Title :
Big Data Processing in Cloud Computing Environments
Author :
Changqing Ji ; Yu Li ; Wenming Qiu ; Awada, U. ; Keqiu Li
Author_Institution :
Coll. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian, China
Abstract :
With the rapid growth of emerging applications like social network analysis, semantic Web analysis and bioinformatics network analysis, a variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing technics from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database and data storage scheme. Following the Map Reduce parallel processing framework, we then introduce Map Reduce optimization strategies and applications reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.
Keywords :
cloud computing; data handling; distributed databases; network theory (graphs); optimisation; parallel processing; social sciences; MapReduce optimization strategies; MapReduce parallel processing; application aspects; big data processing mechanisms; cloud architecture; cloud computing environments; cloud data management; cloud database; data storage scheme; large-scale data analysis; large-scale data management; open issues; system aspects; Cloud computing; Computer architecture; Data handling; Data models; Data storage systems; Distributed databases; Information management; Big Data; Cloud Computing; Data Management; Distributed Computing;
Conference_Titel :
Pervasive Systems, Algorithms and Networks (ISPAN), 2012 12th International Symposium on
Conference_Location :
San Marcos, TX
Print_ISBN :
978-1-4673-5064-8
DOI :
10.1109/I-SPAN.2012.9