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Improving Load Balance for Data-Intensive Computing on Cloud Platforms
2016
2016 IEEE International Conference on Smart Cloud (SmartCloud)
Big Data such as Terabyte and Petabyte datasets are rapidly becoming the new norm for various organizations across a wide range of industries. The widespread data-intensive computing needs have inspired innovations in parallel and distributed computing, which has been the effective way to tackle massive computing workload for decades. One significant example is MapReduce, which is a programming model for expressing distributed computations on huge datasets, and an execution framework for
doi:10.1109/smartcloud.2016.44
dblp:conf/smartcloud/DaiIB16
fatcat:x7vb3ku3srdcfj6xplajx4ugie