed from literature. The suggested approach contributes to increasing the accuracy of final results for MCDM methods.
Telecommunications among unmanned aerial vehicles (UAVs) have emerged recently due to rapid improvements in wireless technology, low-cost equipment, advancement in networking communication techniques, and demand from various industries that seek to leverage aerial data to improve their business and operations. As such, UAVs have started to become extremely prevalent for a variety of civilian, commercial, and military uses over the past few years. UAVs form a flying ad hoc network (FANET) as they communicate and collaborate wirelessly. FANETs may be utilized to quickly complete complex operations. FANETs are frequently deployed in three dimensions, with a mobility model determined by the work they are to do, and hence differ between vehicular ad hoc networks (VANETs) and mobile ad hoc networks (MANETs) in terms of features and attributes. Furthermore, different flight constraints and the high dynamic topology of FANETs make the design of routing protocols difficult. This paper presents a comprehensive review covering the UAV network, the several communication links, the routing protocols, the mobility models, the important research issues, and simulation software dedicated to FANETs. A topology-based routing protocol specialized to FANETs is discussed in-depth, with detailed categorization, descriptions, and qualitatively compared analyses. In addition, the paper demonstrates open research topics and future challenge issues that need to be resolved by the researchers, before UAVs communications are expected to become a reality and practical in the industry.
Next generation (5G&B) networks will require the design of new architectures and technologies capable of supporting time-sensitive applications. To this aim, the implementation of service chaining as a tool to simplify and lighten the execution of complex tasks by splitting these into simpler functions that can be provided at the network edge can represent a critical improvement. Recently, it has been proposed to implement the network edge by way of Unmanned Aerial Vehicles (UAV) organized as a Flying Ad-Hoc Network (FANET). In this article, we shed light on the new paradigm of service chaining at the network edge and present an approach that aims at solving an optimal virtual network function (VNF) placement problem, taking into account UAV computing and battery limitations, as well as latency constraints, tightly associated to the specific application to be supported. Some numerical results assess the effectiveness of this methodology.