A Dynamic Replication Mechanism in Data Grid Based on a Weighted Priority-based Scheme

Mohammad Samadi Gharajeh*
Young Researchers and Elite Club, Tabriz Branch, Islamic Azad University, Tabriz, Iran.
Periodicity:January - June'2019
DOI : https://doi.org/10.26634/jcc.6.1.15897

Abstract

Replication is one of the popular tools to determine the availability degree of resources (e.g., data files) in data grids. Since data grids involve limited file storages and high computing costs, replication process is very essential in these networks. This paper proposes a dynamic replication mechanism in a data grid that uses a weighted priority-based replication scheme, called WPRS. It specifies a value for existing each in a local storage based on three parameters including price, number of access time, and present time. When a resource is not available for a desired job, it is hired from other sites in the network. The proposed mechanism removes the file having the least value to increase the free space of data storage. Simulation results show that the proposed replication mechanism surpasses some of the existing replication methods in terms of the number of successful jobs, number of non successful jobs, and buy price.

Keywords

Data Grid, Data Replication, Weighted Mechanism, Multi-criteria Selection, Priority-based Scheme.

How to Cite this Article?

Gharajeh, M. S.(2019). A Dynamic Replication Mechanism in Data Grid Based on a Weighted Priority-based Scheme, i-manager's Journal on Cloud Computing, 6(1), 9-18. https://doi.org/10.26634/jcc.6.1.15897

References

[1]. Al Mistarihi, H. H. E., & Yong, C. H. (2008). Replica management in data grid. International Journal of Computer Science and Network Security, 8(6), 22-32.
[2]. Alkhanak, E. N., Lee, S. P., Rezaei, R., & Parizi, R. M. (2016). Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: A review, classifications, and open issues. Journal of Systems and Software, 113, 1-26.
[3]. Chamola, V., Sikdar, B., & Krishnamachari, B. (2017). Delay aware resource management for grid energy savings in green cellular base stations with hybrid power supplies. IEEE Transactions on Communications, 65(3), 1092-1104.
[4]. Chang, R. S., Chang, H. P., & Wang, Y. T. (2008, March). A dynamic weighted data replication strategy in data grids. In 2008 IEEE/ACS International Conference on Computer Systems and Applications (pp. 414-421). IEEE.
[5]. Gharajeh, M. S. (2015). The significant concepts of cloud computing : Technology, architecture, applications, and security. CreateSpace Independent Publishing Platform.
[6]. Gharajeh, M. S. (2017). Applications of virtualization technology in grid systems and cloud servers. In P. K. Das and G. C. Deka (Eds.), Design and Use of Virtualization Technology in Cloud Computing (pp. 1-28). Hershey, PA: IGI Global
[7]. Gill, S. S., Chana, I., Singh, M., & Buyya, R. (2018). CHOPPER: An intelligent QoS-aware autonomic resource management approach for cloud computing. Cluster Computing, 21(2), 1203-1241.
[8]. Granville, A., & Rudnick, Z. (Eds.). (2007). Equidistribution in number theory, an introduction (Vol. 237). Springer Science & Business Media.
[9]. Hossain, E., Han, Z., & Poor, H. V. (Eds.). (2012). Smart Grid Communications and Networking. Cambridge University Press.
[10]. Jinno, M., Kozicki, B., Takara, H., Watanabe, A., Sone, Y., Tanaka, T., & Hirano, A. (2010). Distance-adaptive spectrum resource allocation in spectrum- sliced elastic optical path network [topics in optical communications]. IEEE Communications Magazine, 48(8), 138-145.
[11]. Krašovec, B., & Filipčič, A. (2019). Enhancing the Grid with Cloud Computing. Journal of Grid Computing, 17(1), 119-135.
[12]. Kuipers, L., & Niederreiter, H. (2012). Uniform Distribution of Sequences. Courier Corporation.
[13]. Mahmood, A., Ullah, M. N., Razzaq, S., Basit, A., Mustafa, U., Naeem, M., & Javaid, N. (2014). A new scheme for demand side management in future smart grid networks. Procedia Computer Science, 32, 477-484.
[14]. Mansouri, N., & Dastghaibyfard, G. H. (2013). Enhanced dynamic hierarchical replication and weighted scheduling strategy in data grid. Journal of Parallel and Distributed Computing, 73(4), 534-543.
[15]. Mariotti, M., Gervasi, O., Vella, F., Cuzzocrea, A., & Costantini, A. (2018). Strategies and systems towards grids and clouds integration: A DBMS-based solution. Future Generation Computer Systems, 88, 718-729.
[16]. Mishra, M. K., Patel, Y. S., Ghosh, M., & Mund, G. B. (2017). A review and classification of grid computing systems. International Journal of Computational Intelligence Research, 13(3), 369-402.
[17]. Nazir, B., Ishaq, F., Shamshirband, S., & Chronopoulos, A. (2018). The impact of the implementation cost of replication in data grid job scheduling. Mathematical and Computational Applications, 23(2), 1-19.
[18]. Nicholson, C., Cameron, D. G., Doyle, A. T., Millar, A. P., & Stockinger, K. (2008). Dynamic data replication in lcg 2008. Concurrency and Computation: Practice and Experience, 20(11), 1259-1271.
[19]. O'neil, E. J., O'neil, P. E., & Weikum, G. (1993). The LRU-K page replacement algorithm for database disk buffering. ACM Sigmod Record, 22(2), 297-306.
[20]. Prischepa, V. (2004). An efficient web caching algorithm based on LFU-K replacement policy. In Proceedings of the Spring Young Researcher's Colloquium on Database and Information Systems (pp. 1- 5). IEEE.
[21]. Rahman, R. M., Barker, K., & Alhajj, R. (2009). Performance evaluation of different replica placement algorithms. International Journal of Grid and Utility Computing, 1(2), 121-133.
[22]. Ranganathan, K., Iamnitchi, A., & Foster, I. (2002, May). Improving data availability through dynamic model-driven replication in large peer-to-peer communities. In 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID'02) (pp. 376-376). IEEE.
[23]. Sashi, K., & Thanamani, A. S. (2011). Dynamic replication in a data grid using a modified BHR region based algorithm. Future Generation Computer Systems, 27(2), 202-210.
[24]. Tang, M., Lee, B. S., Tang, X., & Yeo, C. K. (2006). The impact of data replication on job scheduling performance in the Data Grid. Future Generation Computer Systems, 22(3), 254-268.
[25]. Wang, L., Jie, W., & Chen, J. (2018). Grid Computing: Infrastructure, Service, and Applications. CRC Press.
[26]. Weng, Y., Negi, R., Faloutsos, C., & Ilić, M. D. (2017). Robust data-driven state estimation for smart grid. IEEE Transactions on Smart Grid, 8(4), 1956-1967.
[27]. Wilkinson, B. (2009). Grid Computing: Techniques and Applications. CRC Press.
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