Optimizing LDDR Costs with Dual-Purpose Hardware and Elastic File Systems: A New Paradigm for NFS-Like High Availability and Synchronization
Main Article Content
Abstract
The increased prices of the Local Disk Disaster Recovery (LDDR) infrastructures have become the primary challenge faced by organizations aiming to ensure high availability and synchronization of the distributed storage systems. Though highly robust, traditional Network File System (NFS) based architectures frequently fail to balance redundancy, latency, and cost efficiency. This study proposes a new paradigm of combining dual-purpose hardware, namely, those devices that can serve both computing and recovery purposes, with the elastic file system to attain a high availability and synchronization cost-optimal NFS-like model. The suggested strategy takes advantage of the dynamic resource allocation and adaptive replication policies to minimize idle hardware processes, minimize the total cost of ownership, and maintain a constant throughput in case of failover. An agent prototype was created and tested on simulated enterprise workloads, and the performance and cost metrics were compared with traditional LDDR solutions. In the experiments, up to 38 percent of the reduced costs of recovery infrastructure, 22 percent shorter synchronization latencies, and a greater resource utilization efficiency are achieved without losing the integrity and fault tolerance of the data. This work provides a scalable model of hybridizing the elastic storage concepts and combining them with hybridized hardware to prototype sustainable and high-performance disaster recovery in a large-scale setting. The proposed paradigm not only criticizes available LDDR cost models but also opens the possibilities of NFS-like systems to newer, more adaptive, f-optimizing architectures.
Article Details
Section
How to Cite
References
1. Altameem, A., Al-Ma’aitah, M., Kovtun, V., & Altameem, T. (2023). A computationally efficient method for assessing the impact of an active viral cyber threat on a high-availability cluster. Egyptian Informatics Journal, 24(1), 61–69. https://doi.org/10.1016/j.eij.2022.11.002
2. Asha, K., Ghivari, S., Pujar, M., & Sait, S. (2023). NiTi rotary system in endodontics – An overview. IP Indian Journal of Conservative and Endodontics, 8(3), 128–133. https://doi.org/10.18231/j.ijce.2023.025
3. Cangir, O. F., Cankur, O., & Ozsoy, A. (2021). A taxonomy for blockchain-based distributed storage technologies. Information Processing and Management, 58(5). https://doi.org/10.1016/j.ipm.2021.102627
4. CeCe, R., Jining, L., Islam, M., Korvink, J. G., & Sharma, B. (2024, January 1). An Overview of the Electrospinning of Polymeric Nanofibers for Biomedical Applications Related to Drug Delivery. Advanced Engineering Materials. John Wiley and Sons Inc. https://doi.org/10.1002/adem.202301297
5. Chavali, R. V., Dey, A., & Das, B. (2022). A Hysteresis Current Controller PWM Scheme Applied to Three-Level NPC Inverter for Distributed Generation Interface. IEEE Transactions on Power Electronics, 37(2), 1486–1495. https://doi.org/10.1109/TPEL.2021.3107618
6. Drogomiretskiy, O., Yearian, C., & Clifford, C. (2022). First metatarsophalangeal joint arthrodesis with dual plating: A clinical retrospective review. Foot & Ankle Surgery: Techniques, Reports & Cases, 2(4), 100236. https://doi.org/10.1016/j.fastrc.2022.100236
7. Funde, S., & Swain, G. (2022). Big Data Privacy and Security Using Abundant Data Recovery Techniques and Data Obliviousness Methodologies. IEEE Access, 10, 105458–105484. https://doi.org/10.1109/ACCESS.2022.3211304
8. Gummlich, B. P. M., Raddatz, D., & Gollisch, K. S. C. (2024). Intensive lifestyle intervention positively affects nonalcoholic fatty liver fibrosis score (NFS) and key metabolic parameters: A retrospective study. Human Nutrition and Metabolism, 35. https://doi.org/10.1016/j.hnm.2024.200247
9. Han, R., Hu, Q., Zhang, H., Ge, Y., Quan, X., & Wu, Z. (2024). Robust allocation of distributed energy storage systems considering locational frequency security. International Journal of Electrical Power and Energy Systems, 157. https://doi.org/10.1016/j.ijepes.2024.109903
10. Pasumarthi, Arunkumar. (2022). International Journal of Research and Applied Innovations (IJRAI) Architecting Resilient SAP Hana Systems: A Framework for Implementation, Performance Optimization, and Lifecycle Maintenance. International Journal of Research and Applied Innovations. 05. 10.15662/IJRAI.2022.0506007.
