Recent advances in autonomic provisioning of big data applications on clouds

Rajiv Ranjan, Lizhe Wang*, Albert Y. Zomaya, Dimitrios Georgakopoulos, Xian He Sun, Guojun Wang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

20 Citations (Scopus)

Abstract

Cloud computing assembles large networks of virtualised ICT services such as hardware resources (such as CPU, storage, and network), software resources (such as databases, application servers, and web servers) and applications. Big Data applications have become a common phenomenon in domain of science, engineering, and commerce. Large-scale, heterogeneous, and uncertain Big Data applications are becoming increasingly common, yet current cloud resource provisioning methods do not scale well and nor do they perform well under highly unpredictable conditions (data volume, data variety, data arrival rate, etc.). Much research effort have been paid in the fundamental understanding, technologies, and concepts related to autonomic provisioning of cloud resources for Big Data applications, to make cloud-hosted Big Data applications operate more efficiently, with reduced financial and environmental costs, reduced under-utilisation of resources, and better performance at times of unpredictable workload. Targeting the aforementioned research challenges, this special issue compiles recent advances in Autonomic Provisioning of Big Data Applications on Clouds. The special issue articles are briefly summarized.

Original languageEnglish
Article number7118807
Pages (from-to)101-104
Number of pages4
JournalIEEE Transactions on Cloud Computing
Volume3
Issue number2
DOIs
Publication statusPublished - 1 Apr 2015
Externally publishedYes

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