Dynamic voltage and frequency scaling (DVFS) is a means to adjust the computing capacity and power consumption\nof computing systems to the application demands. DVFS is generally useful to provide a compromise between\ncomputing demands and power consumption, especially in the areas of resource-constrained computing systems.\nMany modern processors support some form of DVFS.\nIn this article, we focus on the development of an execution framework that provides lightweight DVFS support for\nreactive stream processing systems (RSPS). RSPs are a common form of embedded control systems, operating in\ndirect response to inputs from their environment. At the execution framework, we focus on support for many-core\nscheduling for parallel execution of concurrent programs. We provide a DVFS strategy for RSPs that is simple and\nlightweight, to be used for dynamic adaptation of the power consumption at runtime. The simplicity of the DVFS\nstrategy became possible by the sole focus on the application domain of RSPs. The presented DVFS strategy does not\nrequire specific assumptions about the message arrival rate or the underlying scheduling method.\nWhile DVFS is a very active field, in contrast to most existing research, our approach works also for platforms like\nmany-core processors, where the power settings typically cannot be controlled individually for each computational\nunit. We also support dynamic scheduling with variable workload. While many research results are provided with\nsimulators, in our approach, we present a parallel execution framework with experiments conducted on real\nhardware, using the single-chip cloud computer many-core processor. The results of our experimental evaluation\nconfirm that our simple DVFS strategy provides potential for significant energy saving on RSPs.
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