An important aspect of realizations of the Internet of Things containing sophisticated sensors and actuators is their integration with the Cloud, by the use of a middleware. This integration results in handling streams of data produced by sensors as well as streams sent back to actuators. In cases for which both large streams and a short reaction time are required, a special real-time oriented approach is necessary to design and build an interconnecting middleware. This paper proposes a hybrid low-cost, low-power middleware architecture for handling and processing of sensor related data streams. It is based on two microprocessor boards interconnected by high speed USB link. Variants including three embedded hardware implementations of the proposed architecture, two software realizations (single and multithread ones), and two process scheduling algorithms have been examined to evaluate their real-time performances. Series of experiments have been performed in order to measure closed loop control times and sensor data streams achievable in practice. An outcome is presented and discussed in detail. Obtained results confirm that the proposed architecture can be applied as middleware to integrate such elements of Internet of Things as robots and similarly time-constrained systems with the Cloud. The results can serve as reference point in research and development of real-time middleware solutions.
Abstract:We describe a framework for very lightweight custom remote procedure call protocol. This framework uses variadic templates and other language features introduced in C++11 to furnish effective, cache friendly and hence energy efficient implementation. Our approach provides also type safety and modularity of RPC handlers. Such a solution is useful both in industrial and home automation applications with possibly severe limitations on processing power and network bandwidth (like using GSM in remote areas). Here, the latter constraint may apply to systems implemented on both ends of spectrum: low end embedded systems as well as high end multicore server systems, but under heavy load.
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