His scientific interests lie mostly in Energy consumption, Online algorithm, Real-time computing, Data center and Mathematical optimization. Lachlan L. H. Andrew has included themes like Efficient energy use, Renewable energy and Communications system in his Energy consumption study. His Online algorithm research integrates issues from Server and Competitive analysis.
Lachlan L. H. Andrew focuses mostly in the field of Server, narrowing it down to topics relating to Distributed computing and, in certain cases, Provisioning. His Real-time computing research includes elements of Distributed generation, Artificial neural network, Mean squared error, Processor sharing and Robustness. His Data center research incorporates themes from Load balancing and Load balancing.
Computer network, Distributed computing, Mathematical optimization, Network congestion and Network packet are his primary areas of study. Lachlan L. H. Andrew works mostly in the field of Computer network, limiting it down to concerns involving Wireless lan and, occasionally, Network performance. His biological study spans a wide range of topics, including Download, Quality of service, Server, Scheduling and Efficient energy use.
His work focuses on many connections between Mathematical optimization and other disciplines, such as Competitive analysis, that overlap with his field of interest in Regret and Online algorithm. His Online algorithm study combines topics in areas such as Provisioning and Data center. His research integrates issues of Energy consumption and Load balancing in his study of Data center.
Lachlan L. H. Andrew mostly deals with Mathematical optimization, Computer network, Competitive analysis, Convex optimization and Regret. Lachlan L. H. Andrew has researched Mathematical optimization in several fields, including Energy consumption, Markov model and Robustness. His work deals with themes such as IEEE 802.11, Wireless lan, Throughput and IPv4 address exhaustion, which intersect with Computer network.
His Competitive analysis study deals with Online algorithm intersecting with Efficient energy use, Server and Data center. The Efficient energy use study which covers Algorithm design that intersects with Distributed computing. His work carried out in the field of Data center brings together such families of science as Distributed algorithm, Load management and Load balancing.
His primary scientific interests are in Online algorithm, Competitive analysis, Data center, Convex optimization and Mathematical optimization. His Data center research is multidisciplinary, incorporating elements of Electricity, Load balancing, Efficient energy use and Server. His research in Convex optimization intersects with topics in Metrical task system and Regret.
His study in the field of Online optimization is also linked to topics like Stochastic control. Lachlan L. H. Andrew undertakes interdisciplinary study in the fields of Sizing and Real-time computing through his works. His Workload research overlaps with Distributed computing and Energy consumption.
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)
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)
Geographical load balancing with renewables
Zhenhua Liu;Minghong Lin;Adam Wierman;Steven H. Low.
measurement and modeling of computer systems (2011)
Connectivity, coverage and placement in wireless sensor networks.
Ji Li;Lachlan Leicester Henry Andrew;Chuan Heng Foh;Moshe Zukerman.
Optimality, fairness, and robustness in speed scaling designs
Lachlan L.H. Andrew;Minghong Lin;Adam Wierman.
measurement and modeling of computer systems (2010)
Short-term residential load forecasting: Impact of calendar effects and forecast granularity
Peteris Lusis;Peteris Lusis;Kaveh Rajab Khalilpour;Lachlan Andrew;Ariel Liebman.
Applied Energy (2017)
Understanding XCP: equilibrium and fairness
S.H. Low;L.L.H. Andrew;B.P. Wydrowski.
international conference on computer communications (2005)
Decentralized signal control for urban road networks
Tung Le;Péter Kovács;Neil Walton;Hai L. Vu.
Transportation Research Part C-emerging Technologies (2015)
Profile was last updated on December 6th, 2021.
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