학술논문

Evolutionary Adaptation Mechanism for Edge Caching Under Propagation Dynamics
Document Type
Periodical
Source
IEEE Internet of Things Journal IEEE Internet Things J. Internet of Things Journal, IEEE. 11(9):15179-15192 May, 2024
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
Resource management
Heuristic algorithms
Dynamic scheduling
Epidemics
Adaptation models
User experience
Optimization
Belief propagation
edge caching
epidemic model
resource allocation
Language
ISSN
2327-4662
2372-2541
Abstract
In mobile-edge network, adaptive cache placement and resource allocation are vital for meeting the dynamic requirements of users. The current network cache performance has not been fully implemented, due to the lack of comprehensive knowledge of content popularity dynamics and the impact of network resource deployment on the dynamics. In this article, an epidemic model is applied to characterize the content propagation among users. Based on this model, a joint optimization problem of cache placement and base station resource allocation is formulated, maximizing the satisfaction rate of users. The joint optimization problem is decomposed into two subproblems: 1) caching placement and 2) resource allocation. First, the cache placement strategy is determined based on the dynamic propagation model. Second, considering the impact of network decisions on content propagation, a belief propagation-based iterative algorithm is proposed for dynamic resource allocation. Finally, simulation results reveal that the proposed joint optimization algorithm outperforms the benchmark algorithms.