Abstract
Cloud computing refers to applications and services which run on a distributed network, they also represent the ability of information technology as a service to network users. Data replication is an important way of managing mass data in a distributed manner; data replication is seen as one of the important issues in distributed systems which are usually undertaken for increasing the efficiency, availability, and security of information. Data replication’s core idea is developing methods for putting repetitions in different places, so that there are multiple iterations of the specific file in different sites. A key issue in data managing is the manner that system deals with duplicates. This included steps such as: which files are replicated, when is the data replication done and where in the system are they to be placed. In this study, the proposed method has been implemented using the MATLAB environment and the results have showed that the performing time of the proposed method is much lower as compared to previous methods and it had improved performance time compared to the previous methods.
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References
Jeon M, Lim K, Ahn H, Le B (2010) Dynamic data replication scheme in the cloud computing environment. In: IEEE Second Symposium on network cloud Computing and Applications, vol 3. pp 40–47
Teng M, Junzhou L (2005) In: International conference on advanced information and applications
Mansouri N, Dastghaibyfard G (2012) A dynamic replica management strategy in data grid. J Netw Comput Appl 35:1297–1303
Zaha W, Xu X, Wang Z (2008) A weight-based dynamic replica replacement strategy in data grids. IEEE Asia-pacific service computing conference
Park S, Kim J, Ko Y, Yoon W (2004) Dynamic data replication strategy based on internet hierarchy. Springer-Verlag, Berlin, pp 838–846
Mansouri N, Dastghaibyfard G, Mansouri E (2013) J Netw Comput Appl 36(2):711–722
Rahmani A, Fadaie Z, Chronopoulos AT (2015) Data placement using dewey encoding in a hierarchical data grid. J Netw Comput Appl 88–98
Sakr S, Liu A, Batista D, Alomari M ( 2010) A survey of large scale data management approaches in cloud environments. IEEE communications surveys & tutorials, accepted for publication, Manuscript received 28 Jun 2010; Revised 2 December
Sato H (2008) In: International conference on grid computing, vol 1, pp 250–257
Abdurrab A, Xie T (2010) In: International conference in clustering computing and the grid, vol 10, pp 215–223
Taheri J, Lee Y, Zomaya A, Siegel H (2013) A bee colony based optimization approach for simultaneous job scheduling and data replication in grid environments. Comput Oper Res 1564–1578
Sashi K, Thanamani A (2011) Dynamic replication in a data grid using a modified BHR region based algorithm. Future Gener Comput Syst 202–210
Xu X, Liu Z, Wang Z, Sheng Q, Yu J, Wang X (2017) S-ABC: a paradim of service domain-oriented artificial bee colony algorithm for service selection and composition. Future Gener Comput Syst 68:304–319
Mansouri N, Dastghaibyfard G (2013) Enhanced dynamic hierachical replication and weighted scheduling strategy in data grid. J Parallel Distrib Comput 534–543
Gao K, Suganthan P, Pari Q, Tasgetirn M, Sadollah A (2016) Knowl-Based Syst 109:1–16
Horri A, Sepahvand R, Dastghaibyfard G (2008) IJCSNS Int J Comput Sci Netw Secur 8:8
Camman M, Stockinger K (2002) In: International symposium on cluster computing and the grid, pp 340–345
Sashi K, Santhanam T (2013) ARPN J Eng Appl Sci 8(2)
Abawajy J, Member S (2014) IEEE Trans comput 63:2975–2987
Grossman R, Gu Y, Mambretti J, Sabala M, Szalay A, White K (2010) An overview of the open science data cloud, HPDC’10, Chicago, Illinois, USA
Kingsy R, Manimegalai R (2014) J Parallel Distrib Comput 74(2):2099–2108
Tanenbaum AS, van Steen M (2006) Distributed systems: principles and paradigms. Vrije Universitet Amesterdam, The Netherlands
Mansouri N (2016) Adaptive data replication strategy in cloud computing for performance improvement. Front Comput Sci
Kumar KA, Quamar A, Deshpande A, Khuller S (2014) SWORD: workload aware data placement and replica selection for cloud data management systems. VLDB J 23(6):845–870
Boru D, Kliazovich D, Granelli F, Bouvry P, Zomaya AY (2015) Energy efficient data replication in cloud computing datacenters. J Cluster Comput 18(1):385–402
Janpet J, Wen YF (2013) Reliable and available data replication planning for cloud storage. In: Proceedings of the IEEE 27th international conference on advanced information networking and applications (AINA), pp 772–779
Leesakul W, Townend P, Xu J (2014) Dynamic data reduplication in cloud storage. In: Proceedings of the IEEE 8th international symposium on service oriented system engineering (SOSE), pp 320–325
Huang K, Li D, Sun Y (2014) CRMS: a centralized replication management scheme for cloud storage system. In: Proceedings of the IEEE/CIC international conference on communications in China (ICCC), pp 344–348
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khalili azimi, S. (2019). A Bee Colony (Beehive) Based Approach for Data Replication in Cloud Environments. In: Montaser Kouhsari, S. (eds) Fundamental Research in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 480. Springer, Singapore. https://doi.org/10.1007/978-981-10-8672-4_80
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DOI: https://doi.org/10.1007/978-981-10-8672-4_80
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