Smart handoff technique for internet of vehicles communication using dynamic edge-backup node

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/electronics9030524A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.Published onlin

Adaptive Q-learning-supported Resource Allocation Model in Vehicular Fogs

Urban computing has become a significant driver in supporting the delivery and sharing of services, being a strong ally to intelligent transportation. Smart vehicles present computing and communication capabilities that allow them to enable many autonomous vehicular safety and infotainment applications. Vehicular Cloud Computing (VCC) has already proven to be a technology shifting paradigm harnessing the computation resources from on board units from vehicles to form clustered computing units to solve real world computing problems. However, with the rise of vehicular application use and intermittent network conditions, VCC exhibits many drawbacks. Vehicular Fog computing appears as a new paradigm in enabling and facilitating efficient service and resource sharing in urban environments. Several vehicular resource management works have attempted to deal with the highly dynamic vehicular environment following diverse approaches, e.g. MDP, SMDP, and policy-based greedy techniques. However, the high vehicular mobility causes several challenges compromising consistency, efficiency, and quality of service. RL-enabled adaptive vehicular Fogs can deal with the mobility for properly distributing load and resources over Fogs. Thus, we propose a mobility-based cloudlet dwell time estimation method for accurately estimating vehicular resources in a Fog. Leveraging the CDT estimation model, we devise an adaptive and highly dynamic resource allocation model using mathematical formula for Fog selection, and reinforcement learning for iterative review and feedback mechanism for generating optimal resource allocation policy

Employing Unmanned Aerial Vehicles for Improving Handoff using Cooperative Game Theory

Heterogeneous wireless networks that are used for seamless mobility are expected to face prominent problems in future 5G cellular networks. Due to their proper flexibility and adaptable preparation, remote-controlled Unmanned Aerial Vehicles (UAVs) could assist heterogeneous wireless communication. However, the key challenges of current UAV-assisted communications consist in having appropriate accessibility over wireless networks via mobile devices with an acceptable Quality of Service (QoS) grounded on the users' preferences. To this end, we propose a novel method based on cooperative game theory to select the best UAV during handover process and optimize handover among UAVs by decreasing the (i) end-to-end delay, (ii) handover latency and (iii) signaling overheads. Moreover, the standard design of Software Defined Network (SDN) with Media Independent Handover (MIH) is used as forwarding switches in order to obtain seamless mobility. Numerical results derived from the real data are provided to illustrate the effectiveness of the proposed approach in terms of number of handovers, cost and delay

