Mobility prediction method for vehicular network using Markov chain

This paper proposes mobility prediction technique via Markov Chains with an input of user’s mobile data traces to predict the user’s movement in wireless network. The main advantage of this method is prediction will give knowledge of user’s movement in advance even in fast moving vehicle. Furthermore, the information from prediction result will be use to assist handover procedure by reserve resource allocation in advance in vehicular network. This algorithm is simple and can be computed within short time, thus the implementation of this technique will give the significant impact especially on higher speed vehicle. Finally, an experiment is performed using real mobile user data traces as input for Markov chain to predict next user movement. To evaluate the effectiveness of the proposed method, MATLAB simulations are carried out with several users under same location zone. The results show that the proposed method predicts have good performance which is 30 of mobile users achieved 100 of prediction accuracy

Conhecimento da mobilidade do consumidor em redes centradas em informação

Mobile data traffic is expanding significantly since the surge and evolution of wireless communication technologies, leading to the design and implementation of different types of mobile networks. Information Centric Network paradigms have been pointed as an alternative to bypass the restrictions imposed by the traditional IP Networks, such as the one imposed by the mobility of its users. Despite their potential advantages regarding mobile wireless environments, several significant research challenges remain to be addressed, more specifically the communication damage due to handover, causing loss of packets. The scope of this dissertation is the development of NDN-based mechanisms with support for Consumer mobility in two different communication approaches: single content request and publish-subscribe. The proposed schemes address a remote mobility predictor entity, whose purpose is to monitor and anticipate trajectories, while compelling the infrastructure to adjust to the new paths, resulting in an efficient way to manage the consumers’ mobility with the purpose of attaining a better quality of service to users. The implementation and evaluation of the proposed schemes were performed using ndnSIM, through functional and non-functional scenarios. The latter uses real traces of urban mobility and connectivity. The obtained results show that the proposed solution far surpasses the native NDN workflow and the traditional publish-subscribe solutions with respect to content delivery ratio and network overhead.O tráfego de dados móveis tem vindo a crescer significativamente, sobretudo devido à evolução das tecnologias de comunicação sem fios, o que tem vindo a implicar o desenho e implementação de novos e diferentes tipos de redes móveis. Os paradigmas de redes centradas em informação têm sido apontados como uma alternativa para contornar as restrições impostas pelas redes tradicionais IP, nomeadamente a mobilidade dos seus utilizadores. Apesar das potenciais vantagens em relação aos ambientes móveis sem fios, vários desafios de investigação ainda necessitam de ser resolvidos, mais especificamente aqueles relacionados com o processo de handover dos seus utilizadores móveis, levando por vezes à perda de informação. Esta dissertação tem como objetivo o desenvolvimento de mecanismos de suporte à mobilidade do Consumidor para redes ICN, utilizando duas abordagens distintas de comunicação: solicitação única de conteúdo e o modelo publish − subscribe. Os esquemas propostos exploram uma entidade remota de previsão de mobilidade, cujo objetivo é monitorizar e antecipar eventuais trajetórias de posição dos utilizadores móveis, obrigando a infraestrutura a ajustar-se aos novos caminhos do consumidor, resultando numa forma eficiente de gestão de mobilidade dos utilizadores com o objetivo de garantir uma melhor qualidade de serviço. A implementação e avaliação dos esquemas propostos foi realizada utilizando o ndnSIM, em cenários funcionais e não funcionais. Estes últimos utilizam registos reais de mobilidade e conetividade urbana. Os resultados obtidos mostram que a solução proposta ultrapassa significativamenta a versão nativa do NDN e as soluções tradicionais de publish − subscribe, considerando a taxa de entrega de conteúdos e sobrecarga da rede.Mestrado em Engenharia de Computadores e Telemátic

Integrated Sensing and Communications for IoT: Synergies with Key 6G Technology Enablers

The Internet of Things (IoT) and wireless generations have been evolving simultaneously for the past few decades. Built upon wireless communication and sensing technologies, IoT networks are usually evaluated based on metrics that measure the device ability to sense information and effectively share it with the network, which makes Integrated Sensing and Communication (ISAC) a pivotal candidate for the sixth-generation (6G) IoT standards. This paper reveals several innovative aspects of ISAC from an IoT perspective in 6G, empowering various modern IoT use cases and key technology enablers. Moreover, we address the challenges and future potential of ISAC-enabled IoT, including synergies with Reconfigurable Intelligent Surfaces (RIS), Artificial Intelligence (AI), and key updates of ISAC-IoT in 6G standardization. Furthermore, several evolutionary concepts are introduced to open future research in 6G ISAC-IoT, including the interplay with Non-Terrestrial Networks (NTN) and Orthogonal Time-Frequency Space (OTFS) modulation.Comment: 7 pages, 6 figure

5G NR-V2X: Towards Connected and Cooperative Autonomous Driving

This paper is concerned with the key features and fundamental technology components for 5G New Radio (NR) for genuine realization of connected and cooperative autonomous driving. We discuss the major functionalities of physical layer, Sidelink features and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques with an evolution path from existing cellular vehicle-to-everything (V2X) technology towards NR-V2X. Moreover, we envisage and highlight the potential of machine learning for further enhancement of various NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases in autonomous driving

Self-Evolving Integrated Vertical Heterogeneous Networks

6G and beyond networks tend towards fully intelligent and adaptive design in order to provide better operational agility in maintaining universal wireless access and supporting a wide range of services and use cases while dealing with network complexity efficiently. Such enhanced network agility will require developing a self-evolving capability in designing both the network architecture and resource management to intelligently utilize resources, reduce operational costs, and achieve the coveted quality of service (QoS). To enable this capability, the necessity of considering an integrated vertical heterogeneous network (VHetNet) architecture appears to be inevitable due to its high inherent agility. Moreover, employing an intelligent framework is another crucial requirement for self-evolving networks to deal with real-time network optimization problems. Hence, in this work, to provide a better insight on network architecture design in support of self-evolving networks, we highlight the merits of integrated VHetNet architecture while proposing an intelligent framework for self-evolving integrated vertical heterogeneous networks (SEI-VHetNets). The impact of the challenges associated with SEI-VHetNet architecture, on network management is also studied considering a generalized network model. Furthermore, the current literature on network management of integrated VHetNets along with the recent advancements in artificial intelligence (AI)/machine learning (ML) solutions are discussed. Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are identified. Finally, the potential future research directions for advancing the autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table