In this paper, we propose a network-aware task assignment strategy in shared clusters. By analyzing the relationship between the assignment of both map and ...
It is demonstrated that the network-aware task assignment strategy can shorten the average completion time of MapReduce jobs, as compared to the ...
To deal with this issue, this paper develops a model to analyze the relationship between job completion time and the assignment of both map and reduce tasks ...
Using this, Phurti's flow scheduling strategy allocates net- work bandwidth to the flows of MapReduce jobs in increasing order of maximum sequential-traffic of ...
Oct 22, 2024 · We further design a network-aware task assignment strategy to shorten the completion time of MapReduce jobs in shared clusters. It integrates ...
To deal with this issue, this paper proposes a lightweight networkaware task assignment strategy for MapReduce applications in shared clusters. By analyzing the ...
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A user submits a job comprising of a map function and a reduce function which are subsequently transformed into map and reduce tasks scheduled on slots hosted ...
Dec 16, 2020 · The idea of network scheduling is to schedule the flows or groups of flows (i.e., coflows) generated by tasks, at shared links, based on given ...
Dec 23, 2019 · In this article, we propose and design a hierarchical topology (Hit) aware MapReduce scheduler to minimize overall data traffic cost and hence ...
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Sep 21, 2012 · ABSTRACT. Google's MapReduce has gained significant popularity as a platform for large scale distributed data processing. Hadoop.