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Performance Analysis of Enterprise Cloud Computing: A Review


Cloud computing has swiftly established itself as the norm in its field as a result of the advantages described above. In an attempt to reduce the amount of time spent on infrastructure upkeep, an increasing number of businesses are moving their operations to the cloud. As a result, maintaining a cloud environment has proved to be exceedingly difficult. It is necessary to have an efficient cloud monitoring system in order to reduce the workload associated with administration and improve cloud operation. The cloud monitoring service is beneficial since it has the potential to improve performance and make administration easier. The administration of Quality of Service (QoS) parameters for cloud-hosted, virtualized, and physical services and applications is one of the most important responsibilities of cloud monitoring. As a result, cloud management software retains a record of both actions and services, and it also conducts dynamic setups of the cloud in order to increase operational effectiveness. The performance of businesses and businesses as a whole was examined in this article, as was the influence that cloud-ready programs and tools have on that performance, as well as the advantages that may be obtained from adopting such programs and products.




Enterprises performance, Cloud computing, Cloud monitoring, Types of Cloud, Monitoring tools, IaaS, PaaS, SaaS


Author Biography

Hayfaa Subhi Malallah



Riyadh Qashi



Lozan Mohammed Abdulrahman



Marya Ayoub Omer



Abdulmajeed Adil Yazdeen




  1. L. M. Haji, O. M. Ahmad, S. Zeebaree, H. I. Dino, R. R. Zebari, and H. M. Shukur, "Impact of cloud computing and internet of things on the future internet," Technology Reports of Kansai University, vol. 62, pp. 2179-2190, 2020.
  2. Z. S. Ageed, S. R. Zeebaree, M. M. Sadeeq, S. F. Kak, H. S. Yahia, M. R. Mahmood, et al., "Comprehensive survey of big data mining approaches in cloud systems," Qubahan Academic Journal, vol. 1, pp. 29-38, 2021.
  3. G. Boss, P. Malladi, D. Quan, L. Legregni, and H. Hall, "Cloud computing," IBM white paper, vol. 321, pp. 224-231, 2007.
  4. L. M. Abdulrahman, S. Zeebaree, S. F. Kak, M. Sadeeq, A. Adel, B. W. Salim, et al., "A state of art for smart gateways issues and modification," Asian Journal of Research in Computer Science, pp. 1-13, 2021.
  5. Z. S. Ageed, S. R. Zeebaree, M. M. Sadeeq, S. F. Kak, Z. N. Rashid, A. A. Salih, et al., "A survey of data mining implementation in smart city applications," Qubahan Academic Journal, vol. 1, pp. 91-99, 2021.
  6. G. Westerman, D. Bonnet, and A. McAfee, Leading digital: Turning technology into business transformation: Harvard Business Press, 2014.
  7. F. E. F. Samann, S. R. Zeebaree, and S. Askar, "IoT provisioning QoS based on cloud and fog computing," Journal of Applied Science and Technology Trends, vol. 2, pp. 29-40, 2021.
  8. Z. Ageed, M. R. Mahmood, M. Sadeeq, M. B. Abdulrazzaq, and H. Dino, "Cloud computing resources impacts on heavy-load parallel processing approaches," IOSR Journal of Computer Engineering (IOSR-JCE), vol. 22, pp. 30-41, 2020.
  9. V. Goyal, "layers arhitecture of cloud computing," International Journal of Computing & Business Research, vol. 8, 2012.
  10. H. Jean-Baptiste, M. Qiu, K. Gai, and L. Tao, "Model risk management systems-back-end, middleware, front-end and analytics," in 2015 IEEE 2nd International Conference on Cyber Security and Cloud Computing, 2015, pp. 312-316.
  11. H. S. Yahia, S. Zeebaree, M. Sadeeq, N. Salim, S. F. Kak, A. Adel, et al., "Comprehensive survey for cloud computing based nature-inspired algorithms optimization scheduling," Asian Journal of Research in Computer Science, vol. 8, pp. 1-16, 2021.
  12. S. H. Haji, S. Zeebaree, R. H. Saeed, S. Y. Ameen, H. M. Shukur, N. Omar, et al., "Comparison of software defined networking with traditional networking," Asian Journal of Research in Computer Science, pp. 1-18, 2021.
  13. Y. Hu, L. Wu, C. Shi, Y. Wang, and F. Zhu, "Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS," International Journal of Production Research, vol. 58, pp. 748-757, 2020.
  14. R. R. Zebari, S. R. Zeebaree, A. B. Sallow, H. M. Shukur, O. M. Ahmad, and K. Jacksi, "Distributed denial of service attack mitigation using high availability proxy and network load balancing," in 2020 International Conference on Advanced Science and Engineering (ICOASE), 2020, pp. 174-179.
