Actors: a model of concurrent computation in distributed systems
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UCC '11 Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing
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Accurate Resource Prediction for Hybrid IaaS Clouds Using Workload-Tailored Elastic Compute Units
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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We present the Cloud Operating System (COS), a middleware framework to support autonomous workload elasticity and scalability based on application-level migration as a reconfiguration strategy. While other scalable frameworks (e.g., MapReduce or Google App Engine) force application developers to write programs following specific APIs, COS provides scalability in a general-purpose programming framework based on an actor-oriented programming language. When all executing VMs are highly utilized, COS scales a workload up by migrating mobile actors over to newly dynamically created VMs. When VM utilization drops, COS scales the workload down by consolidating actors and terminating idle VMs. Application-level migration is advantageous compared to VM migration especially in hybrid clouds in which migration costs over the Internet are critical to scale out the workloads. We demonstrate the general purpose programming approach using a tightly-coupled computation. We compare the performance of autonomous (i.e., COS-driven) versus ideal reconfiguration, as well as the impact of granularity of reconfiguration, i.e., VM migration versus application-level migration. Our results show promise for future fully automated cloud computing resource management systems that efficiently enable truly elastic and scalable general-purpose workloads.