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首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >Green Computing in Software Defined Social Internet of Vehicles
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Green Computing in Software Defined Social Internet of Vehicles

机译:绿色计算在软件中定义的社交车辆互联网

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摘要

Social Internet of Vehicles (SIoV) is an evolving vehicular networking framework integrating the next generation smart devices with vehicular communications. Green computing and communication under disruptive vehicular environment is one of the challenging tasks for enabling SIoV. In this context, green traffic data dissemination in SIoV environments is modelled as an NP-hard problem focusing on heterogeneous traffic data, transmission distance from next generation smart devices and probabilistic delay in transmissions due to disruptive vehicular environment. An adopted meta-heuristic solution namely Two-Way Particle Swarm Optimization (TWPSO) is developed for the green traffic data dissemination problem in SIoV considering software defined vehicular network architecture. Extensive simulation experiments were performed to assess the performance of TWPSO as compared to the state-of-the-art techniques. The critical analysis of the comparative results attest the green computing oriented benefits of TWPSO under real SIoV environments.
机译:社交车辆(SIOV)是一种不断发展的车辆网络框架,其集成了具有车辆通信的下一代智能设备。在破坏性车辆环境下的绿色计算和通信是启用Siov的具有挑战性的任务之一。在这种情况下,Siov环境中的绿色交通数据传播被建模为关注异构交通数据的NP难题,从下一代智能设备和由于中断车辆环境引起的传输中的概率延迟的传输距离。考虑到软件定义的车辆网络架构,开发了采用的Meta-heuristic解决方案即双向粒子群优化(TWPSO),用于Siov中的绿色交通数据传播问题。与最先进的技术相比,进行广泛的模拟实验以评估TWPSO的性能。对比率的批判性分析在真正的Siov环境下的Twpso的绿色计算导向效益。

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