Mobilidade de comunicações entre veículos e infraestrutura

Mestrado em Engenharia Electrónica e TelecomunicaçõesThe unique characteristics of VANETs, such as high mobility, dynamic topology and frequent loss of connectivity, turn the network selection scheme into a complex problem. In a crowded wireless environment that surrounds us, mainly in urban areas, there is a proliferation and superposition of multiple networks and technologies. Therefore, in order to guarantee connectivity in a transparent way for users, the presence of a connection manager capable of taking informed decisions is crutial. With the increase of mobile traffic, several initiatives have been performed for deploying free/low-cost Wi-Fi hotspots across the cities, in order to offload traffic from the cellular networks into more cost-effective networks. On the one hand, clients benefit from lower data prices, and on the other hand, operators may reduce the amount of cellular infrastructure deployed. Furthermore, users will certainly prefer to connect to a free source of Internet whenever it is available instead of paying for it. Since nodes in VANETs are vehicles, the perception of the surrounding networks is constantly changing, becoming unstable with speed. Therefore, the high mobility of nodes in VANETs jeopardizes the existing network selection mechanisms, which for the network election, are based on Received Signal Strength (RSS) to choose where to connect. Moreover, in a VANET environment, there are no mechanisms capable of taking into account V2V communication according to the WAVE/DSRC technology. Thereby, we propose a connection manager which considers the Wi-Fi networks, cellular networks and the WAVE/DSRC technology to provide connectivity to vehicles. This connection manager is capable of looking into relevant data that is available in VANET-equipped vehicles, increasing the dynamic of the decision process. VCM is a connection manager optimized to operate in VANET scenarios, which takes into account the vehicle speed and heading, the infrastructure position along with their availability and also the number of hops to reach the service provider, besides the link quality. The proposed connection manager is based on an Analytical Hierarchic Process (AHP) that combines several candidate networks, geographic inputs and physical factors to determine the best connection at all times, including the technology and the best network, for each user. To determine the priority of each parameter, we proposed the combination of pairwise comparisons between the criteria involved, according to Saaty's pairwise comparison scale, enhancing the process through simulation and using a Genetic Algorithm (GA). To observe the enhancements provided by VCM, two typical connection managers were implemented: BCM which only looks to the signal quality to choose where to connect, and PCM which takes into account users preference besides the RSS. The evaluation was performed in a Manhattan grid, composed by several vehicles using SUMO's car-following model and with equal turn probabilities, and infrastructure randomly spread across the scenario. The results show that VCM outperforms the other two connection managers, proving that it is capable of operating in general scenarios minimizing the packet loss and with a reduced number of performed handovers.As características únicas das redes veiculares, como a elevada mobilidade, a topologia dinâmica e a frequente perda de conectividade, tornam o esquema da escolha de rede num problema complexo. Num ambiente replecto de redes sem fios, principalmente nas áreas urbanas, existe um aglomerado e sobreposição de varias redes e tecnologias. Assim, para garantir ao utilizador a conectividade de forma transparente, é necessário a presença de um mecanismo capaz de tomar decisões informadas. Com o aumento do trafego móvel, varias iniciativas estão a ser realizadas, disponibilizando hotspots IEEE 802.11 a/g/n (Wi-Fi) pelas cidades, de forma a retirar trafego das redes celulares. Por um lado, os clientes podem usufruir de preços mais baixos e por outro lado, os operadores conseguem reduzir a quantidade de trafego móvel. Alem disso, os utilizadores irão preferir ligar-se a uma rede mais barata/grátis sempre que estiver disponível, desde que tenha boa qualidade. Uma vez que nas redes veiculares os nos são veículos, as redes disponíveis estão sempre a mudar, tornando-se cada vez mais instáveis com o aumento da velocidade. Assim, a mobilidade dos nos põe em causa as soluções existentes para mecanismos de selecção de redes, que maioritariamente para elegerem a melhor rede se baseiam apenas na qualidade do sinal. Alem disso, para um ambiente de redes veiculares, não existem mecanismos de selecção capazes de ter em conta comunicação Vehicle-to-Vehicle (V2V) de acordo com a tecnologia Wireless Access in Vehicular Environments (WAVE) / (Dedicated Short-Range Communications (DSRC). Assim, é proposta a criação de um gestor de conectividade capaz de ter em conta determinados factores que se encontram disponíveis nos veículos Vehicular Ad-hoc NETwork (VANET)-equipados para aumentar a dinâmica do processo de seleccao. O Vanet Connection Manager (VCM) é um gestor de conectividade optimizado para ambientes veiculares, que considera a disponibilidade de redes Wi-Fi, redes celulares e a tecnologia WAVE / DSRC para veículos. Este gestor tem em conta a velocidade e direcção do veículo, a posição das infraestructuras bem como a sua disponibilidade, o numero de saltos ate ao destino, alem da qualidade do sinal. O mecanismo proposto e baseado num Processo Analítico Hierárquico que combina varias redes candidatas, parâmetros geográficos e factores físicos para determinar a melhor ligação possível, incluindo a tecnologia e a melhor rede, para cada utilizador. Para o calculo das prioridades de cada parâmetro, foi proposto o método das combinações emparelhadas desenvolvido por Saaty, optimizando o processo através de simulação e recorrendo a um Algoritmo Genético. Para observar o desempenho do gestor de conectividade, implementaram-se dois gestores típicos de conectividade: Basic Connection Manager (BCM) que apenas tem em conta a força de sinal para escolher o melhor candidato, e o Preference-based Connection Manager (PCM) que tem em conta as preferências dos utilizadores para além da força de sinal. A avaliação foi realizada num cenário Manhattan, composto por vários veículos com modelos de simulação importados do SUMO e infraestrutura aleatoriamente colocada ao longo do cenário. Os resultados mostram que o VCM apresenta melhores resultados que os outros dois gestores de rede, provando que e capaz de operar em qualquer cenário, minimizando as perdas de dados e com um reduzido numero de mudanças de rede

Mobility management in 5G heterogeneous networks

In recent years, mobile data traffic has increased exponentially as a result of widespread popularity and uptake of portable devices, such as smartphones, tablets and laptops. This growth has placed enormous stress on network service providers who are committed to offering the best quality of service to consumer groups. Consequently, telecommunication engineers are investigating innovative solutions to accommodate the additional load offered by growing numbers of mobile users. The fifth generation (5G) of wireless communication standard is expected to provide numerous innovative solutions to meet the growing demand of consumer groups. Accordingly the ultimate goal is to achieve several key technological milestones including up to 1000 times higher wireless area capacity and a significant cut in power consumption. Massive deployment of small cells is likely to be a key innovation in 5G, which enables frequent frequency reuse and higher data rates. Small cells, however, present a major challenge for nodes moving at vehicular speeds. This is because the smaller coverage areas of small cells result in frequent handover, which leads to lower throughput and longer delay. In this thesis, a new mobility management technique is introduced that reduces the number of handovers in a 5G heterogeneous network. This research also investigates techniques to accommodate low latency applications in nodes moving at vehicular speeds

SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS

A finales de los años noventa, y al comienzo del nuevo milenio, las redes inalámbricas han evolucionado bastante, pasando de ser sólo una tecnología prometedora para convertirse en un requisito para las actividades cotidianas en las sociedades desarrolladas. La infraestructura de transporte también ha evolucionado, ofreciendo comunicación a bordo para mejorar la seguridad vial y el acceso a contenidos de información y entretenimiento. Los requisitos de los usuarios finales se han hecho dependientes de la tecnología, lo que significa que sus necesidades de conectividad han aumentado debido a los diversos requisitos de las aplicaciones que se ejecutan en sus dispositivos móviles, tales como tabletas, teléfonos inteligentes, ordenadores portátiles o incluso ordenadores de abordo (On-Board Units (OBUs)) dentro de los vehículos. Para cumplir con dichos requisitos de conectividad, y teniendo en cuenta las diferentes redes inalámbricas disponibles, es necesario adoptar técnicas de Vertical Handover (VHO) para cambiar de red de forma transparente y sin necesidad de intervención del usuario. El objetivo de esta tesis es desarrollar algoritmos de decisión (Vertical Handover Decision Algorithms (VHDAs)) eficientes y escalables, optimizados para el contexto de las redes vehiculares. En ese sentido se ha propuesto, desarrollado y probado diferentes algoritmos de decisión basados en la infraestructura disponible en las actuales, y probablemente en las futuras, redes inalámbricas y redes vehiculares. Para ello se han combinado diferentes técnicas, métodos computacionales y modelos matemáticos, con el fin de garantizar una conectividad apropiada, y realizando el handover hacia las redes más adecuadas de manera a cumplir tanto con los requisitos de los usuarios como los requisitos de las aplicaciones. Con el fin de evaluar el contexto, se han utilizado diferentes herramientas para obtener información variada, como la disponibilidad de la red, el estado de la red, la geolocalizaciónMárquez Barja, JM. (2012). SCALABLE AND EFFICIENT VERTICAL HANDOVER DECISION ALGORITHMS IN VEHICULAR NETWORK CONTEXTS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17869Palanci

Dynamic Q-learning and fuzzy CNN based vertical handover decision for integration of DSRC, mmWave 5G and LTE in internet of vehicles (IoV)

Internet of vehicles commonly known as IOV is a newly emerged area which with the help of internet assisted communication provides the support to the vehicles. Due to the access of more than one radio access network, 5G makes the connectivity ubiquitous. Vehicle mobility demands for handover in such heterogeneous networks. Instead of using better technology for long ranges and other types of traffic, the vehicles are using devoted short range communications at short ranges. Commonly, networks for handovers were used to be selected directly or with the available radio access it used to connect automatically. With the help of this, the hand over occurrence now takes places frequently. This paper is based on the incorporation of DSRC, LTE as well as mm Wave on Internet of vehicles which is integrated with the Handover decision making algorithm, Network Selection and Routing. The decision of the handovers is to ensure that if there is any requirement of the vertical handovers using dynamic Q-learning algorithms in which entropy function is used to predict the threshold according to the characteristics of the environment. The network selection process is done using Fuzzy Convolution Neural Network commonly known as FCNN which makes the fuzzy rules by considering the parameters such as strength of its signal, its distance, the density of the vehicle, the type of its data as well the Line of Sight (LoS). V2V chain routing is presented in such a manner that V2V pairs are also selected with the help of jellyfish optimization algorithm considering three metrics – Vehicle metrics, Channel metrics and Vehicle performance metrics. OMNET++ simulator is the software in which system is developed. The performance evaluation is done according to its Handover Success Probability, Handover Failure, Redundant Handover, Mean Throughput, delay and Packet Loss

