Research And Application Of Resource Allocation Problem Based On Bidding Mechanism And Multiple Objectives

Edge computing makes it faster to process the information generated by the Internet of Things,which makes real-time distribution of IoT devices achievable,such as electric vehicle charging stations.Therefore,how to properly allocate these IoT devices to users and maximize the benefits of resource providers is a research hotspot in the new field of cloud computing.In this field,there are many studies on the problem of resource allocation.One of the more widely used methods is resource allocation based on the bidding mechanism.With the resource allocation model in cloud computing,this thesis improves the model of resource allocation for edge computing.The goal of rationally allocating resources and maximizing revenue,designing resource allocation algorithms and price payment algorithms,provides a solution for resource allocation problems in the field of cloud computing.This thesis analyzes the research status of resource allocation and pricing.The current research is based on non-trusted and single demand.Taking the new energy vehicle charging service as an example,the charging service resource allocation problem is ed into a mathematical model.A truthful online charging pile resource allocation and pricing mechanism(OCRA)was proposed by this thesis,combined with bidding mechanism design.This mechanism is characterized by the fact that resource providers can get more revenue while ensuring that user bids are credible.A monotonous heuristic algorithm is proposed on the resource allocation problem.The algorithm designs resource redistribution based on the idea of weighted bipartite graph best matching algorithm,which can ensure the optimal resource allocation and maximize the revenue of resource providers.The pricing algorithm uses the VCG pricing mechanism to ensure that the mechanism is fair and trustworthy.This thesis also considers the user's need for scheduled charging,and proposes an offline multi-target resource allocation and pricing mechanism(CRA)based on the bidding mechanism.The mechanism adopts the idea of maximum benefit priority in the resource allocation algorithm,and adopts the dichotomy price algorithm based on the threshold value in the price payment.Based on the Jingdong Global Operational Optimization Challenge "GOC Urban Logistics Transportation Vehicle Intelligent Scheduling" A dataset,this thesis designs a heuristic algorithm OCRA to obtain a feasible allocation scheme,and compares the OCRA with the available social welfare of the classical algorithm.OCRA has increased social welfare by about 30%compared with traditional algorithms,and can guarantee the advantages of user's bidding credibility,optimal resource allocation,and flexible price.