Diversified caching algorithm with cooperation between edge servers
Yongxuan Sang, Yukang Guo, Bo Wang, Ying Song
TL;DR
This paper introduces a new caching algorithm for edge servers that improves performance by collaborating between servers and increasing cache diversity.
Contribution
The novel diversified caching method leverages inter-server collaboration to improve cache hit rates and service efficiency in edge computing.
Findings
The proposed method improves cache hit rates by 27.01–37.43%.
It reduces average service delay by 25.57–30.68%.
The algorithm maintains good performance even as the edge computing platform scales.
Abstract
Edge computing makes up for the high latency of the central cloud network by deploying server resources in close proximity to users. The storage and other resources configured by edge servers are limited, and a reasonable cache replacement strategy is conducive to improving the cache hit ratio of edge services, thereby reducing service latency and enhancing service quality. The spatiotemporal correlation of user service request distribution brings opportunities and challenges to edge service caching. The collaboration between edge servers is often ignored in the existing research work for caching decisions, which can easily lead to a low edge cache hit rate, thereby reducing the efficiency of edge resource use and service quality. Therefore, this article proposes a diversified caching method to ensure the diversity of edge cache services, utilizing inter-server collaboration to enhance…
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Taxonomy
TopicsCaching and Content Delivery · IoT and Edge/Fog Computing · Optimization and Search Problems