How to cite this paper
Alrashdan, M., Wahed, M., Aljarrah, E., Tubishat, M., Alzaqebah, M & Aljawarneh, N. (2024). The impact of data recovery criteria, data backup schedule and data backup prosses on the efficiency of data recovery management in data centers.International Journal of Data and Network Science, 8(4), 2539-2546.
Refrences
Challagidad, P. S., Dalawai, A. S., & Birje, M. N. (2017). Efficient and reliable data recovery technique in cloud compu-ting. Internet of Things and Cloud Computing, 5(1), 13-18.
Cheng, H., Shi, Y., Wu, L., Guo, Y., & Xiong, N. (2021). An intelligent scheme for big data recovery in Internet of Things based on multi-attribute assistance and extremely randomized trees. Information Sciences, 557, 66-83.
Couto, R. D. S., Secci, S., Campista, M. E. M., & Costa, L. H. M. K. (2016). Reliability and survivability analysis of data center network topologies. Journal of Network and Systems Management, 24, 346-392.
Devarajan, H., Kougkas, A., Logan, L., & Sun, X. H. (2020, May). Hcompress: Hierarchical data compression for multi-tiered storage environments. In 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 557-566). IEEE.
Gao, J., Wang, H., & Shen, H. (2020). Task failure prediction in cloud data centers using deep learning. IEEE transactions on services computing, 15(3), 1411-1422.
Garnett, B. S. (2008). Better safe than sorry: criteria for choosing a data backup service. Orthodontic Products, 15(3), 106-109.
Gokulakrishnan, S., & Gnanasekar, J. M. (2020a). Data integrity and recovery management under peer to peer convoluted fault recognition cloud systems. Journal of Computational and Theoretical Nanoscience, 17(5), 2147-2150.
Gokulakrishnan, S., & Gnanasekar, J. M. (2020b). Data integrity and recovery management in cloud systems. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC) (pp. 645-648). IEEE.
Gong, C., Liu, J., Zhang, Q., Chen, H., & Gong, Z. (2010, September). The characteristics of cloud computing. In 2010 39th International Conference on Parallel Processing Workshops (pp. 275-279). IEEE.
Johnson, E. (2017). Lost in the cloud: Cloud storage, privacy, and suggestions for protecting users' data. Stanford Law Re-view, 69, 867.
Kaczmarski, M., Jiang, T., & Pease, D. A. (2003). Beyond backup toward storage management. IBM Systems Jour-nal, 42(2), 322-337.
Li, Z. (2014). GreenDM: A versatile tiering hybrid drive for the trade-off evaluation of performance, energy, and endur-ance (Doctoral dissertation, State University of New York at Stony Brook).
Liu, S., & Kuhn, R. (2010). Data loss prevention. IT professional, 12(2), 10-13.
Ma, F. Q., & Fan, R. N. (2021). Markov Processes in Data Center Networks. IEEE Access, 9, 42216-42225.
Meza, J., Xu, T., Veeraraghavan, K., & Mutlu, O. (2018, October). A large scale study of data center network reliability. In Proceedings of the Internet Measurement Conference 2018 (pp. 393-407).
Mulyono, H., Hadian, A., Purba, N., & Pramono, R. (2020). Effect of service quality toward student satisfaction and loyal-ty in higher education. The Journal of Asian Finance, Economics and Business (JAFEB), 7(10), 929-938.
Nguyen, T. A., Min, D., Choi, E., & Tran, T. D. (2019). Reliability and availability evaluation for cloud data center net-works using hierarchical models. IEEE Access, 7, 9273-9313.
Qin, Y., Hoffmann, B., & Lilja, D. J. (2018, November). Hyperprotect: Enhancing the performance of a dynamic backup system using intelligent scheduling. In 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC) (pp. 1-8). IEEE.
van de Ven, P. M., Zhang, B., & Schörgendorfer, A. (2014, April). Distributed backup scheduling: Modeling and optimiza-tion. In IEEE INFOCOM 2014-IEEE Conference on Computer Communications (pp. 1644-1652). IEEE.
Voorsluys, W., Broberg, J., & Buyya, R. (2011). Introduction to cloud computing. Cloud computing: Principles and para-digms, 1-41.
