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CLC number: TP393

On-line Access: 2024-06-04

Received: 2023-03-05

Revision Accepted: 2024-06-04

Crosschecked: 2023-08-09

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Citations:  Bibtex RefMan EndNote GB/T7714


Yuexia FU






Qinqin TANG


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Frontiers of Information Technology & Electronic Engineering  2024 Vol.25 No.5 P.685-700


Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network

Author(s):  Yuexia FU, Jing WANG, Lu LU, Qinqin TANG, Sheng ZHANG

Affiliation(s):  China Mobile Research Institute, Beijing 100053, China; more

Corresponding email(s):   fuyuexia@chinamobile.com, wangjingjc@chinamobile.com, lulu@chinamobile.com, qqtang@bupt.edu.cn, zhangsheng@chinamobile.com

Key Words:  Computing force network, Resource scheduling, Performance-based reputation, User satisfaction

Yuexia FU, Jing WANG, Lu LU, Qinqin TANG, Sheng ZHANG. Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network[J]. Frontiers of Information Technology & Electronic Engineering, 2024, 25(5): 685-700.

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publisher="Zhejiang University Press & Springer",

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%T Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network
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%A Lu LU
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%A Sheng ZHANG
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%DOI 10.1631/FITEE.2300156

T1 - Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network
A1 - Yuexia FU
A1 - Jing WANG
A1 - Lu LU
A1 - Qinqin TANG
A1 - Sheng ZHANG
J0 - Frontiers of Information Technology & Electronic Engineering
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2300156

Under the development of computing and network convergence, considering the computing and network resources of multiple providers as a whole in a computing force network (CFN) has gradually become a new trend. However, since each computing and network resource provider (CNRP) considers only its own interest and competes with other CNRPs, introducing multiple CNRPs will result in a lack of trust and difficulty in unified scheduling. In addition, concurrent users have different requirements, so there is an urgent need to study how to optimally match users and CNRPs on a many-to-many basis, to improve user satisfaction and ensure the utilization of limited resources. In this paper, we adopt a reputation model based on the beta distribution function to measure the credibility of CNRPs and propose a performance-based reputation update model. Then, we formalize the problem into a constrained multi-objective optimization problem and find feasible solutions using a modified fast and elitist non-dominated sorting genetic algorithm (NSGA-II). We conduct extensive simulations to evaluate the proposed algorithm. Simulation results demonstrate that the proposed model and the problem formulation are valid, and the NSGA-II is effective and can find the Pareto set of CFN, which increases user satisfaction and resource utilization. Moreover, a set of solutions provided by the Pareto set give us more choices of the many-to-many matching of users and CNRPs according to the actual situation.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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