时间：5 月 5 日周一上午 10:00-11:30
地点：计算机楼 405
讲者： Prof. Dieter Hogrefe，哥廷根大学
Prof. Xiaoming Fu，哥廷根大学
联系人：王新 xinw@fudan.edu.cn
Title: "Computer Science in Göttingen"
Speaker: Prof. Dieter Hogrefe (University of Göttingen, Germany)
Abstract:
The presentation will give an overview on the study programms and research groups in Computer Science in Göttingen with the special emphasis on how Computer Science interacts in an interdisciplinary way with other sciences, such as natural sciences, social sciences, life sciences, etc.
Short Bio:
http://www.uni-goettingen.de/en/133497.html
Title: Fine-Grained Multi-Resource Scheduling in Cloud Datacenters
Speaker: Prof. Xiaoming Fu (University of Göttingen, Germany)
Abtract: Cloud datacenters typically require tenants to specify the resource
demands for the virtual machines (VMs) they create using a set of
pre-defined, fixed configurations, to ease the resource allocation
problem. Unfortunately, this leads to low resource utilization of
cloud datacenters as tenants are obligated to conservatively
predict the maximum resource demand of their applications. We argue
that instead of such a static VM resource allocation, a finer-grained
dynamic resource allocation and scheduling can substantially improve
the utilization of the datacenter resources by increasing the number
of jobs accommodated and correspondingly, the cloud datacenter
provider's revenue. The dynamic real-time scheduling of jobs can also
ensure that the performance goals for the tenant VMs are achieved.
Examining a typical publicly available cluster data center trace, we
observe that a large number of jobs are short. Only a small proportion
of jobs are long and which require substantial compute or memory
resources.
We propose an optimization based approach that exploits this division
between the short and long jobs to dynamically allocate a cloud
datacenter's resources to achieve significantly better utilization by
increasing the number of jobs accommodated by the datacenter. We use
a constraint programming solution to schedule the long jobs, and use
simple heuristics to quickly, yet quite accurately schedule the short
jobs. Using trace-driven simulations based on public traces collected
on provider cluster we show that the overall revenue for the cloud
provider can be improved by 30% over the traditional static VM
resource allocation based on the coarse granularity specifications. We
are able to increase the number of jobs accommodated using dynamic
scheduling by 18%. We also compare the performance of our approach
to multi-resource (CPU and memory) first-fit and best-fit algorithms
and to the optimal offline solution, and demonstrate that our solution
achieves within 76% of the offline optimal solution.
This is joint work with Yuan Zhang (Uni Göttingen) and K. K. Ramakrishnan (USA).
Short bio:
Xiaoming Fu obtained his Ph.D. degree in Computer Science from Tsinghua University, China in 2000. He worked as a research staff at Technical University Berlin before joining the University of Göttingen in 2002, where he has been a Professor and heading the Computer Networks Group since 2007. His research areas include architecture, protocols and applications of Internet-based communication systems. He has been involved in EC FP6 ENABLE, MING-T, VIDIOS, Daidalos-II projects and is coordinator of FP7 GreenICN, MobileCloud and CleanSky projects. He is an IEEE Senior Member and an IEEE Communications Society Distinguished Lecturer. He served as Secretary (2008-2010) and Vice Chair (2010-2012) of IEEE ComSoc TCCC, then Chair (2011-2013) of the Internet Technical Committee of the IEEE ComSoc and the Internet Society. Currently he serves on the editorial boards of IEEE Communications Magazine, TNSM, Elsevier ComNet and ComCom journals.
