What is he best known for?
The fields of study he is best known for:
- Computer network
- Operating system
- The Internet
His primary areas of study are Cloud computing, Distributed computing, Energy consumption, Efficient energy use and Scheduling.
His studies in Cloud computing integrate themes in fields like Computer security, Data center and Server.
He interconnects Workload, Service-level agreement, Game theory, Cloud testing and Job shop scheduling in the investigation of issues within Distributed computing.
His Efficient energy use research incorporates elements of Scalability, Resource allocation, Telecommunications, Upload and Information and Communications Technology.
Samee U. Khan focuses mostly in the field of Scheduling, narrowing it down to topics relating to Directed acyclic graph and, in certain cases, End-user computing, Data stream, Critical path method and Heuristic.
As part of one scientific family, he deals mainly with the area of Utility computing, narrowing it down to issues related to the Provisioning, and often Frequency scaling and Simulation.
His most cited work include:
- The rise of big data on cloud computing (1388 citations)
- A Survey of Mobile Cloud Computing Application Models (461 citations)
- Security in cloud computing (456 citations)
What are the main themes of his work throughout his whole career to date?
Samee U. Khan mainly investigates Distributed computing, Cloud computing, Computer network, Scheduling and Energy consumption.
The concepts of his Distributed computing study are interwoven with issues in Resource allocation, Dynamic priority scheduling, Job shop scheduling and Fair-share scheduling.
His research in Cloud computing intersects with topics in Computer security, Scalability, Server and Data center.
His Server study incorporates themes from Virtual machine and Game theory.
His Scheduling study combines topics from a wide range of disciplines, such as Workload, Grid computing and Schedule.
His Energy consumption research includes themes of Real-time computing, Efficient energy use and Heuristics.
He most often published in these fields:
- Distributed computing (41.91%)
- Cloud computing (35.05%)
- Computer network (18.14%)
What were the highlights of his more recent work (between 2017-2021)?
- Cloud computing (35.05%)
- Distributed computing (41.91%)
- Energy consumption (16.67%)
In recent papers he was focusing on the following fields of study:
Samee U. Khan focuses on Cloud computing, Distributed computing, Energy consumption, Big data and Server.
The study incorporates disciplines such as Computer security, Scheduling, Computer network, Encryption and Enhanced Data Rates for GSM Evolution in addition to Cloud computing.
His Scheduling research is multidisciplinary, incorporating perspectives in Real-time computing and Frequency scaling.
His Distributed computing study integrates concerns from other disciplines, such as Scalability, Virtualization, Workload, Quality of service and Edge computing.
His Energy consumption research integrates issues from Virtual machine, Reduction, Data center, Data stream processing and Efficient energy use.
His study looks at the intersection of Big data and topics like Data science with Recommender system.
Between 2017 and 2021, his most popular works were:
- Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers (113 citations)
- FogNetSim++: A Toolkit for Modeling and Simulation of Distributed Fog Environment (55 citations)
- A Double Deep Q-Learning Model for Energy-Efficient Edge Scheduling (51 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- The Internet
His primary scientific interests are in Cloud computing, Distributed computing, Energy consumption, Edge computing and Scheduling.
In his study, which falls under the umbrella issue of Cloud computing, Wireless ad hoc network and Dissemination is strongly linked to Computer network.
His biological study spans a wide range of topics, including Scalability, Virtualization, Quality of service, Elasticity and Server.
His study explores the link between Virtualization and topics such as Virtual machine that cross with problems in Data center.
The Energy consumption study combines topics in areas such as Reduction, Knapsack problem, Greedy algorithm and Parallel computing.
His research in Edge computing intersects with topics in Edge device, Renewable energy, Efficient energy use and Energy management.
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