Adaptive genetic algorithm inspired energy‐efficient cache deployment strategy for caching‐enabled networks. Issue 5 (11th October 2020)

• Record Type: Journal Article
• Authors: Wang, Liwei
• Is Part Of: Internet technology letters. Volume 4:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-11
• Subjects: adaptive genetic algorithm -- bi‐objective optimization -- cache deployment -- CEN; Internet -- Periodicals; 004.67805
• DOI: 10.1002/itl2.245
• Languages: English
• ISSNs: 2476-1508

Abstract

Abstract : Caching‐Enabled Networks (CEN) has the wide application value due to the feature of in‐network caching, which has attracted more researchers paying attention to the cache deployment. However, different caching strategies cause different network performance, such as cache hit ratio and energy consumption. In fact, although the current strategies can provide the satisfied cache hit ratio, they consume too much energy for completing the cache deployment. In this paper, an energy‐efficient cache deployment strategy is proposed, including two stages. The first stage is the mathematical modeling for cache hit ratio and energy consumption, in which a bi‐objective optimization problem is built. The second stage is the model solving, where the adaptive genetic algorithm is used. The proposed cache deployment is evaluated based on Europe‐GTS network topology, and the experimental results on cache hit ratio and energy consumption demonstrate its feasibility and efficiency. Abstract : The proposed strategy has higher average cache hit ratio than HAEE. Especially for the last group of experiment, the average cache hit ratio of this paper can exceed 99.5%.