• DocumentCode
    643488
  • Title

    Detecting Unstable Conjunctive Locality-Aware Predicates in Large-Scale Systems

  • Author

    Min Shen ; Kshemkalyani, Ajay D. ; Khokhar, Ashfaq

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Illinois at Chicago, Chicago, IL, USA
  • fYear
    2013
  • fDate
    27-30 June 2013
  • Firstpage
    127
  • Lastpage
    134
  • Abstract
    Recently, the concept of locality-aware predicates (LAP) has been proposed. A LAP models a predicate within a local region of the whole network in a large-scale locality driven system, such as WSNs and modular robotics. In such systems, the cost of doing a global predicate detection is high, besides which, a predicate over the state of a local region better captures properties of local interactions. Thus, LAP detection becomes a relevant and interesting problem. In this paper, we explore the problem of detecting unstable conjunctive LAP, and develop a scale-free algorithm by running an interval-based detection algorithm using a vector clock built on-the-fly for processes in the local region. More importantly, we develop the encoded vector clock (EVC) technique. EVC makes detecting unstable conjunctive LAP more practical in large-scale systems by reducing the storage cost.
  • Keywords
    cost reduction; graph theory; mobile computing; storage management; EVC; LAP models; conjunctive locality-aware predicate unstability detection; encoded vector clock technique; global predicate detection; interval-based detection algorithm; large-scale locality driven system; scale-free algorithm; storage cost reduction; undirected graph; Clocks; Complexity theory; Detection algorithms; Large-scale systems; Synchronization; Vectors; Wireless sensor networks; distributed system; encoding; large-scale network; locality-aware; predicate detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Computing (ISPDC), 2013 IEEE 12th International Symposium on
  • Conference_Location
    Bucharest
  • Print_ISBN
    978-1-4799-2967-2
  • Type

    conf

  • DOI
    10.1109/ISPDC.2013.25
  • Filename
    6663573