用于无线供电合作 MEC 中个性化服务定制的双级周期互动进化算法

IF 5.3 3区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ning Yang;Hai-Lin Liu
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引用次数: 0

摘要

本文探讨了无线供电合作移动边缘计算(WP-CoMEC)系统中的定价方案,重点关注个性化服务定制。此类系统中的传统定价方案通常采用被动模式,由服务提供商主导,设备所有者跟随。然而,随着个性化需求的增加,本文提出了一种新方法,即设备所有者成为定价方案的主动参与者,从而实现个人定制服务。所提出的定价模型制定了一个双层多目标优化问题,考虑了任务卸载、资源分配和能量收集。这种综合方法确保了更全面的优化过程。为解决双级定价模型带来的计算挑战,本文提出了一种双级周期性交互进化算法(BL-PIEA),它能有效处理混合变量、复杂的目标冲突以及双级定价模型的内嵌套结构。结果表明,BL-PIEA 能有效求解所提出的定价模型,与其他算法相比,它在缩短运行时间和节省评估预算方面表现出色。通过BL-PIEA求解所提出的双层定价模型,服务提供商可以制定出更好的定价方案,满足设备所有者的要求,从而实现良好的个性化服务定制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Bilevel Periodically Interactive Evolutionary Algorithm for Personalized Service Customization in Wireless-Powered Cooperative MEC
This article addresses the pricing scheme in a wireless-powered cooperative mobile edge computing (WP-CoMEC) system, focusing on personalized service customization. Traditional pricing schemes in such systems often assume a passive mode, with the service provider leading, and the device owner following. However, with the rise of personalized requirements, this paper proposes a novel approach where the device owner becomes an active participant in the pricing scheme, leading to personally customized services. The proposed pricing model formulates a bilevel multi-objective optimization problem, considering task offloading, resource allocation, and energy harvesting. This comprehensive approach ensures a more holistic optimization process. To address the computational challenges posed by the bilevel pricing model, this article proposes a bilevel periodically interactive evolutionary algorithm (BL-PIEA), which efficiently handles mixed variables, complex objective conflicts, and the inner nested structure of the bilevel pricing model. The proposed BL-PIEA is tested on ten instances, and the results indicate that BL-PIEA can effectively solve the proposed pricing model, showcasing superior performance in terms of reduced run time and saved evaluation budgets compared to other algorithms. With the proposed bilevel pricing model solved by BL-PIEA, the service provider can make out better pricing schemes that satisfy the device owner's requirements, so as to achieve a good personalized service customization.
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来源期刊
CiteScore
10.30
自引率
7.50%
发文量
147
期刊介绍: The IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) publishes original articles on emerging aspects of computational intelligence, including theory, applications, and surveys. TETCI is an electronics only publication. TETCI publishes six issues per year. Authors are encouraged to submit manuscripts in any emerging topic in computational intelligence, especially nature-inspired computing topics not covered by other IEEE Computational Intelligence Society journals. A few such illustrative examples are glial cell networks, computational neuroscience, Brain Computer Interface, ambient intelligence, non-fuzzy computing with words, artificial life, cultural learning, artificial endocrine networks, social reasoning, artificial hormone networks, computational intelligence for the IoT and Smart-X technologies.
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