Latest Cloud Computing Research Trends- May 2022

One of the best ways to keep yourself updated with the latest research trends in your field of study is to keep an eye on review articles published in reputed journals.

I got some time to review a few related to Deep learning implementation in cloud computing published in January and here they are:

​​Reinforcement Learning Applications for Performance Improvement in Cloud Computing—A Systematic Review – In this paper will provide you with an overview of various reinforcement learning-based published works and their advancement during the last 10 years. The emphasis of this paper is the study of resource allotment problems and Virtual Machine problems.

A Systematic Review of Deep Learning Approaches for Computer Network and Information Security – This research survey consolidates the details of 32 research articles which published their work on deep learning implementation for improving network anomaly detection, intrusion detection, network traffic analysis, and classification. Also, this paper discussed some open issues and future recommendations for further improvement. In my opinion, if you are struggling to find your topic of research you may follow the recommendation leads from this paper.

Comprehensive Study on Machine Learning-Based Container Scheduling in Cloud – This paper referred to different approaches for container scheduling like heuristic, metaheuristic, mathematical modelling, and machine learning. And summaries of the published research work on container orchestration as well as container scheduling. It is a good read for those who are interested in scheduling problems as this paper refers to the main features, advantages and disadvantages of some of the existing algorithms from the past 4 years.

Resource allocation optimization using artificial intelligence methods in various computing paradigms: A Review – This paper reviewed a broader aspect of artificial intelligent methods for optimizing and increasing the efficiency of network node communications(dataflow) and resource allocation. Also this paper summaries various methods used to solve the resource allocation problem in different computing environments and analyses their performance on response time, energy efficiency, throughput, cost, service consuming delay, convergence time and latency. This is a long article but I believe it worth reading for having a baseline understanding of the broader range of resource allocation problems in a cloud computing environment.

Towards Metaheuristic Scheduling Techniques in Cloud and Fog: An Extensive Taxonomic Review – This paper presented a comprehensive taxonomic review and analysis of recent metaheuristic scheduling techniques using exhaustive evaluation criteria in the cloud and fog environment. An open-source article and a good read for those who are just starting up with their research work based on metaheuristic approaches.

So this is it, I hope you found this helpful. It’s just another try to do my contribution to the Cloudsim research community.

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Anupinder Singh

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