What is he best known for?
The fields of study he is best known for:
- The Internet
- Computer network
- Artificial intelligence
His primary areas of investigation include Knowledge management, Scalability, The Internet, Distributed computing and Data science.
His work on Knowledge sharing as part of general Knowledge management study is frequently linked to Systematic review, Psychology and E-learning, therefore connecting diverse disciplines of science.
His Scalability research incorporates themes from Algorithm, Particle swarm optimization, Provisioning and Data as a service.
The concepts of his The Internet study are interwoven with issues in Customer satisfaction, Competitive advantage, Cloud computing security and Process management.
His work in the fields of Distributed computing, such as Load balancing, intersects with other areas such as Information technology.
His Data science study integrates concerns from other disciplines, such as Telecommunications network, Data aggregator and World Wide Web.
His most cited work include:
- An improved genetic algorithm for task scheduling in the cloud environments using the priority queues: Formal verification, simulation, and statistical testing (143 citations)
- Load balancing mechanisms and techniques in the cloud environments (115 citations)
- Customer relationship management mechanisms (107 citations)
What are the main themes of his work throughout his whole career to date?
Nima Jafari Navimipour mainly investigates Distributed computing, Data science, Quantum dot cellular automaton, Scalability and World Wide Web.
In his research, Genetic algorithm is intimately related to Scheduling, which falls under the overarching field of Distributed computing.
His biological study spans a wide range of topics, including Field, Recommender system, Collaborative filtering and The Internet.
His Scalability study combines topics from a wide range of disciplines, such as Utility computing, Cloud computing security and Reliability.
His research in World Wide Web is mostly concerned with Peer-to-peer.
Nima Jafari Navimipour interconnects Algorithm, Ant colony and Software-defined networking in the investigation of issues within Load balancing.
He most often published in these fields:
- Distributed computing (20.61%)
- Data science (13.74%)
- Quantum dot cellular automaton (12.98%)
What were the highlights of his more recent work (between 2019-2021)?
- Cluster analysis (6.11%)
- Energy consumption (5.34%)
- Quantum dot cellular automaton (12.98%)
In recent papers he was focusing on the following fields of study:
Nima Jafari Navimipour focuses on Cluster analysis, Energy consumption, Quantum dot cellular automaton, Distributed computing and Fog computing.
The Cluster analysis study combines topics in areas such as Service composition, Cloud service composition and Data mining.
His Quantum dot cellular automaton study deals with the bigger picture of Cellular automaton.
His work carried out in the field of Distributed computing brings together such families of science as Quality of service, Virtualization and Emerging technologies.
His research in Quality of service intersects with topics in Formal verification, Viterbi algorithm, Hidden Markov model and Service.
Nima Jafari Navimipour has included themes like Latency, Multimedia, Edge computing and World Wide Web in his Fog computing study.
Between 2019 and 2021, his most popular works were:
- A hybrid formal verification approach for QoS-aware multi-cloud service composition (13 citations)
- Quality of service‐aware approaches in fog computing (11 citations)
- Priority-based task scheduling method over cloudlet using a swarm intelligence algorithm (10 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Computer network
- Artificial intelligence
Nima Jafari Navimipour mostly deals with Fog computing, Edge computing, World Wide Web, Quality of service and Energy consumption.
His Quality of service research integrates issues from Latency, Distributed computing, Multimedia, Service and Formal verification.
His Energy consumption studies intersect with other disciplines such as Functional specification, Job shop scheduling, Load balancing, Scheduling and Swarm intelligence.
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