What is he best known for?
The fields of study he is best known for:
- Computer network
- Statistics
- The Internet
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.
His most cited work include:
- Greening geographical load balancing (408 citations)
- Dynamic right-sizing for power-proportional data centers (332 citations)
- Dynamic right-sizing for power-proportional data centers (274 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Computer network (44.75%)
- Distributed computing (15.47%)
- Mathematical optimization (14.92%)
What were the highlights of his more recent work (between 2012-2021)?
- Mathematical optimization (14.92%)
- Computer network (44.75%)
- Competitive analysis (4.42%)
In recent papers he was focusing on the following fields of study:
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.
Between 2012 and 2021, his most popular works were:
- Dynamic right-sizing for power-proportional data centers (274 citations)
- Short-term residential load forecasting: Impact of calendar effects and forecast granularity (111 citations)
- Greening geographical load balancing (80 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- The Internet
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.
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