Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network
Special Feature on Coordination of Networking and Computing: Architecture, Theory, and Practice|Updated:2024-06-03
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Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network
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
“In the realm of computing and network convergence, the research progress in the field of computing force networks (CFNs) has been remarkable. Experts have established a reputation model based on the beta distribution function to measure the credibility of computing and network resource providers (CNRPs). They have also proposed a performance-based reputation update model and formalized the problem into a constrained multi-objective optimization problem. By using a modified fast and elitist non-dominated sorting genetic algorithm (NSGA-II), they have found feasible solutions that increase user satisfaction and resource utilization, providing more choices for the many-to-many matching of users and CNRPs.”
Frontiers of Information Technology & Electronic EngineeringVol. 25, Issue 5, Pages: 685-700(2024)
Affiliations:
1.China Mobile Research Institute, Beijing 100053, China
2.Purple Mountain Laboratories, Nanjing 211111, China
3.China Mobile Communications Corporation, Beijing 100033, China
Yuexia FU, Jing WANG, Lu LU, et al. 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.
DOI:
Yuexia FU, Jing WANG, Lu LU, et al. 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. DOI: 10.1631/FITEE.2300156.
Reputation-based joint optimization of user satisfaction and resource utilization in a computing force network