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SCALABLE HYBRID DATA DISSEMINATION FOR INTERNET HOT SPOTS

Zhang, Wenhui
http://rave.ohiolink.edu/etdc/view?acc_num=case1168985477

Abstract Details

2007, Doctor of Philosophy, Case Western Reserve University, Computing and Information Science.
Server scalability can be greatly enhanced with hybrid data dissemination. Hybrid data dissemination uses a combination of multicast and unicast techniques. Multicast is ideal for popular data that are of interest to most clients. Multicast aggregates multiple unicast data transfers into a single transmission and is thus more scalable than traditional unicast. On the other hand, multicast is inappropriate for unpopular data since it would force unwanted contents on most clients. Therefore, unpopular data is transferred with traditional unicast. As a result, hybrid data dissemination would ideally achieve scalable utilization of server and network resources while avoiding the reception of unneeded contents. In this dissertation, we first present a deployment framework for hybrid data delivery to support web data dissemination. The framework significantly improves the scalability of web servers. Second, we study a fundamental problem in hybrid data delivery: document selection, which determines the data transfer method that is most appropriate for each data item. We individuate special challenges, such as scalable and robust popularity estimation, appropriate classification of documents, and unpopular large documents. We propose solutions to these problems and evaluate them with collected traces and in the real Internet. Third, we examine the multicast push performance with application-perceived performance criteria. We give both theoretical and experimental analysis on the problem. Finally, we devise an efficient and effective application level protocol for transferring application data on a multicast channel.
Vincenzo Liberatore (Advisor)
121 p.
Computer Science
scalability; middleware; multicast; Internet

Recommended Citations

Citations

  • Zhang, W. (2007). SCALABLE HYBRID DATA DISSEMINATION FOR INTERNET HOT SPOTS [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1168985477

    APA Style (7th edition)

  • Zhang, Wenhui. SCALABLE HYBRID DATA DISSEMINATION FOR INTERNET HOT SPOTS. 2007. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1168985477.

    MLA Style (8th edition)

  • Zhang, Wenhui. "SCALABLE HYBRID DATA DISSEMINATION FOR INTERNET HOT SPOTS." Doctoral dissertation, Case Western Reserve University, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=case1168985477

    Chicago Manual of Style (17th edition)

case1168985477
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© 2007, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.