Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4954887 | Computer Networks | 2016 | 55 Pages |
Abstract
Based on thorough performance evaluation simulations after exploring different demand levels, video catalogues and mobility scenarios including human walking and automobile mobility, we show that gains from mobility prediction can be high and able to adapt well to temporal locality due to the short timescale of measurements, exceeding cache gains from popularity-only caching up to â41% for low caching demand scenarios. Our model's performance can be further improved at the cost of an added computational overhead by adapting cache replacements by, e.g. in the aforementioned scenarios, â41%. Also, we find that it is easier to benefit from requests popularity with low mobile caching demand and that mobility-based gains grow with popularity skewness, approaching close to the high and robust gains yielded with the model extensions.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Xenofon Vasilakos, Vasilios A. Siris, George C. Polyzos,