Abstract :

Cloud Computing Is Really Good At Giving Us The Computing Resources We Need When We Need Them.. Sometimes Things Do Not Go As Planned And Jobs Fail. This Happens Because We Do Not Have Resources Or They Are Being Used Too Much. Network Latency And Resource Contention Are Also Problems. When Jobs Fail The System Does Not Work Well As It Should And It Costs More Money To Run. If We Can Predict When Jobs Are Going To Fail Before They Actually Do And If We Can Give Them The Amount Of Resources That Would Be Great. It Would Make Cloud Computing A Lot More Reliable And Efficient. This Project, IntelliCloudPlus Is Trying To Do That. It Uses Machine Learning To Predict When Cloud Jobs Will Fail And To Figure Out The Way To Give Them The Resources They Need. We Use Something Called A Stacking Classifier To Look At Lots Of Things, About Each Job Like How Much CPU And Memory It Needs How Long It Takes To Run And How Healthy The Machine Is. We Also Look At How Much Resources Are Being Used And How Long It Takes For Things To Happen On The Network. Then We Have Something Called The Intelligent Resource Optimization And Recommendation Engine. This Thing Looks At The Jobs That Are Predicted To Fail And Comes Up With A Plan To Make Them Work Better. It Tells Us How To Give Them The Amount Of CPU, Memory And Disk Space. It Also Helps Us Figure Out The Way To Schedule Them Make The Network Work Better And Balance Out The Resources.. It Gives Us A Summary Of What It Thinks We Should Do Including How Bad The Problems Are How Much Better Things Will Work If We Follow Its Advice And How Much Money We Will Save. It Is A Website That People Can Use To Log In Send In Jobs And Get Predictions And Recommendations. It Even Keeps Track Of What Happened In The Past. Our Solution Helps Us Use Resources Better Makes Sure Jobs Do Not Fail Much And Helps Us Make Smart Decisions When It Comes To Cloud Computing.

Published:

24-8-2026

Issue:

Vol. 26 No. 8 (2026)

Page Nos:

1071 - 1076

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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