Analysis of the increase and decrease algorithms for congestion avoidance in computer networks
Computer Networks and ISDN Systems
Cluster-based scalable network services
Proceedings of the sixteenth ACM symposium on Operating systems principles
Efficient network and I/O throttling for fine-grain cycle stealing
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Feedback Control of Computing Systems
Feedback Control of Computing Systems
A method for transparent admission control and request scheduling in e-commerce web sites
Proceedings of the 13th international conference on World Wide Web
Cataclysm: policing extreme overloads in internet applications
WWW '05 Proceedings of the 14th international conference on World Wide Web
Web servers under overload: How scheduling can help
ACM Transactions on Internet Technology (TOIT)
Adaptive overload control for busy internet servers
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Connection scheduling in web servers
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
How are Real Grids Used? The Analysis of Four Grid Traces and Its Implications
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Trace-based evaluation of job runtime and queue wait time predictions in grids
Proceedings of the 18th ACM international symposium on High performance distributed computing
Scaling up workflow-based applications
Journal of Computer and System Sciences
Performance analysis of dynamic workflow scheduling in multicluster grids
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
IEEE Internet Computing
A survey on TCP-friendly congestion control
IEEE Network: The Magazine of Global Internetworking
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Multi-cluster grids are widely employed to execute workloads consisting of compute- and data-intensive applications in both research and production environments. Such workloads, especially when they are bursty, may stress shared system resources, to the point where overload conditions occur. Overloads can severely degrade the system performance and responsiveness, potentially causing user dissatisfaction and perhaps even revenue loss. However, the characteristics of multi-cluster grids, such as their complexity and heterogeneity, raise numerous nontrivial issues while controlling overload in such systems. In this work we present an extensive performance evaluation of overload control in multi-cluster grids. We adapt a dynamic throttling mechanism that enforces a concurrency limit indicating the maximum number of tasks running concurrently for every application. Using diverse workloads we evaluate several throttling mechanisms including our dynamic mechanism in our DAS-3 multi-cluster grid. Our results show that throttling can be used for effective overload control in multi-cluster grids, and in particular, that our dynamic technique improves the application performance by as much as 50% while also improving the system responsiveness by up to 80%.