LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Cache Replacement Schemes Based on Adaptive Time Window for Video on Demand Services in Femtocell Networks

Photo by jontyson from unsplash

The cache replacement policy is a crucial phase in caching-based systems that deal with the process of selecting applicable cache contents. In this paper, we propose two novel cache replacement… Click to show full abstract

The cache replacement policy is a crucial phase in caching-based systems that deal with the process of selecting applicable cache contents. In this paper, we propose two novel cache replacement algorithms based on the dataset obtained from a typical wireless femto network. In the first algorithm, called Weighted Least Frequently used with an Adaptive Time Window (WLF-ATW), we aim to make a balance between the network's traffic and the recognition of popular contents. The WLF-ATW algorithm takes the frequency and the recency information of files into account to ascertain the popularity of contents. We suggest another new cache replacement policy namely Fairness Scheduling-based with an Adaptive Time Window (FS-ATW) that is based on fairness scheduling in order to minimize the user's access delay. The novelty of our proposed FS-ATW lies in ranking clients according to their last situations that lead to a further user's experience. The effectiveness of these new algorithms is evaluated from the cache hit ratio, transferred byte volume, user's access delay, user's experience, and load balance. A comprehensive numerical evaluation shows that the performance of the proposed WLF-ATW and FS-ATW algorithms is significantly better than some existing cache replacement strategies.

Keywords: adaptive time; time window; replacement; cache replacement

Journal Title: IEEE Transactions on Mobile Computing
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.