The cloud monitoring system allows administrators to know the historical performance of each component of the platform at any time and control the usage of various resources. Monitoring can remind operation and maintenance managers in a timely manner when a fault occurs, quickly find problems, and better solve errors. The purpose of this paper is to study the application of consistent hash algorithm in distributed monitoring system. The architecture and design concept of distributed monitoring are analyzed, and a set of good distributed performance monitoring system of cloud platform is developed according to the characteristics of the rapid development of cloud platform. The whole system can be divided into data acquisition unit, real-time alarm unit, historical data storage unit and global control unit. The specific implementation process of the main functional units is given. Finally, the system is tested. The experimental results show that the consistent hash algorithm has a good balance effect in the distributed monitoring system.

Adityan Kumare. Consistent Hash Algorithm in Distributed Monitoring System. Distributed Processing System (2020), Vol. 1, Issue 2: 28-36. https://doi.org/10.38007/DPS.2020.010204.

[1] Katsaros D. Distributed ledger technology: the science of the blockchain (2nd ed.). Computing reviews, 2018, 59(11):596-597.

[2] Mendelson G, Vargaftik S, Barabash K, et al. AnchorHash: A Scalable Consistent Hash. IEEE/ACM Transactions on Networking, 2020, PP(99):1-12.

[3] Thaiyalnayaki S, Sasikala J, Ponraj R. Indexing Near-Duplicate Images In Web Search Using Minhash Algorithm. Materials Today: Proceedings, 2018, 5(1):1943-1949. https://doi.org/10.1016/j.matpr.2017.11.297

[4] Jose C. Document Security System Using Improved Hash Algorithm on Pre-processing Operation. Journal of Advanced Research in Dynamical and Control Systems, 2019, 11(11-SPECIAL ISSUE):972-978.

[5] Kumar M S, Pvrd P, Rao. Advanced SHA-256 Algorithm for Device to Device Communication. International Journal of Advanced Science and Technology, 2020, 29(7):1189-1191.

[6] Santra R, Obermeyer M. A first encounter with the Hartree-Fock self-consistent-field method. American Journal of Physics, 2020, 89(4):426-436. https://doi.org/10.1119/10.0002644

[7] Mettler M, Mueller-Gritschneder D, Schlichtmann U. A Distributed Hardware Monitoring System for Runtime Verification on Multi-Tile MPSoCs. ACM Transactions on Architecture and Code Optimization, 2020, 18(1):1-25. https://doi.org/10.1145/3430699

[8] Kazemi Z, Safavi A A, Pouresmaeeli S, et al. A practical framework for implementing multivariate monitoring techniques into distributed control system. Control Engineering Practice, 2019, 82(JAN.):118-129.

[9] Ciminello M. Distributed Fiber Optic for Structural Health Monitoring System Based on Auto-Correlation of the First-Order Derivative of Strain. IEEE sensors journal, 2019, 19(14):5818-5824. https://doi.org/10.1109/JSEN.2019.2903911

[10] Salih H S, Egorov S Y. Development Of A Monitoring System For Scheduled Works At Distributed Facilities. Vestnik Tambovskogo gosudarstvennogo tehnicheskogo universiteta, 2020, 26(1):056-063.

[11] Mohammed A, Hu B, Hu Z, et al. Distributed Thermal Monitoring of Wind Turbine Power Electronic Modules Using FBG Sensing Technology. IEEE Sensors Journal, 2020, PP(99):1-1.

[12] Ciminello M. Reliability of structural health monitoring system based on distributed fiber optic and autocorrelation of the first order derivative of strain. IEEE Sensors Journal, 2019, PP(99):1-1.

[13] Monsberger C M, Lienhart W. Design, Testing, and Realization of a Distributed Fiber Optic Monitoring System to Assess Bending Characteristics Along Grouted Anchors. Journal of Lightwave Technology, 2019, PP(99):1-1. https://doi.org/10.1109/JLT.2019.2913907

[14] Masouros D, Xydis S, Soudris D J. Rusty: Runtime interference-aware predictive monitoring for modern multi-tenant systems. IEEE Transactions on Parallel and Distributed Systems, 2020, PP(99):1-1. https://doi.org/10.1109/TPDS.2020.3013948

[15] Alfredo, Güemes, Antonio, et al. Simulation Tools for a Fiber-Optic Based Structural Health Monitoring System. Transactions of Nanjing University of Aeronautics and Astronautics, 2018, v.35(02):5-11.

[16] Charapko A, Ailijiang A, Demirbas M, et al. Retroscope: Retrospective Monitoring of Distributed Systems. IEEE Transactions on Parallel and Distributed Systems, 2019, 30(11):2582-2594. https://doi.org/10.1109/TPDS.2019.2911944

[17] Abdurakhmanov A S, Fedorova V A. Intellectual mobile system for monitoring environment in the premises. Radio Industry (Russia), 2018, 28(4):41-46.

[18] Sancho J I, Almandoz I, Barandiaran M, et al. Scalable Wireless Wearing Monitoring System for Harsh Industrial Environment. IEEE Transactions on Industrial Electronics, 2020, PP(99):1-1. https://doi.org/10.1109/TIE.2020.3053892