CPA-VoD： Cloud and Peer-Assisted Video on Demand System for Mobile Devices

• Published in: Journal of computer science and technology 2016-11, Vol.31 (6), p.1087-1095
• Main Authors: Cheng, Lei-Gen, Cui, Laizhong, Jiang, Yong
• Format: Article
• Language: English
• Subjects: Adjustment; Analysis; Artificial Intelligence; Bandwidths; Cloud computing; Computer Science; Costs; Data Structures and Information Theory; Devices; Electronic devices; Information Systems Applications (incl.Internet); Leasing; Mobile communication systems; Networks; Operating costs; Pareto optimum; Peer to peer computing; Peers; Popularity; R&D; Regular Paper; Research & development; Servers; Service introduction; Software Engineering; Streaming media; Studies; Theory of Computation; User behavior; Video on demand; Wireless networks; 内存缓存; 内容提供商; 动态调整; 对等; 帕累托原理; 用户行为; 移动设备; 视频点播系统
• ISSN: 1000-9000; 1860-4749
• DOI: 10.1007/s11390-016-1684-9

With the rapid development of WiFi and 3G/4G, people tend to view videos on mobile devices. These devices are ubiquitous but have small memory to cache videos. As a result, in contrast to traditional computers, these devices aggravate the network pressure of content providers. Previous studies use CDN to solve this problem. But its static leasing mechanism in which the rental space cannot be dynamically adjusted makes the operational cost soar and incompatible with the dynamically video delivery. In our study, based on a thorough analysis of user behavior from Tencent Video, a popular Chinese on-line video share platform, we identify two key user behaviors. Firstly, lots of users in the same region tend to watch the same video. Secondly, the popularity distribution of videos conforms with the Pareto principle, i.e., the top 20% popular videos own 80% of all video traffic. To turn these observations into silver bullet, we propose and implement a novel cloud- and peer-assisted video on demand system （CPA-VoD）. In the system, we group users in the same region as a peer swarm, and in the same peer swarm, users can provide videos to other users by sharing their cached videos. Besides, we cache the 10% most popular videos in cloud servers to further alleviate the network pressure. We choose cloud servers to cache videos because the rental space can be dynamically adjusted. According to the evaluation on a real dataset from Tencent Video, CPA-VoD alleviates the network pressure and the operation cost excellently, while only 20.9% traffic is serviced by the content provider.