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CLOUD computing risk management for server‐farm repair rates, consumer load cycle, server‐farm repair crew count, and additional servers
Author(s) -
Sahinoglu Mehmet
Publication year - 2018
Publication title -
wiley interdisciplinary reviews: computational statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.693
H-Index - 38
eISSN - 1939-0068
pISSN - 1939-5108
DOI - 10.1002/wics.1424
Subject(s) - cloud computing , computer science , server , reliability engineering , operating system , engineering
A discrete event simulator, CLOURAM: CLOUD Risk Assessor and Manager, algorithmically estimates the risk indices in modern‐day CLOUD computing scenarios with tangible risk management targets that are favorable to the intractably tedious, theoretical Markov solutions or hand calculations overly limited in scope. The goal is to improve the operational quality of CLOUD by optimizing the number of servers for capacity addition and optimizing the final repair crew count. We too optimize the server unit repair rates, and the consumer load cycle by curbing the demand using Linear Programming (LP) ‐ based optimization with the proper objective functions and constraints. Small and large CLOUD systems are simulated with cost and benefit comparisons. The 2‐state (UP and DN) or 3‐State (UP, DN, and DER) units statistically fail and recover with Negative Exponential or Weibull densities. WIREs Comput Stat 2018, 10:e1424. doi: 10.1002/wics.1424 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control Algorithms and Computational Methods > Networks and Security Statistical Models > Simulation Models Algorithms and Computational Methods > Linear Programming