Sharc: Managing CPU and Network Bandwidth in Shared Clusters
IEEE Transactions on Parallel and Distributed Systems
Resource overbooking and application profiling in shared hosting platforms
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Performance management for cluster-based web services
IEEE Journal on Selected Areas in Communications
A scalable application placement controller for enterprise data centers
Proceedings of the 16th international conference on World Wide Web
Server virtualization in autonomic management of heterogeneous workloads
ACM SIGOPS Operating Systems Review
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Run-time resource management in SOA virtualized environments
Proceedings of the 1st international workshop on Quality of service-oriented software systems
Rate-based SIP flow management for SLA satisfaction
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
Joint admission control and resource allocation in virtualized servers
Journal of Parallel and Distributed Computing
Self-adaptive resource management for large-scale shared clusters
Journal of Computer Science and Technology
Untangling mixed information to calibrate resource utilization in virtual machines
Proceedings of the 8th ACM international conference on Autonomic computing
Gossip-based resource allocation for green computing in large clouds
Proceedings of the 7th International Conference on Network and Services Management
Automated simulation-based capacity planning for enterprise data fabrics
Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques
Statistical inference of software performance models for parametric performance completions
QoSA'10 Proceedings of the 6th international conference on Quality of Software Architectures: research into Practice - Reality and Gaps
Efficient experiment selection in automated software performance evaluations
EPEW'11 Proceedings of the 8th European conference on Computer Performance Engineering
Resource-aware adaptive scheduling for mapreduce clusters
Middleware'11 Proceedings of the 12th ACM/IFIP/USENIX international conference on Middleware
Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
Journal of Parallel and Distributed Computing
Resource-aware adaptive scheduling for MapReduce clusters
Proceedings of the 12th International Middleware Conference
Algorithms for Web service selection with static and dynamic requirements
Service Oriented Computing and Applications
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
On the effects of omitting information exchange between autonomous resource management agents
AIMS'13 Proceedings of the 7th IFIP WG 6.6 international conference on Autonomous Infrastructure, Management, and Security: emerging management mechanisms for the future internet - Volume 7943
Constructing performance model of JMS middleware platform
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Managing the resources in a large Web serving system requires knowledge of the resource needs for service request-s of various kinds, and these needs may change over time. Assessing resource needs is commonly performed using techniques such as offline profiling, application instrumentation, and kernel-based instrumentation. Little attention has been given to the dynamic estimation of dynamic resource needs, relying only on external and high-level measurements such as overall resource utilization and request rates. We consider the problem of dynamically estimating dynamic CPU demands of multiple kinds of requests using CPU utilization and throughput measurements. We formulate the problem as a linear regression problem and obtain its basic solution. However, in practice one is faced with issues such as insignificant flows, collinear flows, space and temporal variations, and background noise. In order to deal with such issues, we present several mechanisms such as data aging, flow rejection, flow combining, noise reduction, and smoothing. We implemented these techniques in a Work Profiler component that we delivered as part of a broader system management product. We present experimental results from using this component in scenarios inspired by real-world usage of that product; our technique produces estimates that are roughly within a factor of 2 of the right answer, for the request flows that draw significant CPU power.