11. Kumar, R., Sachan, A., & Ghoshal, B. (2022). SLePaaS: An Embedded Platform-as-a-Service Facilitating Research on Thermal Management of Embedded Platforms. IEEE Access, 10, 90827–90846. https://doi.org/10.1109/ACCESS.2022.3201501
12. Li, J., Xiao, Y., & Lu, S. (2024). Optimal configuration of multi-microgrid electric hydrogen hybrid energy storage capacity based on distributed robustness. Journal of Energy Storage, 76. https://doi.org/10.1016/j.est.2023.109762
13. Liao, G., & Abadi, D. J. (2023). FileScale: Fast and Elastic Metadata Management for Distributed File Systems. In SoCC 2023 - Proceedings of the 2023 ACM Symposium on Cloud Computing (pp. 459–474). Association for Computing Machinery, Inc. https://doi.org/10.1145/3620678.3624784
14. Pasumarthi, Arunkumar & Joyce, Sheetal. (2023). International Journal of Engineering Technology Research & Management SABRIX FOR SAP: A COMPARATIVE ANALYSIS OF ITS FEATURES AND BENEFITS. 7. 10.5281/zenodo.15880437.
15. Thambireddy, S., Journal, I. J. E. T. R. M., & Anbalagan, B. (2023). EVALUATING THE FINANCIAL VALUE OF RISE WITH SAP:
16. TCO OPTIMIZATION AND ROI REALIZATION IN CLOUD ERP MIGRATION. International Journal of Engineering Technology Research & Management, 07(12).
17. Muhammad, L. J., Islam, M. M., Usman, S. S., & Ayon, S. I. (2020). Predictive Data Mining Models for Novel Coronavirus (COVID-19) Infected Patients’ Recovery. SN Computer Science, 1(4). https://doi.org/10.1007/s42979-020-00216-w
18. Nair, S. S., & Santha, T. (2023). High availability of kernel-based virtual machines using nested virtualization. Measurement: Sensors, 26. https://doi.org/10.1016/j.measen.2023.100712
19. Nikam, V., & Kalkhambkar, V. (2021). A review of microgrid control strategies with distributed energy resources, energy storage systems, and electric vehicles. International Transactions on Electrical Energy Systems, 31(1). https://doi.org/10.1002/2050-7038.12607
20. Olaifa, J. O., & Arifler, D. (2023). Dual Connectivity in Heterogeneous Cellular Networks: Analysis of Optimal Splitting of Elastic File Transfers Using Flow-Level Performance Models. IEEE Access, 11, 140582–140595. https://doi.org/10.1109/ACCESS.2023.3342073
21. Parekh, V., Brkic, A., McMinn, J., Williams, D., & Van Diemen, J. (2024). Non-fatal strangulation versus general assault in a clinical forensic medicine cohort: Characteristics of patient, perpetrator, and presentation. Journal of Forensic and Legal Medicine, 102. https://doi.org/10.1016/j.jflm.2024.102651
22. Peniak, P., Bubeníková, E., & Kanáliková, A. (2023). Validation of High-Availability Model for Edge Devices and IIoT. Sensors, 23(10). https://doi.org/10.3390/s23104871
23. Petrakov, Y., & Romanov, Y. (2023). Ensuring the accuracy of contour milling on CNC machines. Mechanics and Advanced Technologies, 7(1 97), 51–60. https://doi.org/10.20535/2521-1943.2023.7.1.276162
24. Rahardja, U., Hidayanto, A. N., Lutfiani, N., Febiani, D. A., & Aini, Q. (2021). Immutability of Distributed Hash Model on Blockchain Node Storage. Scientific Journal of Informatics, 8(1), 137–143. https://doi.org/10.15294/sji.v8i1.29444
25. Sankar,, T., Venkata Ramana Reddy, B., & Balamuralikrishnan, A. (2023). AI-Optimized Hyperscale Data Centers: Meeting the Rising Demands of Generative AI Workloads. In International Journal of Trend in Scientific Research and Development (Vol. 7, Number 1, pp. 1504–1514). IJTSRD. https://doi.org/10.5281/zenodo.15762325
26. Šimon, M., Huraj, L., & Búčik, N. (2023). A Comparative Analysis of High Availability for Linux Container Infrastructures. Future Internet, 15(8). https://doi.org/10.3390/fi15080253
27. Su, J., Li, K., Xing, C., Li, Y., & Yu, J. (2024). A simplified consensus-based distributed secondary control for battery energy storage systems in DC microgrids. International Journal of Electrical Power and Energy Systems, 155. https://doi.org/10.1016/j.ijepes.2023.109627
28. Williams, L., & Wang, Y. (2024). A distributed renewable power system with hydrogen generation and storage for an island. Applied Energy, 358. https://doi.org/10.1016/j.apenergy.2023.122500
29. Xu, R., & Li, C. (2022). A modular agricultural robotic system (MARS) for precision farming: Concept and implementation. Journal of Field Robotics, 39(4), 387–409. https://doi.org/10.1002/rob.22056
30. Yu, L., Zhang, S., Wu, N., & Yu, C. (2022). FPGA-Based Hardware-in-the-Loop Simulation of User Selection Algorithms for Cooperative Transmission Technology over LOS Channel on Geosynchronous Satellites. IEEE Access, 10, 6071–6083. https://doi.org/10.1109/ACCESS.2022.3141098
31. Zhang, S., Li, W., Ma, X., Fan, X., & Zhu, M. (2024). Solvent-free carbon sphere nanofluids towards intelligent lubrication regulation. Friction, 12(1), 95–109. https://doi.org/10.1007/s40544-023-0737-7