• Admin
    UC Research Repository
    View Item 
       
    • UC Home
    • Library
    • UC Research Repository
    • College of Science
    • Science: Theses and Dissertations
    • View Item
       
    • UC Home
    • Library
    • UC Research Repository
    • College of Science
    • Science: Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of the RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    Statistics

    View Usage Statistics

    Reliability-Focused Scheduling with (m, k)-firm Deadlines over Wireless Channels - A Reinforcement-Learning Approach

    Thumbnail
    View/Open
    Matusovsky, Yakir MSc Thesis.pdf (5.444Mb)
    Author
    Matusovsky, Yakir
    Date
    2016
    Permanent Link
    http://hdl.handle.net/10092/12943
    Thesis Discipline
    Computer Science
    Degree Grantor
    University of Canterbury
    Degree Level
    Masters
    Degree Name
    Master of Science

    In wireless radio applications, the quality of an underlying wireless channel is important, however, we know of a few applications that can tolerate some losses. As an example, real-time applications like streaming voice or video do permit packet loss and still retain a bearable service. With respect to quality of service requirement, we embrace one concise method to distinguish between the allowed and forbidden loss patterns. This method is known as the (m; k)- rm deadlines; at least m out of k consecutive packets have to be successfully delivered to their destination. We consider a point to multi- point network with a known population of wireless communication terminals and with one base station periodically polling all terminals. Given limited network resources, a recovery from data losses in such arrangement might be very challenging under high error rates and with large number of nodes. In this thesis, we consider policies that improve quality of multiple periodic streams by retransmission of failed packets. The base scheduler decides which streams to serve with respect to the primary goal of minimizing violation of the stream's deadline. We introduce an algorithm from Reinforcement Learning theory and compare its performance to a few baseline scheduling policies with static channels and channels with time-varying characteristics. We found that although the Learning scheme introduces good performance it doesn't outperform a baseline technique which is based on immediate slot allocation decisions with respect to packet error rate of each stream.

    Collections
    • Science: Theses and Dissertations [3603]
    Rights
    https://canterbury.libguides.com/rights/theses

    UC Research Repository
    University Library
    University of Canterbury
    Private Bag 4800
    Christchurch 8140

    Phone
    364 2987 ext 8718

    Email
    ucresearchrepository@canterbury.ac.nz

    Follow us
    FacebookTwitterYoutube

    © University of Canterbury Library
    Send Feedback | Contact Us