Abstract
A grid is an infrastructure to meet the ongoing demands of science and engineering (Foster et al. in Int J High Perform Comput Appl 13(3):200–222, 2001) [1]. In the midst of the 1980s and the 1990s, researchers observed that parallel computing and distributed computing was not only sufficient for solving the biggest challenges of engineering problems. They needed some mechanism which could utilize the power of distributed as well as parallel computing. Grid computing (Foster and Kesselmen in The grid: blueprint for a future computing infrastructure. Morgan Kaufmann Publishers, pp 1–593, 1999; Jacob et al. in Introduction to grid computing, 1st edn., 2005) [2, 3] was the solution to their problem. But working in a grid environment is not really easy since the grid users are increasing and services are becoming commercial, so it is desirable to free the users from the load of job handling. The grid scheduler or resource broker performs the task of job handling such as resource management and fulfilling user requirements. In this chapter, an anatomy of grid schedulers has been discussed which discusses intrinsic properties of different grid schedulers.
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References
Foster I, Kesselman C, Tuecke S (2001) The anatomy of the grid: enabling scalable virtual organisations. Int J High Perform Comput Appl 15(3):200–222
Foster I, Kesselmen C (1999) The grid: blueprint for a future computing infrastructure. Morgan Kaufmann Publishers, pp 1–593
Jacob B et al (2005) Introduction to grid computing, 1st edn. IBM Redbooks, International Technical Support Organisation
Buyya R, Venugopal S (2005) A gentle introduction to grid computing and technologies. Computer Society of India
Krauter K, Buyya R, Maheswaran M (2002) A taxonomy and survey of grid resource management systems for distributed computing. Softw: Practice Experience 32(2):135–164
Casavant TL, Kuhl JG (1988) A taxonomy of scheduling in general-purpose distributed computing systems. IEEE Trans Softw Eng 14(2):141–154
Yu J, Buyya R (2005) A taxonomy of scientific workflow systems for grid computing. SIGMOD Record 34(3):44–49
Ekmecic I, Tartalja I, Milutinovic V (1996) A survey of heterogeneous computing: concepts and systems. Proc IEEE 84(8):1127–1144
Maheswaran M, Krauter K (2000) A parameter-based approach to resource discovery in Grid Computing Systems. In: Proceedings 1st IEEE/ACM international workshop grid computing, 2000, pp 181–190
Punia A, Mittal P (2014) A review: grid computing. Int J Comput Sci Mob Comput 3(4):634–639
Singh MK, Pal S (2011) Five layer security architecture and policies for grid computing system. Int J Comput Sci Inf Technol 2(3):1312–1314
Buyya R (2007) Special issue: middleware for grid computing. Wiley Interscience
Rood B, Lewis MJ (2008) Scheduler on the grid via multi-state resource availability prediction. In: 9th IEEE/ACM international conference, 2008
Venugopal S, Buyya R, Winton L (2004) A grid service broker for scheduling distributed data-oriented applications on global grids. In: Proceedings of the second workshop on middleware for grid computing, 2004, pp 75–80
Abramson D, Giddy J, Kotler L (2000) High performance parametric modeling with Nimrod/g: killer application for the global grid? In: Proceedings of the 14th international parallel and distributed processing symposiums (IPDPS 2000), 2000, pp 520–528
Buyya R, Abramson D, Giddy J (2000) Nimrod/G: an architecture for a resource management system and scheduling system in a global computational grid. In: Proceedings of the international conference on high performance computing in Asia-Pacific Region (HPC Asia 2000), 2000
Berman F, Wolski R (1997) The AppleS project: a status report. In: Proceedings of the 8th NEC research symposium, May 1997
Casanova H, Obertelli G, Berman F, Wolski R (2000) The AppleS parameter sweep template: user level middleware for the grid. In: Proceedings of the IEEE SC 2000, international conference networking ad computing. IEEE CS Press, USA
Xiaohui W, Zhaohui D, Shutao Y, Chang H, Huizhen L, CSF4: A WSRF compliant meta-scheduler. Jilin University
Mohamed H, Epema D (2007) KOALA: a co-allocating grid scheduler. Wiley Interscience
Kim YS, Yu J-L, Hahm J-G, Kim J-S, Lee J-W (2004) Design and implementation of an OGSI-compliant Grid broker service. In: IEEE international symposium on cluster computing and the grid, 2004
Chu X, Venugopal S, Buyya R (2008) Grid resource broker for scheduling component-based applications on distributed resources. In: CyberInfrastructure technologies and applications. Nova Science Publishers
Dumitrescu CL, Foster I (2005) GRUBER: a grid resource usage SLA Broker. Springer, Berlin, pp 465–474
Kwon O-H, Hahm J, Kim S, Lee J (2004) GRASP: a grid resource allocation system based on OGSA. In: Proceedings 13th IEEE international symposium on high performance distributed computing, 2004
Venugopal S, Buyya R, Winton L (2005) A grid service broker for scheduling e-Science applications on global data grids. Concurrency Comput Pract Experience 18(6):685–699
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Ankita, Sahana, S.K. (2019). A Survey on Grid Schedulers. In: Nath, V., Mandal, J. (eds) Nanoelectronics, Circuits and Communication Systems . Lecture Notes in Electrical Engineering, vol 511. Springer, Singapore. https://doi.org/10.1007/978-981-13-0776-8_25
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DOI: https://doi.org/10.1007/978-981-13-0776-8_25
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