Xia, R., Machida, F., & Trivedi, K. (2014, June). A Markov decision process approach for optimal data backup scheduling. In 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (pp. 660-665). IEEE.
Zhou, G., & Maas, M. (2021). Learning on distributed traces for data center storage systems. Proceedings of Machine Learning and Systems, 3, 350-364.
Cheng, H., Shi, Y., Wu, L., Guo, Y., & Xiong, N. (2021). An intelligent scheme for big data recovery in Internet of Things based on multi-attribute assistance and extremely randomized trees. Information Sciences, 557, 66-83.
Couto, R. D. S., Secci, S., Campista, M. E. M., & Costa, L. H. M. K. (2016). Reliability and survivability analysis of data center network topologies. Journal of Network and Systems Management, 24, 346-392.
Devarajan, H., Kougkas, A., Logan, L., & Sun, X. H. (2020, May). Hcompress: Hierarchical data compression for multi-tiered storage environments. In 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 557-566). IEEE.
Gao, J., Wang, H., & Shen, H. (2020). Task failure prediction in cloud data centers using deep learning. IEEE transactions on services computing, 15(3), 1411-1422.
Garnett, B. S. (2008). Better safe than sorry: criteria for choosing a data backup service. Orthodontic Products, 15(3), 106-109.
Gokulakrishnan, S., & Gnanasekar, J. M. (2020a). Data integrity and recovery management under peer to peer convoluted fault recognition cloud systems. Journal of Computational and Theoretical Nanoscience, 17(5), 2147-2150.
Gokulakrishnan, S., & Gnanasekar, J. M. (2020b). Data integrity and recovery management in cloud systems. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC) (pp. 645-648). IEEE.
Gong, C., Liu, J., Zhang, Q., Chen, H., & Gong, Z. (2010, September). The characteristics of cloud computing. In 2010 39th International Conference on Parallel Processing Workshops (pp. 275-279). IEEE.
Johnson, E. (2017). Lost in the cloud: Cloud storage, privacy, and suggestions for protecting users' data. Stanford Law Re-view, 69, 867.
Kaczmarski, M., Jiang, T., & Pease, D. A. (2003). Beyond backup toward storage management. IBM Systems Jour-nal, 42(2), 322-337.
Li, Z. (2014). GreenDM: A versatile tiering hybrid drive for the trade-off evaluation of performance, energy, and endur-ance (Doctoral dissertation, State University of New York at Stony Brook).
Liu, S., & Kuhn, R. (2010). Data loss prevention. IT professional, 12(2), 10-13.
Ma, F. Q., & Fan, R. N. (2021). Markov Processes in Data Center Networks. IEEE Access, 9, 42216-42225.
Meza, J., Xu, T., Veeraraghavan, K., & Mutlu, O. (2018, October). A large scale study of data center network reliability. In Proceedings of the Internet Measurement Conference 2018 (pp. 393-407).
Mulyono, H., Hadian, A., Purba, N., & Pramono, R. (2020). Effect of service quality toward student satisfaction and loyal-ty in higher education. The Journal of Asian Finance, Economics and Business (JAFEB), 7(10), 929-938.
Nguyen, T. A., Min, D., Choi, E., & Tran, T. D. (2019). Reliability and availability evaluation for cloud data center net-works using hierarchical models. IEEE Access, 7, 9273-9313.
Qin, Y., Hoffmann, B., & Lilja, D. J. (2018, November). Hyperprotect: Enhancing the performance of a dynamic backup system using intelligent scheduling. In 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC) (pp. 1-8). IEEE.
van de Ven, P. M., Zhang, B., & Schörgendorfer, A. (2014, April). Distributed backup scheduling: Modeling and optimiza-tion. In IEEE INFOCOM 2014-IEEE Conference on Computer Communications (pp. 1644-1652). IEEE.
Voorsluys, W., Broberg, J., & Buyya, R. (2011). Introduction to cloud computing. Cloud computing: Principles and para-digms, 1-41.
Xia, R., Machida, F., & Trivedi, K. (2014, June). A Markov decision process approach for optimal data backup scheduling. In 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (pp. 660-665). IEEE.
Zhou, G., & Maas, M. (2021). Learning on distributed traces for data center storage systems. Proceedings of Machine Learning and Systems, 3, 350-364.