Generalized Statistical Indicators For Cloud Computing Fault Tolerance


  • Subramanyam M Vadlamaani Research Scholar, Department of CSE, Shri Venkateshwara University, Gajraula, UP
  • P K Bharti Vice-chancellor, Shri Venkateshwara University, Gajraula, UP
  • M. Rudra Kumar Professor, Department of CSE, GPCET, Kurnool


Cloud Computing Indicator Patterns, Computer Programming, Fault Tolerance, Heikin Ashi Cloud Indicators, KPI indicators for Cloud Computing


Contemporary information and transaction processing systems mainly rely on cloud computing for their infrastructure. A shared pool of reconfigurable computing resources (such as networks, servers, storage, applications, and services) may be quickly deployed and released with no administration labour or service disruption thanks to cloud computing, which offers universal, practical, on-demand network connectivity. Due to the increasing need for more fault-tolerant and high-availability cloud computing servers, server managers must increasingly concentrate on key performance indicators for these systems. Server administrators are very concerned about the performance of high-availability and fault-tolerance systems since it is usual for unanticipated and unplanned outages to occur often. Based on the sustainability and pattern indicators discussed in earlier research, this study suggests a directional analytic pattern indicator for cloud computing servers. The Heikin Ashi charting pattern, which is akin to a Japanese candlestick pattern, is used by the Generalized Statistical Indicators for Fault Tolerance (GSI-FT) to identify the patterns in service consumption across various time periods. The preceding research's ISO/IEC 30134-1 and 30134-2-Datacenters-Main performance indicators, which examined the internet bandwidth frequency for high availability and fault tolerance movements, were used as the basis for the experiments. Results of testing have demonstrated that GSI-FT may function as a directional indicator to identify the pattern frequencies of the performance indicators and offer details on fault tolerance by giving observation frequency, performance trend, and awareness level for this pattern. The red candlesticks show the model's progress toward fault tolerance, while the green symbolises the model's high availability. A charting model that has evolved over time over the pattern shows the model's capacity to depict server-level signals that are plausible using our methodology.


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Heikin ashi trend indicators




How to Cite

S. M. Vadlamaani, P. K. . Bharti, and M. R. . Kumar, “Generalized Statistical Indicators For Cloud Computing Fault Tolerance”, Int J Intell Syst Appl Eng, vol. 10, no. 1s, pp. 269 –, Oct. 2022.