!!Rajkumar Buyya - Publications
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__PUBLICATIONS’ CONTEXT & SUMMARY__\\
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In Computer Science, research outputs are disseminated by publications in journals and conference proceeding; both venues are well regarded in our discipline. Journal papers are generally more significant due to their in-depth analysis of their research contributions.\\
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Professor Buyya’s publications reflect his research philosophy of completing the entire research and innovation cycle – from developing the new concepts in computing paradigms to creating prototype systems with application demonstrators. His research papers are either the first or among the first to present ground-breaking ideas to the field, making innovative contributions that are adopted by others. His top 10 outputs are landmark and seminal papers on systems, algorithms, and technologies for grid, cloud, and edge computing and paved the way for new breakthroughs in computer science. Associated software systems that he developed, such as CloudSim, are used by several organisations including CalTech, Columbia Uni., IBM, HP, and Ericsson in 50+ countries worldwide. For being at the forefront of his research areas, he is able to produce high impact research outcomes and attract funding from varies agencies and companies. He has been recognised as “Web of Science Highly Cited Researcher” “six” times since 2016.\\
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__PUBLICATIONS IMPACT/ESTEEM__\\
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Buyya has authored >755 publications, including 380 journal papers, 310 conference papers, six textbooks, and 10 edited books, attracting >123,300 GS citations and an h-index of 153.  Most of his papers have appeared in ERA (Excellence for Research in Australia) A/A* rated venues (CORE ranking http://www.core.edu.au/); and 12 have received “Best Paper Awards” from IEEE and Elsevier. Several are referenced by prominent researchers such as ACM Turing Award recipient Dr Patterson from UC Berkley. His book “Mastering Cloud Computing” has been adopted as a textbook in the curriculum of many universities in the US, Brazil, Europe, China, and India. \\
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The esteem of journals is also demonstrated by their relative impact factors (IF) according to SCI (Science Citation Index), Google Scholar H5-index along with CORE ranking in the field.  Some of these highly regarded journals, where he has published, include IEEE Transactions on Parallel and Distributed Systems (IF: 4.181, H5-index 106, CORE A*), IEEE Transactions on Services Computing (IF: 5.8,  H5-index 86, CORE2020 A*), IEEE Transactions on Cloud Computing (IF: 7.928, H5-index 77), Future Generation Computer Systems (IF: 7.18, H5-index 127), IEEE Transactions on Mobile Computing (IF: 5.11, H5-index 71, CORE A*), Proceedings of the IEEE (IF: 16.79, Q1, ERA A*), IEEE Communications Surveys and Tutorials (IF: 25.25, H5-index 248), and ACM Computing Surveys (IF: 10.28, H5-index 141, CORE A*).\\
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__TOP 10 PUBLICATIONS__ \\
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1. R. Buyya, D. Abramson, and S. Venugopal, “The Grid Economy”, Proceedings of the IEEE, 93(3): 698-714, IEEE Press, New Jersey, USA, March 2005. [[IF: 10.25, ERA (2010 Rank) A*]\\
 * A definitive work on Grid economy and architectural models for management of resources of compute and data-intensive applications in distributed systems, which are playing a significant role in Cloud platforms from Amazon, Google, and Microsoft. It attracted 724+ Google scholar citations.\\
 * Journal Impact Factor: 10.25, Rank 6/260, Engineering, Electrical & Electronic (InCites Journal Citation Reports)\\
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2.  R. Ranjan, A. Harwood, and R. Buyya, “Peer-to-peer-based Resource Discovery in Global Grids: a tutorial”, IEEE Communication Surveys and Tutorials (COMST), IEEE Communications Surveys and Tutorials, Volume 10, Number 2, Pages: 6-33, IEEE Communications Society Press, USA, 2008. [[IF: 22.973, Google H5-Index 248]\\
 * Winner of “2009 Outstanding Paper Award” from the IEEE Communications Society. IEEE Communications Surveys and Tutorial is ranked the #1 journal in computer science and electronics for 2016, 2017, 2018, 2019, and 2020 based on its impact factor (22.973). Google Scholar Ranks this journal #1 based on its H5-Index (248) in the Computer Networks and Wireless Communication research area.\\
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3. R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, “Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility”, Future Generation Computer Systems, Volume 25, Number 6, Pages: 599-616, ISSN: 0167-739X, Elsevier Science, Amsterdam, The Netherlands, June 2009. [[IF: 7.187, H5-index 77, CORE A] \\
 * A definitive work laying out the vision and identifying new research challenges in Cloud computing. It attracted 8200+ Google Scholar citations. Scopus noted it as the most cited (#1 position) work published in FGCS.\\
 * Journal Impact Factor: 7.187, Rank 7/103 Computer Science, Theory & Methods (InCites JCR).\\
 * Highly Cited Paper, top 1% of its field - a highly cited threshold for the field & publication year (Web of Science).\\
