H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 64 Citations 21,307 300 World Ranking 1239 National Ranking 69

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Cloud computing
  • Computer network

Rajiv Ranjan mostly deals with Cloud computing, Distributed computing, Big data, Scalability and Quality of service. His Cloud computing research incorporates themes from Computer network, Server and Provisioning. His Distributed computing research is multidisciplinary, incorporating elements of Virtual machine, Scheduling, CloudSim, Utility computing and Grid computing.

Rajiv Ranjan has researched CloudSim in several fields, including Data center and Intercloud. His Big data research integrates issues from Data security, Sparse approximation and Distributed database. His studies in Quality of service integrate themes in fields like Web server, Resource and Operating system.

His most cited work include:

  • CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms (3363 citations)
  • InterCloud: utility-oriented federation of cloud computing environments for scaling of application services (808 citations)
  • Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities (781 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Cloud computing, Distributed computing, Big data, Quality of service and Scalability. His Cloud computing research also works with subjects such as

  • Data science that intertwine with fields like Software,
  • Virtual machine which connect with Data center. His biological study spans a wide range of topics, including Grid computing, Resource, Scheduling, Provisioning and Workflow.

He interconnects Data modeling, Analytics and The Internet in the investigation of issues within Big data. His Quality of service study combines topics in areas such as Enhanced Data Rates for GSM Evolution and Cloud testing. Scalability is often connected to Service in his work.

He most often published in these fields:

  • Cloud computing (67.12%)
  • Distributed computing (37.77%)
  • Big data (27.99%)

What were the highlights of his more recent work (between 2018-2021)?

  • Cloud computing (67.12%)
  • Distributed computing (37.77%)
  • Big data (27.99%)

In recent papers he was focusing on the following fields of study:

Rajiv Ranjan focuses on Cloud computing, Distributed computing, Big data, Quality of service and Enhanced Data Rates for GSM Evolution. Particularly relevant to Edge computing is his body of work in Cloud computing. His research on Distributed computing also deals with topics like

  • Workflow that intertwine with fields like Scheduling and Orchestration,
  • Scalability and related Provisioning.

His study looks at the relationship between Big data and topics such as Data science, which overlap with Data analysis. The Quality of service study combines topics in areas such as Service and Cloud testing. His Enhanced Data Rates for GSM Evolution study combines topics from a wide range of disciplines, such as Computer security and Resource.

Between 2018 and 2021, his most popular works were:

  • A Hybrid Deep Learning-Based Model for Anomaly Detection in Cloud Datacenter Networks (75 citations)
  • SAFE: SDN-Assisted Framework for Edge–Cloud Interplay in Secure Healthcare Ecosystem (41 citations)
  • Renewable Energy-Based Multi-Indexed Job Classification and Container Management Scheme for Sustainability of Cloud Data Centers (40 citations)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms

Rodrigo N. Calheiros;Rajiv Ranjan;Anton Beloglazov;César A. F. De Rose.
Software - Practice and Experience (2011)

4626 Citations

InterCloud: utility-oriented federation of cloud computing environments for scaling of application services

Rajkumar Buyya;Rajiv Ranjan;Rodrigo N. Calheiros.
international conference on algorithms and architectures for parallel processing (2010)

1116 Citations

Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities

Rajkumar Buyya;Rajiv Ranjan;Rodrigo N. Calheiros.
international conference on high performance computing and simulation (2009)

1108 Citations

CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services

Rodrigo N. Calheiros;Rajiv Ranjan;César A. F. De Rose;Rajkumar Buyya.
arXiv: Distributed, Parallel, and Cluster Computing (2009)

596 Citations

Workload Prediction Using ARIMA Model and Its Impact on Cloud Applications’ QoS

Rodrigo N. Calheiros;Enayat Masoumi;Rajiv Ranjan;Rajkumar Buyya.
ieee international conference on cloud computing technology and science (2015)

383 Citations

G-Hadoop: MapReduce across distributed data centers for data-intensive computing

Lizhe Wang;Jie Tao;Rajiv Ranjan;Holger Marten.
Future Generation Computer Systems (2013)

376 Citations

Virtual Machine Provisioning Based on Analytical Performance and QoS in Cloud Computing Environments

Rodrigo N. Calheiros;Rajiv Ranjan;Rajkumar Buyya.
international conference on parallel processing (2011)

356 Citations

Remote sensing big data computing

Yan Ma;Haiping Wu;Lizhe Wang;Bormin Huang.
Future Generation Computer Systems (2015)

350 Citations

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

Abdul Hameed;Alireza Khoshkbarforoushha;Rajiv Ranjan;Prem Prakash Jayaraman.
Computing (2016)

283 Citations

Streaming Big Data Processing in Datacenter Clouds

Rajiv Ranjan.
IEEE Cloud Computing (2014)

275 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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