Abstract
Objectives: This work reviewed the latest, state-of-the-art works in the area of Cloud Computing to help researchers, developers and stakeholders in decisionmaking. Method: The reviewed works are filtered after the rigorous process by using renowned indexing database of ACM and IEEE along with the subject based journals on Cloud Computing of international repute. These papers are further filtered by selecting papers published in last 4 years only. Our initial findings lead our reviews to five major areas of Cloud Computing including Load balancing, resource scheduling, resource allocation, resource sharing, and job scheduling. In this work we have limited ourselves to only technical aspects of cloud computing while excluding areas of security, privacy and economics (for example CapEx). We have presented our findings in the form of tables and graphs showing trends in Cloud Computing towards research community on the basis of five aspects as mentioned above. Findings: Our findings show that researchers are working in the area of Job Scheduling while low attention has been given in Resource Scheduling. Moreover, an open source robust framework for research community is needed covering all the aspects shown above for running experiments. Currently these features are available in commercial and proprietary frameworks including Amazon Web Service, Microsoft Azure, and Google Cloud Platform. Keywords: Load balancing; resource scheduling; resource allocation; cloud computing; resource sharing; job scheduling
Highlights
Modern cloud computing has changed the computing paradigm with tools like i.e. Azure ML services, Amazon AWS, CV (Computer Vision) and DL (Deep Learning) services, Google Cloud, CV and DL services
Resource Sharing is the capability of cloud computing to share its resources on demand basis while Resource scheduling refers to the use of different algorithms to deliver and allocate different resources in a dynamic environment
We presented a comprehensive review of Cloud Computing
Summary
Modern cloud computing has changed the computing paradigm with tools like i.e. Azure ML services, Amazon AWS, CV (Computer Vision) and DL (Deep Learning) services, Google Cloud, CV and DL services. Survey works presented in[7] and[8] discussed cloud computing from the perspective of Virtual Machines for load balancing and resource allocation. The survey only provided the detailed discussion on job scheduling problem along-with load balancing in Cloud Computing setting. Authors investigated green computing challenges which are faced during deployment of Big Data lifecycle using two metrics namely effective energy efficiency and effective resource efficiency Researchers surveyed both areas and highlighted future directions. Authors highlighted state-ofthe-art practices for SLA based resource management and job scheduling In this survey we considered load balancing, resource scheduling, resource allocation, job scheduling and resource sharing in cloud computing environment. In this survey we only considered literature from last four-year. First we shortlisted the papers which lie under the considered categories after select papers that are most relevant to theme of this review
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