  15. R. J. Hassan, S. Zeebaree, S. Y. Ameen, S. F. Kak, M. Sadeeq, Z. S. Ageed, et al., "State of art survey for iot effects on smart city technology: challenges, opportunities, and solutions," Asian Journal of Research in Computer Science, vol. 22, pp. 32-48, 2021.
  16. B. T. Jijo, S. Zeebaree, R. R. Zebari, M. Sadeeq, A. B. Sallow, S. Mohsin, et al., "A comprehensive survey of 5G mm-wave technology design challenges," Asian Journal of Research in Computer Science, vol. 8, pp. 1-20, 2021.
  17. H. Malallah, S. Zeebaree, R. R. Zebari, M. Sadeeq, Z. S. Ageed, I. M. Ibrahim, et al., "A comprehensive study of kernel (issues and concepts) in different operating systems," Asian Journal of Research in Computer Science, vol. 8, pp. 16-31, 2021.
  18. S. Mukherjee, "Benefits of AWS in modern cloud," arXiv preprint arXiv:1903.03219, 2019.
  19. S. R. Zeebaree, H. M. Shukur, L. M. Haji, R. R. Zebari, K. Jacksi, and S. M. Abas, "Characteristics and analysis of hadoop distributed systems," Technology Reports of Kansai University, vol. 62, pp. 1555-1564, 2020.
  20. B. R. Ibrahim, S. R. Zeebaree, and B. K. Hussan, "Performance Measurement for Distributed Systems using 2TA and 3TA based on OPNET Principles," Science Journal of University of Zakho, vol. 7, pp. 65-69, 2019.
  21. H. I. Dino, S. Zeebaree, O. M. Ahmad, H. M. Shukur, R. R. Zebari, and L. M. Haji, "Impact of load sharing on performance of distributed systems computations," International Journal of Multidisciplinary Research and Publications (IJMRAP), vol. 3, pp. 30-37, 2020.
  22. H. I. Dino, S. Zeebaree, A. A. Salih, R. R. Zebari, Z. S. Ageed, H. M. Shukur, et al., "Impact of Process Execution and Physical Memory-Spaces on OS Performance," Technology Reports of Kansai University, vol. 62, pp. 2391-2401, 2020.
  23. Y. S. Jghef and S. Zeebaree, "State of art survey for significant relations between cloud computing and distributed computing," International Journal of Science and Business, vol. 4, pp. 53-61, 2020.
  24. A. P. Rajan, "Evolution of cloud storage as cloud computing infrastructure service," arXiv preprint arXiv:1308.1303, 2013.
  25. N. R. Omar, R. H. Saeed, J. A. Ahmed, S. B. Muhammad, Z. S. Ageed, and Z. N. Rashid, "Enhancing OS Memory Management Performance: A."
  26. Z. S. Ageed, S. R. Zeebaree, M. A. Sadeeq, R. K. Ibrahim, H. M. Shukur, and A. Alkhayyat, "Comprehensive Study of Moving from Grid and Cloud Computing Through Fog and Edge Computing towards Dew Computing," in 2021 4th International Iraqi Conference on Engineering Technology and Their Applications (IICETA), 2021, pp. 68-74.
  27. T. M. G. Sami, Z. S. Ageed, Z. N. Rashid, and Y. S. Jghef, "Distributed, Cloud, and Fog Computing Motivations on Improving Security and Privacy of Internet of Things," Mathematical Statistician and Engineering Applications, vol. 71, pp. 7630-7660, 2022.
  28. S. A. Mohammed, R. H. Saeed, J. A. Ahmed, S. B. Muhammad, Z. S. Ageed, and Z. N. Rashid, "GPU Concepts and Graph Application Challenges: A."
  29. D. M. Abdulqader and S. R. Zeebaree, "Impact of Distributed-Memory Parallel Processing Approach on Performance Enhancing of Multicomputer-Multicore Systems: A Review," QALAAI ZANIST JOURNAL, vol. 6, pp. 1137-1140, 2021.
  30. Z. S. Hammed, S. Y. Ameen, and S. R. Zeebaree, "Massive MIMO-OFDM performance enhancement on 5G," in 2021 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), 2021, pp. 1-6.
  31. Z. S. Ageed, R. K. Ibrahim, and M. Sadeeq, "Unified ontology implementation of cloud computing for distributed systems," Current Journal of Applied Science and Technology, vol. 39, pp. 82-97, 2020.
  32. K. D. Ahmed and S. R. Zeebaree, "Resource allocation in fog computing: A review," International Journal of Science and Business, vol. 5, pp. 54-63, 2021.
  33. F. Abedi, S. R. Zeebaree, Z. S. Ageed, H. M. Ghanimi, A. Alkhayyat, M. A. Sadeeq, et al., "Severity Based Light-Weight Encryption Model for Secure Medical Information System."
  34. G. A. Qadir and S. R. Zeebaree, "Evaluation of QoS in distributed systems: A review," International Journal of Science and Business, vol. 5, pp. 89-101, 2021.
  35. Z. J. Hamad and S. R. Zeebaree, "Recourses utilization in a distributed system: A review," International Journal of Science and Business, vol. 5, pp. 42-53, 2021.
