期刊
IEEE TRANSACTIONS ON MOBILE COMPUTING
卷 19, 期 2, 页码 288-299出版社
IEEE COMPUTER SOC
DOI: 10.1109/TMC.2019.2893917
关键词
Videos; Bit rate; Quality of experience; Approximation algorithms; Servers; Mobile computing; Base stations; Mobile edge computing; edge caching algorithm; quality of experience; multiple bitrate video
资金
- National Key R&D Program of China [2018YFB1004704]
- National Natural Science Foundation of China [61832005, 61501221, 61872171, 61872310]
- Key R&D Program of Jiangsu Province [BE2017152]
- Natural Science Foundation of Jiangsu Province [BK20150588]
- Shenzhen Basic Research Funding Scheme [JCYJ20170818103849343]
- Collaborative Innovation Center of Novel Software Technology
Caching popular videos at mobile edge servers (MESs) has been confirmed as a promising method to improve mobile users (MUs) perceived quality of experience (QoE) and to alleviate the server load. However, with the multiple bitrate encoding techniques prevalently employed in modern streaming services, caching deployment is challenging for the following three facts: (1) cooperative caching should be explored for MUs located at overlapped coverage areas of MESs; (2) there exists tradeoff consideration for caching either high bitrate videos or high diversity videos; and (3) the relationship between MU perceived QoE and MU received bitrate, known as QoE function, varies in different services. Aiming to maximize the MU perceived QoE, we formulate the multiple bitrate video caching problem, and prove this problem is NP-hard for any given positive and strictly increasing QoE function. We then propose a polynomial complexity algorithm based on a general QoE function, which can achieve an approximate ratio arbitrarily close to 1/2. Specifically, for a linear QoE function, we explore useful property of optimal solutions, based on which more efficient algorithms are proposed. We demonstrate the effectiveness of our solutions via both theoretical analysis and extensive simulations.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据