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  • 1. Brodnik, Andrej
    et al.
    Carlsson, Svante
    Blekinge Institute of Technology, Karlskrona.
    Fredman, Michael L.
    Department of Computer Science, Rutgers University, New Brunswick, NJ.
    Karlsson, Johan
    Luleå tekniska universitet.
    Munro, J. Ian
    School of Computer Science, University of Waterloo, Waterloo, Ontario.
    Worst case constant time priority queue2005In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 78, no 3, p. 249-156Article in journal (Refereed)
    Abstract [en]

    We present a new data structure of size 3M bits, where M is the size of the universe at hand, for realizing a discrete priority queue. When this data structure is used in combination with a new memory topology it executes all discrete priority queue operations in O(1) worst case time. In doing so we demonstrate how an unconventional, but practically implementable, memory architecture can be employed to sidestep known lower bounds and achieve constant time performance.

  • 2.
    Jayaputera, G. T.
    et al.
    Monash University, Melbourne, VIC.
    Zaslavsky, Arkady
    Loke, Seng Wai
    La Trobe University.
    Enabling run-time composition and support for heterogeneous pervasive multi-agent systems2007In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 80, no 12, p. 2039-2062Article in journal (Refereed)
    Abstract [en]

    User needs-driven and computer-supported development of pervasive heterogeneous and dynamic multi-agent systems remains a great challenge for agent research community. This paper presents an innovative approach to composing, validating and supporting multi-agent systems at run-time. Multi-agent systems (MASs) can and should be assembled quasi-automatically and dynamically based on high-level user specifications which are transformed into a shared and common goal-mission. Dynamically generating agents could also be supported as a pervasive service. Heterogeneity of MASs refers to diverse functionality and constituency of the system which include mobile as well as host associated software agents. This paper proposes and demonstrates on-demand and just-in-time agent composition approach which is combined with run-time support for MASs. Run-time support is based on mission cost-efficiency and shared objectives which enable termination, generation, injection and replacement of software agents as the mission evolves at run-time. We present the formal underpinning of our approach and describe the prototype tool - called eHermes, which has been implemented using available agent platforms. Analysis and results of evaluating eHermes are presented and discussed.

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