What is he best known for?
The fields of study he is best known for:
- The Internet
- Computer network
- Operating system
His primary scientific interests are in World Wide Web, Web server, Computer network, The Internet and Workload.
His World Wide Web research integrates issues from Video sharing, Limiting, Timeline, Simulation and Bandwidth.
His research in Web server intersects with topics in Web service, Service level objective, Database, Control theory and Testbed.
His studies deal with areas such as Web application, Container and Adaptive control as well as Computer network.
His research integrates issues of Machine learning, Cluster analysis, Artificial intelligence and Data mining in his study of The Internet.
His study in Workload is interdisciplinary in nature, drawing from both Server and Scripting language.
His most cited work include:
- Youtube traffic characterization: a view from the edge (778 citations)
- Web server workload characterization: the search for invariants (734 citations)
- A workload characterization study of the 1998 World Cup Web site (713 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns World Wide Web, Computer network, The Internet, Database and Server.
His World Wide Web study which covers Multimedia that intersects with Web 2.0 and Session.
Martin Arlitt has included themes like Cloud computing, Data mining and Network packet in his The Internet study.
He combines subjects such as Web server and Cache with his study of Database.
His Web server study integrates concerns from other disciplines, such as Application server and Web service.
Martin Arlitt interconnects Computer security, Workload, Resource and Data center in the investigation of issues within Server.
He most often published in these fields:
- World Wide Web (19.02%)
- Computer network (17.18%)
- The Internet (16.56%)
What were the highlights of his more recent work (between 2010-2020)?
- The Internet (16.56%)
- Data mining (11.66%)
- World Wide Web (19.02%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in The Internet, Data mining, World Wide Web, Multimedia and Server.
His The Internet study combines topics from a wide range of disciplines, such as Computer security, Key, Protocol and Video streaming.
His Data mining research is multidisciplinary, relying on both Value, Web server, Logfile and Artificial intelligence.
His World Wide Web research incorporates themes from Scalability and Enhanced Data Rates for GSM Evolution.
His work carried out in the field of Server brings together such families of science as Workload and Provisioning.
His work deals with themes such as Early adopter, Download, BitTorrent and Database, which intersect with Workload.
Between 2010 and 2020, his most popular works were:
- Unsupervised disaggregation of low frequency power measurements (394 citations)
- Device characterization system and methods (131 citations)
- Minimizing data center SLA violations and power consumption via hybrid resource provisioning (118 citations)
In his most recent research, the most cited papers focused on:
- The Internet
- Computer network
- Operating system
Martin Arlitt mostly deals with Data center, Power management, Provisioning, Workload and Server.
His work focuses on many connections between Power management and other disciplines, such as Distributed computing, that overlap with his field of interest in Green computing, Base load power plant and Resource allocation.
His Provisioning study combines topics in areas such as Data center services and Database.
In his study, Computer security is strongly linked to World Wide Web, which falls under the umbrella field of Database.
His Server research is included under the broader classification of Computer network.
Martin Arlitt studied Computer network and Virtualization that intersect with Resource.
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.
