Abstract
In this paper, we present a high performance recovery algorithm for distributed systems in which checkpoints are taken asynchronously. It offers fast determination of the recent consistent global checkpoint (maximum consistent state) of a distributed system after the system recovers from a failure. The main feature of the proposed recovery algorithm is that it avoids to a good extent unnecessary comparisons of checkpoints while testing for their mutual consistency. The algorithm is executed simultaneously by all participating processes, which ensures its fast execution. Moreover, we have presented an enhancement of the proposed recovery idea to put a limit on the dynamically growing lengths of the data structures used. It further reduces the number of comparisons necessary to determine a recent consistent state and thereby reducing further the time of completion of the recovery algorithm. Finally, it is shown that the proposed algorithm offers better performance compared to some related existing works that use asynchronous checkpointing. Povzetek: Opisan je izboljsan postopek okrevanja v porazdeljenih sistemih.
Highlights
Introduction and MotivationIn this paper, we study the problem of partitioning a complete weighted graph into complete subgraphs, each having the same number of vertices, with the objective of minimizing the total edge weights of the resulting subgraphs
We study the problem of partitioning a complete weighted graph into complete subgraphs, each having the same number of vertices, with the objective of minimizing the total edge weights of the resulting subgraphs
Since a supervisor assigned to any given cluster needs to frequently travel between the branches within the clusters, it is desired that the sum of the distances between the branches of a given cluster should be small. This problem can likewise be modelled as a complete graph partitioning problem having 15 vertices, each of which represents a branch, and with n = 3, where the edge weight associated with any pair of vertices is given by the distance between the corresponding branches
Summary
We study the problem of partitioning a complete weighted graph into complete subgraphs, each having the same number of vertices, with the objective of minimizing the total edge weights of the resulting subgraphs.
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