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OPTIMAL AND INCENTIVE COMPATIBLE PRICING FOR HETEROGENEOUS PERIODS

Journal of Systems Science and Systems Engineering 2008年第1期17卷 50-65页

作者： Jian CHEN Nan ZHANG Shuo HUANG Research Center for Contemporary Management Key Research Institute of Humanities and Social Sciences at Universities School of Economics and Management Tsinghua University Beijing 100084 China

This paper studies a service firm whose business time can be divided into several periods, each providing different value to customers. Heterogeneous service is a major reason resulting in imbalances between supply and demand. Since customers differ in their degree of impatience, firrns can use differential pricing mechanisms to optimize their objectives and match supply with demand in each period, by inducing customers to choose different periods. We study two types of firrns, an internal firm, the objective of which is to maximize the system＇s （including the f＇nan and all the customers） total net value, and a commercial firm, which aims to optimize its own profit. Though impatience factors are customers＇ private information, for each type of firm, we derive the optimal incentive compatible pricing policy, under which all the coming customers will follow the firm＇s assignment, that is, patient customers will buy the service in high-value periods, but their waiting time will be longer, while impatient customers will enter into the low-value periods, but they will be compensated by shorter waiting times. Furthermore, in the internal firm, we also prove that this mechanism enables the decentralization of decisions, while maintaining centralized system-wide optimality. Numerical analysis shows that when there is sufficient capacity, the internal firm does not always need to set lower prices than the commercial firm in every period.

关键词： delay cost queuing differential pricing information asymmetry incentive compatibility

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Service Caching and Task Offloading for Mobile Edge Computing-Enabled Intelligent Connected Vehicles

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 670-679页

作者： HUANG Mengting YI Yuhan ZHANG Guanglin College of Information Science and Technology Donghua UniversityShanghai 201620China

The development of intelligent connected vehicles(ICVs)has tremendously inspired the emergence of a new computing paradigm called mobile edge computing(MEC),which meets the demands of delay-sensitive on-vehicle *** existing studies focusing on the issue of task offloading in ICVs assume that the MEC server can directly complete computation tasks without considering the necessity of service ***,this is unrealistic in practice because a large number of tasks require the use of corresponding third-party libraries and databases,that is,service ***,we investigate the delay optimization in an MEC-enabled ICVs system with multiple mobile vehicles,resource-limited base stations(BSs),and one cloud *** aim to determine the optimal service caching and task offloading decisions to minimize the overall system delay using mixed-integer nonlinear *** address this problem,we first convert it into a quadratically constrained quadratic program and then propose an efficient semidefinite relaxation-based joint service caching and task offloading(JSCTO)algorithm to obtain the service caching and task offloading *** the simulations,we validate the efficiency of our proposed method by setting different numbers of vehicles and the storage capacity of *** results show that our proposed JSCTO algorithm can significantly decrease the total delay of all offloaded tasks compared with the cloud processing only scheme.

关键词： intelligent connected vehicle(ICV) mobile edge computing(MEC) service caching task offloading delay cost

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