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NETWORK MEASUREMENT TOOL COMPONENTS FOR ENABLING PERFORMANCE INTELLIGENCE WITHIN CLOUD-BASED APPLICATIONS

Selvadhurai, Arunprasaath

Abstract Details

2013, Master of Science, Ohio State University, Computer Science and Engineering.
Popular applications such as email, photo/video galleries, and file storage are increasingly being supported by cloud platforms in residential, academic and industry communities. The next frontier for these user communities will be to transition `traditional desktops’ that have dedicated hardware and software configurations into `virtual desktop clouds’ that are accessible via thin-clients. In our thesis, we show how the underlying measurement services, with some additional capabilities, can be used as intelligent agents to provide network intelligence within thin-client based virtual desktops applications. The framework leverages principles of software defined networking and features an `unified resource broker’ that uses special `marker packets’ for: (a) “route setup” when handling non-IP traffic between thin-client sites and data centers, (b) “path selection” and “load balancing” of virtual desktop flows to improve the performance of interactive applications and video playback, and to cope with faults such as link-failures or Denial-of-Service cyber-attacks. In addition, we detail our framework implementation within a virtual desktop cloud (VDC) in a multi-domain Global Environment for Network Innovations (GENI). We present empirical results from our experimentation that leverages OpenFlow programmable networking, as well as OnTimeMeasure instrumentation-and-measurement capabilities for validating our framework in GENI under realistic settings. Our results demonstrate the importance of scheduling regulated measurements that can be used for intelligent resource placement decisions. Our results also show the feasibility and benefits of using the measurement services for effective path selection and load balancing between thin-client sites and data centers in VDCs and simulation applications.
Rajiv Ramnath, Dr (Advisor)
Jay Ramanathan, Dr (Committee Member)
Prasad Calyam, Dr (Committee Member)
62 p.

Recommended Citations

Citations

  • Selvadhurai, A. (2013). NETWORK MEASUREMENT TOOL COMPONENTS FOR ENABLING PERFORMANCE INTELLIGENCE WITHIN CLOUD-BASED APPLICATIONS [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367446588

    APA Style (7th edition)

  • Selvadhurai, Arunprasaath. NETWORK MEASUREMENT TOOL COMPONENTS FOR ENABLING PERFORMANCE INTELLIGENCE WITHIN CLOUD-BASED APPLICATIONS. 2013. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1367446588.

    MLA Style (8th edition)

  • Selvadhurai, Arunprasaath. "NETWORK MEASUREMENT TOOL COMPONENTS FOR ENABLING PERFORMANCE INTELLIGENCE WITHIN CLOUD-BASED APPLICATIONS." Master's thesis, Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367446588

    Chicago Manual of Style (17th edition)