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Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency

Manoj Bhoyar

Subject area: Science,Engineering and Technology  ·  Area of research: Cloud Computing

Abstract

Cloud computing is another rapidly advancing technology area that has expanded the possibilities for managing and growing infrastructure for contemporary organizations. Growing business requirements for reliable, elastic, and real-time solutions are responded to by edge computing, serverless solutions, and self-managed resources. Edge computing reduces data processing centralization by performing a part of the calculation near the data source and helps improve real-time decisions in the IoT setting. Serverless solutions allow a developer to build app solutions without worrying about the details of underlying infrastructure frameworks, and services can scale as needed while being cost-effective. On the other hand, autonomous resource management, enabled using AI and machine learning coordinator, greatly enhances resource management and the overall organizational self-organizing, self-optimization, and healing processes, thus strengthening the organization?s organizational Roi and scalability. This paper aims to discuss the combined approach of these paradigms, looking at their opportunities, constraints, and effects on future advancements in cloud computing. SAP products make new approaches to upgrade the scaleability and cost-effectiveness by implementing these superior technology-programmed applications for businesses to increase innovation in an increased data-oriented business environment.

Keywords

Serverless Architectures, Autonomous Resource Management, Cloud Scalability, Real-time Data Processing

References

[1] Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R. H., Konwinski, A., ... & Patterson, D. A. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58. This reference can support the introduction discussing the evolution of cloud computing and the need for innovative paradigms.

[2] Marinos, A., & Briscoe, G. (2009). Community cloud computing. In 2010 1st International Conference on Cloud Computing (pp. 1-8). IEEE. This paper can provide insights into the benefits of cloud computing, relevant to the entire discussion.

[3] Shi, W., Wang, H., Yang, H., & Li, Y. (2016). Edge computing: A new frontier for computing. Computer Science & Information Systems, 13(1), 1-29. This study is pertinent for the Edge Computing section, illustrating its architecture and advantages.

[4] Zhang, K., Wang, Y., Zhang, X., & Wang, Y. (2018). Edge computing for the Internet of Things: A case study. IEEE Communications Magazine, 56(3), 14-20. This article can serve as a case study for edge computing applications and benefits in various industries.

[5] Roberts, M. (2018). Serverless Architectures on AWS. O'Reilly Media, Inc. This reference discusses serverless computing models and can support the Serverless Architectures section.

[6] Zhang, W., & Liu, H. (2018). Serverless computing: A new computing model for cloud-native applications. ACM Computing Surveys (CSUR), 51(6), 1-34. This paper offers insights into serverless computing frameworks and their advantages.

[7] Kuo, T. C., & Kuo, R. H. (2019). Autonomous resource management in cloud computing. IEEE Access, 7, 116153-116166. This paper discusses various AI and machine learning techniques for resource management, relevant for the Autonomous Resource Management section.

[8] Soni, P., & Kaur, S. (2020). AI-driven autonomous resource management in cloud environments: A review. Journal of Cloud Computing: Advances, Systems and Applications, 9(1), 1-19. This review can provide comprehensive insights into AI techniques in resource management.

[9] Zhou, M., & Wang, J. (2017). Performance evaluation of cloud computing based on a resource management strategy. Future Generation Computer Systems, 76, 178-187. This reference supports the discussion on performance benchmarking of traditional versus combined approaches in the Enhancing Scalability and Efficiency section.

[10] Cloud Computing vs. Edge Computing. (2022, April 18). telecomHall Forum.

[11] Zhang, L., Chen, X., & Chen, C. (2018). A survey of resource management for cloud computing and edge computing: Opportunities and challenges. IEEE Internet of Things Journal, 6(1), 77-87. This survey can highlight challenges and future directions in resource management.

[12] Chaudhary, A. A. (2022). Asset-Based Vs Deficit-Based Esl Instruction: Effects On Elementary Students Academic Achievement And Classroom Engagement. Migration Letters, 19(S8), 1763-1774.

How to cite this paper

Manoj Bhoyar "Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 709-717
Manoj Bhoyar "Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022
Manoj Bhoyar (2022). Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency. Iconic Research And Engineering Journals, 6(1).
Manoj Bhoyar "Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency" Iconic Research And Engineering Journals, vol. 6, no. 1, Jul. 2022.
@article{1703606,
      author = {Manoj Bhoyar},
      title = {Innovative Paradigms in Advanced Cloud Computing: Exploring Edge Computing, Serverless Architectures, and Autonomous Resource Management for Enhanced Scalability and Efficiency},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {1},
      pages = {709-717},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703606.pdf},
      abstract = {Cloud computing is another rapidly advancing technology area that has expanded the possibilities for managing and growing infrastructure for contemporary organizations. Growing business requirements for reliable, elastic, and real-time solutions are responded to by edge computing, serverless solutions, and self-managed resources. Edge computing reduces data processing centralization by performing a part of the calculation near the data source and helps improve real-time decisions in the IoT setting. Serverless solutions allow a developer to build app solutions without worrying about the details of underlying infrastructure frameworks, and services can scale as needed while being cost-effective. On the other hand, autonomous resource management, enabled using AI and machine learning coordinator, greatly enhances resource management and the overall organizational self-organizing, self-optimization, and healing processes, thus strengthening the organization?s organizational Roi and scalability. This paper aims to discuss the combined approach of these paradigms, looking at their opportunities, constraints, and effects on future advancements in cloud computing. SAP products make new approaches to upgrade the scaleability and cost-effectiveness by implementing these superior technology-programmed applications for businesses to increase innovation in an increased data-oriented business environment.},
      keywords = {Serverless Architectures, Autonomous Resource Management, Cloud Scalability, Real-time Data Processing},
      month = {July},
  }