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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

Cited: 0

Clicked: 454

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yuexia FU

https://orcid.org/0009-0001-6096-2039

Jing WANG

https://orcid.org/0009-0006-5747-2115

Lu LU

https://orcid.org/0009-0000-5740-9489

Qinqin TANG

https://orcid.org/0000-0002-3930-7005

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

http://doi.org/10.1631/FITEE.2300156


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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Abstract: 
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.

基于声誉机制的算力网络资源利用率和用户满意度联合优化

付月霞1,王晶1,陆璐1,唐琴琴2,张晟3
1中国移动通信有限公司研究院,中国北京市,100053
2紫金山实验室,中国南京市,211111
3中国移动通信集团有限公司,中国北京市,100033
摘要:随着算力和网络融合的发展,在算力网络(CFN)中统筹考虑多个提供商的算力资源和网络资源逐渐成为一种新趋势。然而,由于每个算网资源提供商(CNRP)只考虑自身利益,与其他CNRP存在竞争关系,因此引入多个CNRP会造成缺乏信任和难以统一调度的问题。此外,多个并发用户的需求各不相同,因此迫切需要研究如何在多对多的基础上优化匹配用户和CNRP,从而提高用户满意度,保证和提高有限资源的利用率。首先采用基于贝塔分布函数的声誉模型衡量CNRP可信度,并提出基于性能的声誉更新模型。其次,将问题形式化为一个约束多目标优化问题,并使用改进的快速精英非支配排序遗传算法(NSGA-II)找到可行解。本文进行大量仿真实验评估所提算法。仿真结果表明,所提模型、问题表述、和NSGA-II是有效的,NSGA-II可以找到CFN的帕累托集,提高用户满意度和资源利用率。此外,帕累托集所提供的一组解决方案根据实际情况为用户和CNRP的多对多匹配问题提供更多选择。

关键词:算力网络;资源调度;基于性能的声誉;用户满意度

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