Autonomous data reallocation technology for high assurance in streaming service system

Kazuaki Wakao*, Tatsuya Tsuda, Xiaodong Lu, Kinji Mori

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the advances of compression, storage and network technologies, online streaming service is becoming more and more popular. However, it is difficult for conventional systems to meet the continuous and heterogeneous requirements from service providers and users simultaneously. This paper introduces an autonomous decentralized VoD system to provide service in heterogeneous quality with adaptability and fewer additional storage volume. In this system, service provider allocates layered streaming data in separated nodes distributed in different levels. The users send pull mobile agents to select appropriate nodes for required service quality. However, for changing preference of users and local congestion, the response time will become worse. To increase the capacity of the edge level with base layered data, Autonomous Data Reallocation Technology is proposed by dynamically reallocating the layered data between the nodes in different levels. Moreover, the tradeoff between Service Level Agreement (SLA) and response time is analyzed. The effectiveness of the proposed technology is proved by comparison with conventional system.

Original languageEnglish
Title of host publicationProceedings - 2011 10th International Symposium on Autonomous Decentralized Systems, ISADS 2011
Pages260-266
Number of pages7
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 10th International Symposium on Autonomous Decentralized Systems, ISADS 2011 - Tokyo and Hiroshima
Duration: 2011 Mar 232011 Mar 27

Other

Other2011 10th International Symposium on Autonomous Decentralized Systems, ISADS 2011
CityTokyo and Hiroshima
Period11/3/2311/3/27

Keywords

  • Autonomous decentralized VoD system
  • Data reallocation technology
  • Video-on-demand

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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