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Ligang He

Researcher at University of Warwick

Publications -  172
Citations -  2585

Ligang He is an academic researcher from University of Warwick. The author has contributed to research in topics: Scheduling (computing) & Cloud computing. The author has an hindex of 24, co-authored 157 publications receiving 1967 citations. Previous affiliations of Ligang He include Hunan University & University of Cambridge.

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Proceedings ArticleDOI

Optimal dispatching and scheduling for both periodic and aperiodic jobs in cluster

TL;DR: Based on extensive simulation studies, it is have that the algorithms proposed in the paper can achieve great performance improvement and work out the workload zone in which the response time of aperiodic jobs in the cluster with N schedulers is the same as the ideal bound of response time in the corresponding M/M/N model.
Proceedings ArticleDOI

An efficient method for motif discovery in CPU host load

TL;DR: The framework is elaborately designed to take into account the important properties in host load data and benefits from its ability of on-line discovery and the adaptivity to work with massive data.

Developing lightweight application execution mechanisms in grids

TL;DR: The experimental results suggest that the execution mechanism based on data servers is able to deliver higher performance; moreover, if multiple data replicas are provided, even higher performance can be achieved.
Proceedings ArticleDOI

ModellingWeb transfer Performance over Asymmetric Networks

TL;DR: The effects of bandwidth asymmetry on Web-like short-lived transfers is investigated and a close-form prediction model is presented for TCP transfers over asymmetric links and the Web transfer model is derived from it.
Proceedings ArticleDOI

iFlatLFS: Performance optimization for accessing massive small files

TL;DR: iFlatLFS aims to substitute the traditional file system on data servers that are mainly used to store small files, and it can greatly simplify the original data access procedure, as well as optimizing the performance of data servers in accessing massive small files.