What is he best known for?
The fields of study he is best known for:
- Operating system
- Database
- Programming language
His primary scientific interests are in Workflow, Cloud computing, Distributed computing, Data science and Database.
Yogesh Simmhan has researched Workflow in several fields, including e-Science and Web service, World Wide Web.
His study in e-Science is interdisciplinary in nature, drawing from both Workflow management system, Scheduling and Data management.
His work in the fields of Open research overlaps with other areas such as Reuse.
His Cloud computing research includes elements of Software architecture, Scalability, Software deployment and Information integration.
As a member of one scientific family, Yogesh Simmhan mostly works in the field of Database, focusing on Metadata and, on occasion, Data warehouse, Drill down and Data mapping.
His most cited work include:
- A survey of data provenance in e-science (986 citations)
- The Open Provenance Model core specification (v1.1) (560 citations)
- Cloud-Based Software Platform for Big Data Analytics in Smart Grids (224 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Cloud computing, Distributed computing, Data science, Workflow and Scalability.
His Cloud computing research incorporates themes from Real-time computing, Enhanced Data Rates for GSM Evolution, Software deployment and Smart city.
In his study, Quality of service is strongly linked to Dataflow, which falls under the umbrella field of Distributed computing.
Yogesh Simmhan usually deals with Data science and limits it to topics linked to Data management and e-Science.
His studies deal with areas such as Scheduling, Metadata, World Wide Web and Service as well as Workflow.
The Web service and Semantic grid research Yogesh Simmhan does as part of his general World Wide Web study is frequently linked to other disciplines of science, such as Provenance, therefore creating a link between diverse domains of science.
He most often published in these fields:
- Cloud computing (35.82%)
- Distributed computing (34.33%)
- Data science (20.90%)
What were the highlights of his more recent work (between 2018-2021)?
- Distributed computing (34.33%)
- Cloud computing (35.82%)
- Scalability (19.90%)
In recent papers he was focusing on the following fields of study:
Yogesh Simmhan mostly deals with Distributed computing, Cloud computing, Scalability, Theoretical computer science and Analytics.
His Distributed computing study combines topics in areas such as Virtual machine, Scheduling, Edge computing and Dataflow.
His Scheduling study integrates concerns from other disciplines, such as Quality of service and Workflow.
His Workflow study incorporates themes from Resource, Fog computing and Application scheduling.
Yogesh Simmhan has researched Cloud computing in several fields, including Workload, Enhanced Data Rates for GSM Evolution, Smart city and Programming paradigm.
He studied Analytics and Big data that intersect with Replication, Data management and Pipeline.
Between 2018 and 2021, his most popular works were:
- Characterizing application scheduling on edge, fog, and cloud computing resources (12 citations)
- AutoBoT : Resilient and Cost-Effective Scheduling of a Bag of Tasks on Spot VMs (7 citations)
- ElfStore: A Resilient Data Storage Service for Federated Edge and Fog Resources (5 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Database
- Programming language
Yogesh Simmhan focuses on Distributed computing, Cloud computing, Scalability, Edge computing and Theoretical computer science.
With his scientific publications, his incorporates both Distributed computing and Vehicle dynamics.
His work carried out in the field of Cloud computing brings together such families of science as Scheduling and Dataflow.
His Dataflow research is multidisciplinary, relying on both Object, Enhanced Data Rates for GSM Evolution and Workflow.
His Scalability research includes elements of Distributed object and Programming paradigm.
His Edge computing study combines topics from a wide range of disciplines, such as Data access, Edge device, Distributed data store and Computer data storage.
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