Static scheduling in clouds Henzinger, Thomas A ; https://orcid.org/0000−0002−2985−7724 Singh, Anmol Singh, Vasu Wies, Thomas Zufferey, Damien ; https://orcid.org/0000-0002-3197-8736 ddc:000 ddc:005 Cloud computing aims to give users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. We present a new job execution environment Flextic that exploits scal- able static scheduling techniques to provide the user with a flexible pricing model, such as a tradeoff between dif- ferent degrees of execution speed and execution price, and at the same time, reduce scheduling overhead for the cloud provider. We have evaluated a prototype of Flextic on Amazon EC2 and compared it against Hadoop. For various data parallel jobs from machine learning, im- age processing, and gene sequencing that we considered, Flextic has low scheduling overhead and reduces job du- ration by up to 15% compared to Hadoop, a dynamic cloud scheduler. USENIX 2011 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://research-explorer.ista.ac.at/record/3302 https://research-explorer.ista.ac.at/download/3302/5333 Henzinger TA, Singh A, Singh V, Wies T, Zufferey D. Static scheduling in clouds. In: USENIX; 2011:1-6. eng info:eu-repo/semantics/openAccess