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2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) (2017)
Atlanta, Georgia, USA
June 5, 2017 to June 8, 2017
ISSN: 1063-6927
ISBN: 978-1-5386-1792-2
pp: 1063-1073
Calvin is an IoT framework for application development, deployment and execution in heterogeneous environments, that includes clouds, edge resources, and embedded or constrained resources. Inside Calvin, all the distributed resources are viewed as one environment by the application. The framework provides multi-tenancy and simplifies development of IoT applications, which are represented using a dataflow of application components (named actors) and their communication. The idea behind Calvin poses similarity with the serverless architecture and can be seen as Actor as a Service instead of Function as a Service. This makes Calvin very powerful as it does not only scale actors quickly but also provides an easy actor migration capability. In this work, we propose Calvin Constrained, an extension to the Calvin framework to cover resource-constrained devices. Due to limited memory and processing power of embedded devices, the constrained side of the framework can only support a limited subset of the Calvin features. The current implementation of Calvin Constrained supports actors implemented in C as well as Python, where the support for Python actors is enabled by using MicroPython as a statically allocated library, by this we enable the automatic management of state variables and enhance code re-usability. As would be expected, Python-coded actors demand more resources over C-coded ones. We show that the extra resources needed are manageable on current off-the-shelve micro-controller-equipped devices when using the Calvin framework.
Runtime, Temperature measurement, Frequency measurement, Sensors, Cloud computing, Actuators, Ports (Computers)

A. Mehta, R. Baddour, F. Svensson, H. Gustafsson and E. Elmroth, "Calvin Constrained — A Framework for IoT Applications in Heterogeneous Environments," 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, Georgia, USA, 2017, pp. 1063-1073.
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