An intelligent network selection mechanism for vertical handover decision in vehicular Ad Hoc wireless networks

The design of the Vehicular Ad-hoc Network (VANET) technology is a modern paradigm for vehicular communication on movement. However, VANET's vertical handover (VHO) decision in seamless connectivity is a huge challenge caused by the network topology complexity and the large number of mobile nodes that affect the network traffic in terms of the data transmission and dissemination efficiency. Furthermore, the conventional scheme only uses a received signal strength as a metric value, which shows a lack of appropriate handover metrics that is more suitable in horizontal handover compared to VHO. Appropriate VHO decisions will result in an increase in the network quality of service (QoS) in terms of delay, latency, and packet loss. This study aims to design an intelligent network selection to minimize the handover delay and latency, and packet loss in the heterogeneous Vehicle-to- Infrastructure (V2I) wireless networks. The proposed intelligent network selection is known as the Adaptive Handover Decision (AHD) scheme that uses Fuzzy Logic (FL) and Simple Additive Weighting (SAW) algorithms, namely F-SAW scheme. The AHD scheme was designed to select the best-qualified access point (AP) and base station (BS) candidates without degrading the performance of ongoing applications. The F-SAW scheme is proposed to develop a handover triggering mechanism that generates multiple attributes parameters using the information context of vertical handover decision in the V2I heterogeneous wireless networks. This study uses a network simulator (NS-2) as the mobility traffic network and vehicular mobility traffic (VANETMobiSim) generator to implement a topology in a realistic VANET mobility scenario in Wi-Fi, WiMAX, and LTE networks technologies. The proposed AHD scheme shows an improvement in the QoS handover over the conventional (RSS-based) scheme with an average QoS increased of 21%, 20%, and 13% in delay, latency and packet loss, while Media Independent Handover based (MIH-based) scheme with 12.2%, 11%, and 7% respectively. The proposed scheme assists the mobile user in selecting the best available APs or BS during the vehicles’ movement without degrading the performance of ongoing applications

Design Models for Trusted Communications in Vehicle-to-Everything (V2X) Networks

Intelligent transportation system is one of the main systems which has been developed to achieve safe traffic and efficient transportation. It enables the road entities to establish connections with other road entities and infrastructure units using Vehicle-to-Everything (V2X) communications. To improve the driving experience, various applications are implemented to allow for road entities to share the information among each other. Then, based on the received information, the road entity can make its own decision regarding road safety and guide the driver. However, when these packets are dropped for any reason, it could lead to inaccurate decisions due to lack of enough information. Therefore, the packets should be sent through a trusted communication. The trusted communication includes a trusted link and trusted road entity. Before sending packets, the road entity should assess the link quality and choose the trusted link to ensure the packet delivery. Also, evaluating the neighboring node behavior is essential to obtain trusted communications because some misbehavior nodes may drop the received packets. As a consequence, two main models are designed to achieve trusted V2X communications. First, a multi-metric Quality of Service (QoS)-balancing relay selection algorithm is proposed to elect the trusted link. Analytic Hierarchy Process (AHP) is applied to evaluate the link based on three metrics, which are channel capacity, link stability and end-to-end delay. Second, a recommendation-based trust model is designed for V2X communication to exclude misbehavior nodes. Based on a comparison between trust-based methods, weighted-sum is chosen in the proposed model. The proposed methods ensure trusted communications by reducing the Packet Dropping Rate (PDR) and increasing the end-to-end delivery packet ratio. In addition, the proposed trust model achieves a very low False Negative Rate (FNR) in comparison with an existing model