The Role of Grid Technologies: A Next Level Combat with Big Data

Grid computing has successfully delivered a service oriented architecture that is ubiquitous, dynamic and scalable to the world of networking. It promises to deliver these services to the world of computations that is about to deal with high volume of scalable information involving heterogeneous data i.e., Big data. The Big data needs to explore the new era of technologies and infrastructures that can provide higher level services for managing high volumes of scalable and diverse data. Therefore, it is a timely and challenging opportunity for the Grid technologies to fulfill its promises. This chapter enlightens and examines the key challenges, issues and applications of Grid technologies in the management of Big data.

[1]  Seref Sagiroglu,et al.  Big data: A review , 2013, 2013 International Conference on Collaboration Technologies and Systems (CTS).

[2]  Ku Ruhana Ku-Mahamud,et al.  Big data clustering using grid computing and ant-based algorithm , 2013 .

[3]  G. B. Mund,et al.  A Survey on Scheduling Heuristics in Grid Computing Environment , 2014 .

[4]  Leonardo Neumeyer,et al.  S4: Distributed Stream Computing Platform , 2010, 2010 IEEE International Conference on Data Mining Workshops.

[5]  Xiaoyong Du,et al.  Big data challenge: a data management perspective , 2013, Frontiers of Computer Science.

[6]  Xiongpai Qin.  Making Use of the Big Data: Next Generation of Algorithm Trading , 2012, AICI.

[7]  Avita Katal,et al.  Big data: Issues, challenges, tools and Good practices , 2013, 2013 Sixth International Conference on Contemporary Computing (IC3).

[8]  Peter Kilpatrick,et al.  WIQ: Work-Intensive Query Scheduling for In-Memory Database Systems , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[9]  K. Bakshi,et al.  Considerations for big data: Architecture and approach , 2012, 2012 IEEE Aerospace Conference.

[10]  I. Halcu,et al.  A big data implementation based on Grid computing , 2013, 2013 11th RoEduNet International Conference.

[11]  R. S. D. Wahida Banu,et al.  Communication Aware Co-Scheduling For Parallel Job Scheduling In Cluster Computing , 2011, ACC.

[12]  Lei Gao,et al.  Data Infrastructure at LinkedIn , 2012, 2012 IEEE 28th International Conference on Data Engineering.