  36. N. T. Muhammed, S. R. Zeebaree, and Z. N. Rashid, "Distributed Cloud Computing and Mobile Cloud Computing: A Review," QALAAI ZANIST JOURNAL, vol. 7, pp. 1183-1201, 2022.
  37. A. A. Salih, S. Y. Ameen, S. Zeebaree, M. Sadeeq, S. F. Kak, N. Omar, et al., "Deep learning approaches for intrusion detection," Asian Journal of Research in Computer Science, pp. 50-64, 2021.
  38. S. Sharma, K. Chen, and A. Sheth, "Toward practical privacy-preserving analytics for IoT and cloud-based healthcare systems," IEEE Internet Computing, vol. 22, pp. 42-51, 2018.
  39. T. Huang, Z. Zeng, C. Li, and C. S. Leung, Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part II vol. 7664: Springer, 2012.
  40. R. F. Babiceanu and R. Seker, "Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook," Computers in industry, vol. 81, pp. 128-137, 2016.
  41. K. A. Phung, C. Kirbas, L. Dereci, and T. V. Nguyen, "Pervasive Healthcare Internet of Things: A Survey," Information, vol. 13, p. 360, 2022.
  42. M. Elmagzoub, D. Syed, A. Shaikh, N. Islam, A. Alghamdi, and S. Rizwan, "A survey of swarm intelligence based load balancing techniques in cloud computing environment," Electronics, vol. 10, p. 2718, 2021.
  43. H. Jamshaid, F. Zahid, A. Zeb, H. G. Choi, and G. M. Khan, "Diagnostic and treatment strategies for COVID-19," AAPS PharmSciTech, vol. 21, pp. 1-14, 2020.
  44. C. Wu, S. Horiuchi, K. Murase, H. Kikushima, and K. Tayama, "Intent-driven cloud resource design framework to meet cloud performance requirements and its application to a cloud-sensor system," Journal of Cloud Computing, vol. 10, pp. 1-22, 2021.
  45. N. V. Chawla, N. Japkowicz, and A. Kotcz, "Special issue on learning from imbalanced data sets," ACM SIGKDD explorations newsletter, vol. 6, pp. 1-6, 2004.
  46. A. H. M. Aman, W. H. Hassan, S. Sameen, Z. S. Attarbashi, M. Alizadeh, and L. A. Latiff, "IoMT amid COVID-19 pandemic: Application, architecture, technology, and security," Journal of Network and Computer Applications, vol. 174, p. 102886, 2021.
  47. D. G. Stephen and J. A. Dixon, "Strong anticipation: Multifractal cascade dynamics modulate scaling in synchronization behaviors," Chaos, Solitons & Fractals, vol. 44, pp. 160-168, 2011.
  48. D. Mourtzis, "Simulation in the design and operation of manufacturing systems: state of the art and new trends," International Journal of Production Research, vol. 58, pp. 1927-1949, 2020.
  49. M. Banerjee, J. Lee, and K.-K. R. Choo, "A blockchain future for internet of things security: a position paper," Digital Communications and Networks, vol. 4, pp. 149-160, 2018.
  50. G. Ciccarella, R. Giuliano, F. Mazzenga, F. Vatalaro, and A. Vizzarri, "Edge cloud computing in telecommunications: Case studies on performance improvement and TCO saving," in 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), 2019, pp. 113-120.
  51. O. Pandithurai, S. Aishwarya, B. Aparna, and K. Kavitha, "Agro-tech: A digital model for monitoring soil and crops using internet of things (IOT)," in 2017 Third International Conference on Science Technology Engineering & Management (ICONSTEM), 2017, pp. 342-346.
  52. M. A. Sharkh, Y. Xu, and E. Leyder, "CloudMach: cloud computing application performance improvement through machine learning," in 2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2020, pp. 1-6.
  53. W.-L. Tsai, "Constructing assessment indicators for enterprises employing cloud IaaS," Asia Pacific Management Review, vol. 26, pp. 23-29, 2021.
  54. B. Vellingiri, K. Jayaramayya, M. Iyer, A. Narayanasamy, V. Govindasamy, B. Giridharan, et al., "COVID-19: A promising cure for the global panic," Science of the total environment, vol. 725, p. 138277, 2020.
  55. A. L. Richards, "The Political Climate of Saxony during the Conversion of Karl G. Maeser: With Special Reference to the Franklin D. Richards Letter to Brigham Young, November 1855," BYU Studies Quarterly, vol. 56, pp. 93-114, 2017.
  56. M. Liu, L. Zhao, G. Gong, L. Zhang, L. Shi, J. Dai, et al., "Invited review: Remediation strategies for mycotoxin control in feed," Journal of Animal Science and Biotechnology, vol. 13, pp. 1-16, 2022.
  57. N. Kratzke and R. Siegfried, "Towards cloud-native simulations–lessons learned from the front-line of cloud computing," The Journal of Defense Modeling and Simulation, vol. 18, pp. 39-58, 2021.


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