Managing energy and server resources in hosting centers
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Energy conservation in heterogeneous server clusters
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Energy-Efficient Real-Time Heterogeneous Server Clusters
RTAS '06 Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium
Statistical QoS Guarantee and Energy-Efficiency in Web Server Clusters
ECRTS '07 Proceedings of the 19th Euromicro Conference on Real-Time Systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Energy-aware server provisioning and load dispatching for connection-intensive internet services
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Dynamic allocation in a self-scaling cluster database
Concurrency and Computation: Practice & Experience - Selection of Best Papers of the VLDB Data Management in Grids Workshop (VLDB DMG 2007)
A framework for dynamic adaptation of power-aware server clusters
Proceedings of the 2009 ACM symposium on Applied Computing
The GREEN-NET framework: Energy efficiency in large scale distributed systems
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems
Performance Evaluation and Benchmarking
Analysis of energy reduction on dynamic voltage scaling-enabled systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Scalability is a major concern of internet based applications. Access peaks that overload the application are a financial risk. Therefore, systems are built to scale. They are usually configured to be able to process peaks at any give moment. This can be very inefficient. Yet, there are various ways to improve efficiency. One reasonable approach is to scale applications according to their current workload. This requires the possibility to scale a system up and down. In this paper we present a scaling framework for Java applications. It allows not only autonomic scaling, but also migration of distributed applications. We will then show how energy efficiency can be increased by scaling applications. To present an example we have used our framework to autonomically scale a web server cluster.