• Login
    View Item 
    •   etd@IISc
    • Division of Electrical, Electronics, and Computer Science (EECS)
    • Computer Science and Automation (CSA)
    • View Item
    •   etd@IISc
    • Division of Electrical, Electronics, and Computer Science (EECS)
    • Computer Science and Automation (CSA)
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Studies In Automatic Management Of Storage Systems

    View/Open
    G25425.pdf (936.8Kb)
    Date
    2015-11-16
    Author
    Pipada, Pankaj
    Metadata
    Show full item record
    Abstract
    Autonomic management is important in storage systems and the space of autonomics in storage systems is vast. Such autonomic management systems can employ a variety of techniques depending upon the specific problem. In this thesis, we first take an algorithmic approach towards reliability enhancement and then we use learning along with a reactive framework to facilitate storage optimization for applications. We study how the reliability of non-repairable systems can be improved through automatic reconfiguration of their XOR-coded structure. To this regard we propose to increase the fault tolerance of non-repairable systems by reorganizing the system, after a failure is detected, to a new XOR-code with a better fault tolerance. As errors can manifest during reorganization due to whole reads of multiple submodules, our framework takes them in to account and models such errors as based on access intensity (ie.BER-biterrorrate). We present and evaluate the reliability of an example storage system with and without reorganization. Motivated by the critical need for automating various aspects of data management in virtualized data centers, we study the specific problem of automatically implementing Virtual Machine (VM) migration in a dynamic environment according to some pre-set policies. This is a problem that requires automated identification of various workloads and their execution environments running inside virtual machines in a non-intrusive manner. To this end we propose AuM (for Autonomous Manager) that has the capability to learn workloads by aggregating variety of information obtained from network traces of storage protocols. We use state of the art Machine Learning tools, namely Multiple Kernel learning ,to aggregate information and show that AuM is indeed very accurate in identifying work loads, their execution environments and is also successful in following user set policies very closely for the VM migration tasks. Storage infrastructure in large-scale cloud data center environments must support applications with diverse, time-varying data access patterns while observing the quality of service. To meet service level requirements in such heterogeneous application phases, storage management needs to be phase-aware and adaptive ,i.e. ,identify specific storage access patterns of applications as they occur and customize their handling accordingly. We build LoadIQ, an online application phase detector for networked (file and block) storage systems. In a live deployment , LoadIQ analyzes traces and emits phase labels learnt online. Such labels could be used to generate alerts or to trigger phase-specific system tuning.
    URI
    https://etd.iisc.ac.in/handle/2005/2489
    Collections
    • Computer Science and Automation (CSA) [392]

    Related items

    Showing items related by title, author, creator and subject.

    • Modeling and Experimental Investigations into Soluble Lead Redox Flow Battery : New Mechanisms 

      Nandanwar, Mahendra N (2018-05-14)
      Continued emission of green house gases has energized research activity worldwide to develop efficient ways to harness renewal energy. The availability of large scale energy storage technologies is essential to make renewal ...
    • MIST : Mlgrate The Storage Too 

      Kamala, R (2017-05-25)
      We address the problem of migration of local storage of desktop users to remote sites. Assuming a network connection is maintained between the source and destination after the migration makes it possible for us to transfer ...
    • Structure And Oxygen Storage Capacity Of Ce1-xMxO2-δ(M=Sn, Zr, Mn, Fe, Co, Ni, Cu, La, Y, Pd, Pt, Ru) : Experimental And Density Functional Theoritical Study 

      Gupta, Asha (2011-06-30)
      Ceria (CeO2) containing materials are the subject of numerous investigations recently owing to their broad range of applications in various fields. Ceria is one of the most important components of three-way catalysts (TWC). ...

    etd@IISc is a joint service of SERC & J R D Tata Memorial (JRDTML) Library || Powered by DSpace software || DuraSpace
    Contact Us | Send Feedback | Thesis Templates
    Theme by 
    Atmire NV
     

     

    Browse

    All of etd@IIScCommunities & CollectionsTitlesAuthorsAdvisorsSubjectsBy Thesis Submission DateThis CollectionTitlesAuthorsAdvisorsSubjectsBy Thesis Submission Date

    My Account

    LoginRegister

    etd@IISc is a joint service of SERC & J R D Tata Memorial (JRDTML) Library || Powered by DSpace software || DuraSpace
    Contact Us | Send Feedback | Thesis Templates
    Theme by 
    Atmire NV