4 research outputs found

    Cooperative Computing with Fragmentable and Mergeable Groups

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    This work considers the problem of performing a set of N tasks on a set of P cooperating message-passing processors (P N ). The processors use a group communication service (GCS) to coordinate their activity in the setting where dynamic changes in the underlying network topology cause the processor groups to change over time. GCSs have been recognized as effective building blocks for fault-tolerant applications in such settings. Our results explore the efficiency of fault-tolerant cooperative computation using GCSs. Prior investigation of this area by Dolev et al. [8] focused on competitive lower bounds, non-redundant task allocation schemes and work-efficient algorithms in the presence of fragmentation regroupings. In this work we investigate work-efficient and message-efficient algorithms for fragmentation and merge regroupings. We present an algorithm that uses GCSs and implements a coordinator-based strategy. This algorithm is motivated by the results in [8]. It achieves similar work complexity of O(N f + N) for fragmentations, where f is the number of new groups created by dynamic fragmentations

    Cooperative Computing with Fragmentable and Mergeable Groups

    No full text
    ABSTRACT: This work considers the problem of performing a set of N tasks on a set of P cooperating message-passing processors (P ≤ N). The processors use a group communication service (GCS) to coordinate their activity in the setting where dynamic changes in the underlying network topology cause the processor groups to change over time. GCSs have been recognized as effective building blocks for fault-tolerant applications in such settings. Our results explore the efficiency of fault-tolerant cooperative computation using GCSs. The original investigation of this area by Dolev et al. [8] focused on competitive lower bounds, non-redundant task allocation schemes and work-efficient algorithms in the presence of fragmentation regroupings. In this work we investigate work-efficient and message-efficient algorithms for fragmentation and merge regroupings. We present an algorithm that uses GCSs and implements a coordinatorbased strategy. For the analysis of our algorithm we introduce the notion of view-graphs that represent the partially-ordered view evolution history witnessed by the processors. For fragmentations and merges, the work of the algorithm (defined as the worst case total number of task executions counting multiplicities) is not more than min{N · f + N, N · P}, and the message complexity is no worse than 4(N ·f +N +P ·m), where f and m denote the number of new groups created by fragmentations and merges respectively. Note that the constants are very small and that, interestingly, while the work efficiency depends on the number of groups f created as the result of fragmentations, work does not depend on the number of groups m created as the result of merges
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