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4. R. Calheiros, R. Ranjan, A. Beloglazov, C. De Rose, and R. Buyya, “CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms”, Software: Practice and Experience (SPE), Volume 41, Number 1, Pages: 23-50, Wiley Press, New York, USA, January 2011. [[CORE A]\\
 * Along with a model for InterClouds, the paper led to the creation of CloudSim software, which is the world's most widely adopted cloud computing simulation, benchmarking, and performance evaluation toolkit. The CloudSim software (www.cloudbus.org/cloudsim/) has over 8,000 downloads and is used globally by IBM Labs, HP, Ericsson and prestigious universities and research institutions. It attracted 5525+ Google Scholar citations.\\
 * Highly Cited Paper, top 1% of its field - a highly cited threshold for the field & publication year (Web of Science).\\
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5.  (*) A. Beloglazov and R. Buyya, "Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers Under Quality of Service Constraints", IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 24, No. 7, Pages: 1366-1379, IEEE CS Press, Los Alamitos, CA, USA, July 2013.. [[CORE A*, IF: 4.181, H5-index 106] \\
 * Proposed novel algorithms and policies for dynamic provisioning and consolidation of Cloud resources for minimizing cost and energy consumption of servers yet meeting user QoS requirements. This paper has >3570 downloads through IEEE Xplore. IEEE TPDS is Ranked #3 in Computing Systems area based on its H5-index (106) by Google Scholar. The paper attracted 556+ Google scholar citations.\\
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6. L. Wu, S. Garg, S. Versteeg, and R. Buyya, “SLA-Based Resource Provisioning for Hosted Software-as-a-Service Applications in Cloud Computing Environments”, IEEE Transactions on Services Computing (TSC), Volume 7, Number 3, Pages: 456-485, IEEE Computer Society Press, USA, July-September 2014. (CORE A*, IF: 5.8,  H5-index 86)\\
 * Proposed a novel method for the effective management of Cloud resources to meet users Quality of Service (QoS) requirements. We demonstrated to our industry partner—CA for incorporating into their Cloud infrastructure management solutions. The paper also influenced on Cloud Service Measurement Index standards. This paper has >2355 downloads through IEEE Xplore. \\
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7. (*) R. Calheiros and R. Buyya, “Meeting Deadlines of Scientific Workflows in Public Clouds with Tasks Replication”, IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 25, Issue 7, Pages: 1787 - 1796, IEEE CS Press, Los Alamitos, CA, USA, July 2014. [[CORE A*, IF: 4.181, H5-index 106] \\
 * Proposed innovative Cloud resource provisioning and workflow application scheduling on Clouds to meet user Quality of Service (QoS) requirements such as deadlines. It attracted 253+ Google Scholar citations. This paper has >1755 downloads through IEEE Xplore. IEEE TPDS is Ranked #3 in Computing Systems area based on its H5-index (106) by Google Scholar.\\
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8. R. Calheiros, E. Masoumi, R. Ranjan and R. Buyya, "Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS," in IEEE Transactions on Cloud Computing (TCC), Volume 3, Number 4, Pages: 449-458, IEEE Computer Society Press, USA, Oct.-Dec. 2015. [[IF: 7.928, H5-index 77]  \\
 *This work proposes a new workload prediction technique that dynamically decides on the allocation of resources to the cloud applications with the aim of lowering the cost for the application providers along with delivering good quality of service to the end-users. Experimental evaluations, using real traces of workload from the Wikimedia Foundation, show that the proposed model can achieve up to 91% accuracy. The most cited paper, according to Scopus, among 613 papers published with IEEE TCC (IF: 7.9), since its inception in 2013. It attracted 435+ Google Scholar citations.\\
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9. S. Ilager, K. Ramamohanarao, and R. Buyya, “Thermal Prediction for Efficient Energy Management of Clouds using Machine Learning”, IEEE Transactions on Parallel and Distributed Systems (TPDS), Volume 32, No. 5, Pages: 1044-1056, ISSN: 1045-9219, IEEE Computer Society Press, USA, May 2021. [[CORE A*, IF: 4.181, H5-index 106]\\
 * Proposed a novel data-driven/machine learning method for thermal prediction for use in efficient management of resources for Cloud Data Centre and reduce their energy consumption by 35%. This paper has >745 downloads through IEEE Xplore. IEEE TPDS is Ranked #3 in Computing Systems area based on its H5-index (106) by Google Scholar.\\
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10. M. Goudarzi, H. Wu, M. Palaniswami, and R. Buyya, “An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments”, IEEE Transactions on Mobile Computing (TMC), Volume 20, Number 4, Pages: 1298-1311, IEEE Computer Society Press, USA, April 2021. [[CORE A*, IF: 5.57, H5-index 71]\\
 *Proposed a novel method for batch scheduling of concurrent IoT applications in Edge computing systems. The performance results demonstrate that our technique significantly improves the weighted cost of IoT applications up to 65 percent in comparison to its counterparts. This paper has >2855 downloads through IEEE Xplore; recognised as Highly-Cited Paper in Web of Science in its publication year.