1,327 research outputs found

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

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    © 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 Network Based Fuzzy Inference System Model For Minimizing Handover Failure in Mobile Networks

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    For seamless connection between mobile users on the same and different mobile technologies there is need for the deployment of a more complex algorithm for a successful switching of mobile users. Signal to interference ratio, speed of the mobile users and traffic distance are the three input used in the Adaptive network based Fuzzy inference system (ANFIS) which is an hybrid of two techniques of artificial intelligence which make it suitable to handle complexities such as ping-pong effect and interference which impair on the quality of service (QoS) during call handover process as the mobile users move from one coverage area (cell) to anothe

    Mobility management in 5G heterogeneous networks

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    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

    Fuzzy Based Vertical Handoff Decision Controller for Future Networks

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    — In Next generation wireless Networks, the received signals (RSS) from different networks do not have a same meaning since each network is composed of its specific characteristics and there is no common pilot signal. Then, RSS comparisons are insufficient for handoff decision and may be inefficient and impractical. A more complex decision criterion that combines a large number of parameters or factors such as monetary cost, bandwidth, and power consumption and user profile is necessary. Though there are a lot works available for vertical handoff decision (VHD) for wireless networks, the selection of best network is still challenging problem. In this paper we propose a Fuzzy based vertical handoff decision controller (FVHDC) Which performs handover decision based on the output of fuzzy based rules

    Fuzzy-logic framework for future dynamic cellular systems

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    There is a growing need to develop more robust and energy-efficient network architectures to cope with ever increasing traffic and energy demands. The aim is also to achieve energy-efficient adaptive cellular system architecture capable of delivering a high quality of service (QoS) whilst optimising energy consumption. To gain significant energy savings, new dynamic architectures will allow future systems to achieve energy saving whilst maintaining QoS at different levels of traffic demand. We consider a heterogeneous cellular system where the elements of it can adapt and change their architecture depending on the network demand. We demonstrate substantial savings of energy, especially in low-traffic periods where most mobile systems are over engineered. Energy savings are also achieved in high-traffic periods by capitalising on traffic variations in the spatial domain. We adopt a fuzzy-logic algorithm for the multi-objective decisions we face in the system, where it provides stability and the ability to handle imprecise data
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