An approach to model the optimal service provisioning in vehicular cloud networks

Farhoud Jafari Kaleibar, M. Abbaspour
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Abstract

In recent years, the development of the Internet of things has also extended to transportation networks, affecting smart transportation networks. There are many vehicles in the city that do not use their resources (storage, processing and bandwidth) and therefore there is a good potential to use these resources as a cloud. However, the mobility of vehicles poses a challenge in providing and receiving services available in the cloud. On the other hand, service requests are not predictable and require the use of dynamic approaches for service provisioning. In this paper, we try to reduce the effect of these challenges by modeling the existing problem with the customized mathematical model of maximum coverage, and by using the approximate heuristic algorithm in this field. The simulation performed by the heuristic algorithm shows an improvement in terms of service delivery rate and resource efficiency compared to the random allocation mode.
车用云网络中最优服务供给建模方法
近年来,物联网的发展也延伸到交通网络,影响智能交通网络。城市中有许多车辆没有使用它们的资源(存储、处理和带宽),因此有很好的潜力将这些资源用作云。然而,车辆的移动性在提供和接收云中的可用服务方面提出了挑战。另一方面,服务请求是不可预测的,需要使用动态方法来提供服务。在本文中,我们试图通过最大覆盖的定制数学模型对现有问题进行建模,并使用该领域的近似启发式算法来减少这些挑战的影响。启发式算法的仿真结果表明,与随机分配模式相比,启发式算法在服务交付率和资源效率方面都有提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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