A Comparative Analysis of Resource Management in Cloud and Grid Computing

Cloud computing and Grid computing are two intricately connected concepts which are very popular among researchers as well as users because of its efficient resource management capability. Numbers of definitions have been given till now for Cloud and Grid. Both of these computing paradigms are milestones for the revolutionary change that has come into the field of distributed computing but when we talk about resource management then how these two paradigms differ from each other?, which one is better and why? What are the considerations which one has to think upon while using any of these two? In this paper we have tried to answer all these questions by doing a 360 degree comparative analysis in context of resource management. In the first section we have given an introduction of Grid and Cloud Computing paradigm and have described the Grids and Clouds resource management. In the next section we have explained the concepts whose understanding is must in order to understand the challenges faced by these two computing paradigms. In the next section we have presented a table which gives a comparative overview of these two computing paradigms. We have tried to bring out the challenges being faced today by these two computing paradigms. Finally we have drawn some conclusions based on our analysis and have suggested some future work in this area.

[1]  Alexander S. Szalay,et al.  Accelerating large-scale data exploration through data diffusion , 2008, DADC '08.

[2]  Ian Foster,et al.  Monitoring and Discovery in a Web Services Framework: Functionality and Performance of Globus Toolkit MDS4 , 2006 .

[3]  Yong Zhao,et al.  Chimera: a virtual data system for representing, querying, and automating data derivation , 2002, Proceedings 14th International Conference on Scientific and Statistical Database Management.

[4]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[5]  Gregor von Laszewski,et al.  Swift: Fast, Reliable, Loosely Coupled Parallel Computation , 2007, 2007 IEEE Congress on Services (Services 2007).

[6]  Paul T. Groth,et al.  Recording and using provenance in a protein compressibility experiment , 2005, HPDC-14. Proceedings. 14th IEEE International Symposium on High Performance Distributed Computing, 2005..

[7]  Ian T. Foster,et al.  Condor-G: A Computation Management Agent for Multi-Institutional Grids , 2004, Cluster Computing.

[8]  Ian T. Foster,et al.  The data grid: Towards an architecture for the distributed management and analysis of large scientific datasets , 2000, J. Netw. Comput. Appl..

[9]  Yong Zhao,et al.  Falkon: a Fast and Light-weight tasK executiON framework , 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).

[10]  Jing Hua,et al.  Service-Oriented Architecture for VIEW: A Visual Scientific Workflow Management System , 2008, 2008 IEEE International Conference on Services Computing.

[11]  Katarzyna Keahey,et al.  Contextualization: Providing One-Click Virtual Clusters , 2008, 2008 IEEE Fourth International Conference on eScience.

[12]  Ian T. Foster,et al.  The Community Authorization Service: Status and Future , 2003, ArXiv.

[13]  Wang Chiew Tan Provenance in Databases: Past, Current, and Future , 2007, IEEE Data Eng. Bull..

[14]  Yogesh L. Simmhan,et al.  A survey of data provenance in e-science , 2005, SGMD.

[15]  David Abramson,et al.  Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid , 2000, Proceedings Fourth International Conference/Exhibition on High Performance Computing in the Asia-Pacific Region.

[16]  R. Buyya,et al.  Market-Oriented Grid and Utility Computing , 2009 .

[17]  Klara Nahrstedt,et al.  A distributed resource management architecture that supports advance reservations and co-allocation , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[18]  Message Passing Interface Forum MPI: A message - passing interface standard , 1994 .

[19]  Edward A. Lee,et al.  Scientific workflow management and the Kepler system , 2006, Concurr. Comput. Pract. Exp..

[20]  Ian T. Foster,et al.  Globus: a Metacomputing Infrastructure Toolkit , 1997, Int. J. High Perform. Comput. Appl..

[21]  Ian T. Foster,et al.  MPICH-G2: A Grid-enabled implementation of the Message Passing Interface , 2002, J. Parallel Distributed Comput..

[22]  Ian T. Foster,et al.  Virtual workspaces: Achieving quality of service and quality of life in the Grid , 2005, Sci. Program..

[23]  Yong Zhao,et al.  A Logic Programming Approach to Scientific Workflow Provenance Querying , 2008, IPAW.