S. M. Hussain, K. M. Yusof, Shaik Ashfaq Hussain, Rolito Asuncion
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Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. Existing solutions have addressed the issues related to handover and network selection but they have failed to address the need for handover while selecting the network. Previous studies have only mentioned that the network is being selected directly for handover or it was connected to the available radio access. Due to this, the occurrence of handover had to take place frequently. Hence, in this research, the integration of DSRC, LTE, and mmWave 5G is incorporated with handover decision, network selection, and routing algorithms. The handover decision is to ensure whether there is a need for vertical handover by using a dynamic Q-learning algorithm. Then, the network selection is based on a fuzzy-convolution neural network that creates fuzzy rules from signal strength, distance, vehicle density, data type, and line of sight. V2V chain routing is proposed to select V2V pairs using a jellyfish optimization algorithm that takes into account the channel, vehicle characteristics, and transmission metrics. This system is developed in an OMNeT++ simulator and the performances are evaluated in terms of mean handover, handover failure, mean throughput, delay, and packet loss.","PeriodicalId":45623,"journal":{"name":"International Journal on Smart Sensing and Intelligent Systems","volume":"14 1","pages":"1 - 16"},"PeriodicalIF":0.5000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Performance evaluation of vertical handover in Internet of Vehicles\",\"authors\":\"S. M. Hussain, K. M. 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Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. 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引用次数: 5
摘要
车联网(Internet of vehicle, IoV)是智能交通系统(ITS)与物联网(IoT)相结合的产物。物联网的目标是使车辆能够与其他车辆、人类、行人、路边单位和其他基础设施进行通信。V2X通信的两种潜在技术是专用短距离通信(DSRC)和蜂窝网络技术。每种方法都有其优点和局限性。DSRC具有低延迟,但它限制了覆盖范围,并且缺乏频谱可用性。而4G LTE提供高带宽、更宽的小区覆盖范围,但缺点是传输时间间隔高。5G提供更高的数据速率和极低的传输延迟,为目前的无线通信技术带来了巨大的好处,但由于无法穿透物体,因此容易出现阻塞。因此,考虑到上述问题,单一技术将无法完全适应V2X的要求,从而危及安全应用的有效性。因此,为了实现高效的V2X通信,需要与DSRC和蜂窝网络技术相结合。在过去的几年里,一个公开的研究挑战已经引起了研究界的关注,那就是在异构的车联网环境中选择合适的网络进行切换。现有的解决方案已经解决了与切换和网络选择相关的问题,但未能解决在选择网络时需要切换的问题。以前的研究只提到网络被直接选择进行切换,或者它被连接到可用的无线接入。因此,交接的发生不得不频繁。因此,在本研究中,DSRC、LTE和毫米波5G的集成与切换决策、网络选择和路由算法相结合。切换决策是通过动态q学习算法来确定是否需要进行垂直切换。然后,网络选择基于模糊卷积神经网络,该网络根据信号强度、距离、车辆密度、数据类型和视线创建模糊规则。V2V链路由采用海蜇优化算法选择V2V对,该算法综合考虑了信道、车辆特性和传输指标。该系统在omnet++模拟器上开发,并从平均切换、切换失败、平均吞吐量、延迟和丢包等方面对系统性能进行了评估。
Performance evaluation of vertical handover in Internet of Vehicles
Abstract Internet of Vehicles (IoV) is developed by integrating the intelligent transportation system (ITS) and the Internet of Things (IoT). The goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Two potential technologies of V2X communication are dedicated short-range communication (DSRC) and cellular network technologies. Each of these has its benefits and limitations. DSRC has low latency but it limits coverage area and lacks spectrum availability. Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. Existing solutions have addressed the issues related to handover and network selection but they have failed to address the need for handover while selecting the network. Previous studies have only mentioned that the network is being selected directly for handover or it was connected to the available radio access. Due to this, the occurrence of handover had to take place frequently. Hence, in this research, the integration of DSRC, LTE, and mmWave 5G is incorporated with handover decision, network selection, and routing algorithms. The handover decision is to ensure whether there is a need for vertical handover by using a dynamic Q-learning algorithm. Then, the network selection is based on a fuzzy-convolution neural network that creates fuzzy rules from signal strength, distance, vehicle density, data type, and line of sight. V2V chain routing is proposed to select V2V pairs using a jellyfish optimization algorithm that takes into account the channel, vehicle characteristics, and transmission metrics. This system is developed in an OMNeT++ simulator and the performances are evaluated in terms of mean handover, handover failure, mean throughput, delay, and packet loss.
期刊介绍:
nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity