A Novel Multi-Factored Replacement Algorithm for In-Network Content Caching
Lijun Dong, Richard Z. Li · 2019
The paper takes multiple new factors into consideration in designing the optimal replacement algorithm for in-network content caching, i.e. requester's tolerance to common semantics information of requested content, latency requirement on content arrival. The paper proposes a new metric, named importance value, to indicate a content is important enough to be cached in the network. By formulating a 0-1 knapsack optimization problem, an algorithm based on dynamic programming is proposed (named MTT). The performance valuations show the proposed MTT algorithm improves over the existing Least Recently Used (LRU) and popularity based replacement algorithms in achieving shorter response time in various content popularity settings.