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All Journal International Journal of Multidisciplinary Sciences and Arts BULLET : Jurnal Multidisiplin Ilmu
Nur Nahar Rimi
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Humanities Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing

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The Role of AI and Machine Learning in Optimizing Cloud Resource Allocation Abdullah Al Noman; Zakir Hossain; Md Abu Shihab; Nipa Akter; Nur Nahar Rimi; Md Farhad Kabir
International Journal of Multidisciplinary Sciences and Arts Vol. 2 No. 1 (2023): International Journal of Multidisciplinary Sciences and Arts, Article January 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v1i2.2190

Abstract

Resource allocation inside the cloud infrastructure is an essential requirement for better performance and cost-effectiveness. With workloads growing so much more complex and dynamic, we now need automated solutions that allow us to move past tedious, manual resource management. AI provides a unique paradigm for optimizing resource allocation in such complex and dynamic environments. In this paper, we have compared various AI techniques such as machine learning, evolutionary algorithms and deep reinforcement learning for the problem of resource allocation in cloud infrastructure. We analyze their effectiveness for dynamic resource provisioning to satisfy performance objectives while reducing operational expenditure. We offer an in-depth performance comparison using real-world datasets and simulations to showcase the merits and drawbacks of each. Implications: We believe that our findings can offer guidelines to cloud providers, researchers, and practitioners who are interested in making proactive improvements on managing cloud infrastructures using intelligent resource allocation techniques.
Server less Architecture: Optimizing Application Scalability and Cost Efficiency in Cloud Computing Nisher Ahmed; Md Emran Hossain; S M Shadul Islam Rishad; Nur Nahar Rimi; Md Imran Sarkar
BULLET : Jurnal Multidisiplin Ilmu Vol. 1 No. 06 (2022): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

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Abstract

Server less is recognized as one of the game changing technologies in cloud computing with large gains in scalability and cost to run applications. We explore the effect of Server less computing on these important facets in this paper. Server less platforms abstract away server management: Your applications can now scale automatically based on real-time fluctuations in demand which means no more manual provisioning and promise full resource utilization. However this is driven constantly, it indeed offers consistent high performance applications and in turn a very cost effective solution by eliminating idle time with the servers as well as operational overhead. Our objective is to trace the main attributes of Server less, namely event driven, statelessness, and micro services supported, and how these features provide scalability and cost optimization benefits. In addition, the paper explores the challenges and considerations of adopting Server less computing including vendor locking, security issues, and cold starts. This research presents detailed analyses of the pros and cons of the Server less architectures, bringing crucial insights into their ability to transform application scalability and cost savings when deployed in the cloud computing arena.
Co-Authors Abdullah Al Noman Md Abu Shihab Md Emran Hossain Md Farhad Kabir Md Imran Sarkar Nipa Akter Nisher Ahmed S M Shadul Islam Rishad Zakir Hossain