His primary scientific interests are in Distributed computing, Data center, Scheduling, Real-time computing and Workload. His Distributed computing research is multidisciplinary, relying on both Speculative execution, Theoretical computer science, Resource allocation and Operations research. His Data center study also includes
His Scheduling research is multidisciplinary, incorporating perspectives in Queue and Scalability. His work is dedicated to discovering how Real-time computing, Server are connected with Online algorithm and other disciplines. His Processor sharing research integrates issues from Mathematical optimization and Robustness.
His primary areas of study are Mathematical optimization, Scheduling, Distributed computing, Competitive analysis and Online algorithm. His Mathematical optimization study combines topics from a wide range of disciplines, such as Control, Upper and lower bounds and Regret. Adam Wierman combines subjects such as Workload, Queue, Queueing theory and Response time with his study of Scheduling.
Adam Wierman has included themes like Real-time computing and Operations research in his Workload study. The Real-time computing study which covers Data center that intersects with Supply. His study looks at the relationship between Distributed computing and topics such as Server, which overlap with Load balancing.
Adam Wierman spends much of his time researching Mathematical optimization, Electric power system, Distributed computing, Control and Competitive analysis. Adam Wierman interconnects State and Server in the investigation of issues within Mathematical optimization. The various areas that Adam Wierman examines in his Electric power system study include Automatic frequency control, Control theory and Reliability.
While the research belongs to areas of Distributed computing, Adam Wierman spends his time largely on the problem of Scalability, intersecting his research to questions surrounding Structure, Workload and Entropy. His work deals with themes such as Online algorithm and Online optimization, which intersect with Competitive analysis. His work in Throughput addresses issues such as Queue, which are connected to fields such as Scheduling.
His primary areas of investigation include Mathematical optimization, Control, Constant, Competitive analysis and Online optimization. His studies deal with areas such as Nonlinear control, Temporal difference learning, Contrast, Dynamical system and State as well as Mathematical optimization. His Control research includes elements of Upper and lower bounds and Regret.
His Competitive analysis research incorporates elements of Connection, Online algorithm, Leverage and Descent. Borrowing concepts from Class, Adam Wierman weaves in ideas under Convex optimization. Class is intertwined with Scalability, Structure, Distributed computing, Distance and Property in his study.
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.
Dynamic right-sizing for power-proportional data centers
Minghong Lin;Adam Wierman;Lachlan L. H. Andrew;Eno Thereska.
IEEE ACM Transactions on Networking (2013)
Greening geographical load balancing
Zhenhua Liu;Minghong Lin;Adam Wierman;Steven Low.
IEEE ACM Transactions on Networking (2015)
Renewable and cooling aware workload management for sustainable data centers
Zhenhua Liu;Yuan Chen;Cullen Bash;Adam Wierman.
measurement and modeling of computer systems (2012)
Open versus closed: a cautionary tale
Bianca Schroeder;Adam Wierman;Mor Harchol-Balter.
networked systems design and implementation (2006)
Power-Aware Speed Scaling in Processor Sharing Systems
A. Wierman;L. L. H. Andrew;A. Tang.
international conference on computer communications (2009)
Online algorithms for geographical load balancing
Minghong Lin;Zhenhua Liu;Adam Wierman;Lachlan L. H. Andrew.
2012 International Green Computing Conference (IGCC) (2012)
Data center demand response: avoiding the coincident peak via workload shifting and local generation
Zhenhua Liu;Adam Wierman;Yuan Chen;Benjamin Razon.
measurement and modeling of computer systems (2013)
Distributed Welfare Games
Jason R. Marden;Adam Wierman.
Operations Research (2013)
Geographical load balancing with renewables
Zhenhua Liu;Minghong Lin;Adam Wierman;Steven H. Low.
measurement and modeling of computer systems (2011)
Classifying scheduling policies with respect to unfairness in an M/GI/1
Adam Wierman;Mor Harchol-Balter.
measurement and modeling of computer systems (2003)
Profile was last updated on December 6th, 2021.
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