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20152025
most citedA Survey on Geographically Distributed Big-Data Processing using MapReduce

77 citations · 159 across the 20 of their papers we have counts for

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Showing 2015Show all

6 papers · 1 filter

cs.IT2015

A Survey on 5G: The Next Generation of Mobile Communication

Nisha Panwar, Shantanu Sharma, Awadhesh Kumar Singh

The rapidly increasing number of mobile devices, voluminous data, and higher data rate are pushing to rethink the current generation of the cellular mobile communication. The next…

cs.DB2015

Computing Marginals Using MapReduce

Foto Afrati, Shantanu Sharma, Jeffrey D. Ullman +1

We consider the problem of computing the data-cube marginals of a fixed order (i.e., all marginals that aggregate over dimensions), using a single round of MapReduce. The f…

cs.DB2015★ 8 cited

Meta-MapReduce: A Technique for Reducing Communication in MapReduce Computations

Foto Afrati, Shlomi Dolev, Shantanu Sharma +1

MapReduce has proven to be one of the most useful paradigms in the revolution of distributed computing, where cloud services and cluster computing become the standard venue for com…

cs.NI2015★ 11 cited

On Detecting Termination in Cognitive Radio Networks

Shantanu Sharma, Awadhesh Kumar Singh

The cognitive radio networks are an emerging wireless communication and computing paradigm. The cognitive radio nodes execute computations on multiple heterogeneous channels in the…

cs.DB2015★ 2 cited

Assignment Problems of Different-Sized Inputs in MapReduce

Foto Afrati, Shlomi Dolev, Ephraim Korach +2

A MapReduce algorithm can be described by a mapping schema, which assigns inputs to a set of reducers, such that for each required output there exists a reducer that receives all t…

cs.DB2015★ 2 cited

Assignment of Different-Sized Inputs in MapReduce

Foto Afrati, Shlomi Dolev, Ephraim Korach +2

A MapReduce algorithm can be described by a mapping schema, which assigns inputs to a set of reducers, such that for each required output there exists a reducer that receives all t…