Cost-and-Delay Aware Dynamic Resource Allocation in Federated Vehicular Clouds

Najm, Moustafa; Patra, Moumita; Tamarapalli, Venkatesh

doi:10.1109/tvt.2021.3079912

Cited by 10 publications

(1 citation statement)

References 39 publications

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“…Therefore, the RSUs are not only important network access equipment with providing high-speed message forwarding services for vehicles over high bandwidth links, but also gateway nodes of the surrounding environmental monitoring sensor network, which undertakes the function of transmitting monitoring data to roadside units connected with the Internet [3,4]. Nevertheless, the high-speed and high bandwidth for-warding services require high power consumption [5]. In addition, the RSUs are powered by the electrical grid instead of no-renewable energy, which costs too much, and increased usage of such energy resources will lead to increase carbon dioxide emission.…”

Section: Introductionmentioning

confidence: 99%

The Optimal Packets Scheduling for Buffer-Aid Energy Harvesting RSUs in Cooperative Vehicle Infrastructure System

Shi

Feng

Wang

et al. 2022

Wireless Communications and Mobile Computing

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In this paper, we investigate the optimal packet scheduling for RSU-to-vehicle downlink communication in Cooperative Vehicle Infrastructure System (CVIS). The RSU is powered by a capacity-limited battery storing harvested energy with reliable energy source as backup, which meets requirement of renewable energy and ensures sustainability of communication system. We aim to find the optimal packet scheduling policy that minimizes the data queuing delay under a given the reliable power constraint and downlink availability rate. According to probabilistic scheduling policy, we adopt data buffer queue and harvesting energy queue as the state-space, and determine the transition action by the joint state of packet arrivals and channel state to establish a two-dimensional Markov chain. Based on this, the optimization problem is formulated. By solving the problem and analysing its solution, we derive the optimal transmission parameters and the optimal scheduling policy which turns out to be threshold-based. Simulations are demonstrated to verify the accuracy of the theoretical derivation results.

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Section: Introductionmentioning

confidence: 99%