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Contract-based scheme for computational resource allocation in cloud-assisted parked vehicular edge computing
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AI
DOI：10.1016/j.phycom.2022.101916.png)
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Abstract
En 中文
Having shown promising performance with high flexibility and efficiency in vehicular edge computing (VEC) network, the parked vehicles (PVs) received an increasing number of attentions in recent years. However, PVs' residual battery power restricts their running time. In addition, there is still no alternate resource pool for the PVs to cope with the emergencies in the previous VEC framework. To alleviate these problems, we model a cloud-assisted parked vehicular edge computing (PVEC) framework, in which the PVs are classified based on their residual battery power. PVs corporate with the cloud servers (CSs) for the computational resources provision. In addition, we formulate the utilities of the service provider (SP) and PVs and design a contract-based resource allocation problem for the maximization of the SP's utility. Considering that it is intractable to solve the optimization problem directly, the primal problem is simplified and decoupled into two sub-problems. To design the optimal contracts, we solve the sub-problems by Lagrangian multiplier method and dual function. Simulation results prove that the utilities of PVs can reach to the maximum when they choose the contract corresponding to their types. In addition, the simulation results illustrate the superiority of proposed scheme over previous schemes in improving the utilities of the SP and social welfare.(c) 2022 Elsevier B.V. All rights reserved.
Keywords:
Parked vehicular edge computing (PVEC)
Cloud assistance
Incentive mechanism
Contract theory
Journal
IF:
2.2
Papers:
360
Citations:
2.6K