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A Machine-to-Machine protocol benchmark for eHealth applications - Use case: Respiratory rehabilitation
Alejandro Talaminos-Barroso1, Miguel A Estudillo-Valderrama2, Laura M Roa2
1Grupo de Ingeniería Biomédica, Universidad de Sevilla, Spain.
Computer Methods and Programs in Biomedicine
|April 17, 2016
Summary
Selecting the right Machine-to-Machine (M2M) communication protocols is crucial for eHealth applications. A new benchmarking tool, the Distributed Computing Framework (DFC), objectively evaluates M2M protocols for eHealth solutions.
Area of Science:
- Computer Science
- Biomedical Engineering
- Telecommunications
Background:
- Machine-to-Machine (M2M) communication is fundamental to the Internet of Things (IoT) and eHealth.
- The proliferation of M2M protocols complicates the selection for eHealth applications.
Purpose of the Study:
- To develop a tool for objective benchmarking of M2M protocols for eHealth.
- To validate this tool using a respiratory rehabilitation use case.
Main Methods:
- A software tool, Distributed Computing Framework (DFC), was developed for benchmarking.
- DFC supports various M2M protocols and performance metrics across distributed environments.
Main Results:
- Six M2M protocols (DDS, MQTT, CoAP, JMS, AMQP, XMPP) were benchmarked.
- Performance metrics included CPU usage, memory, bandwidth, latency, and jitter.
- The tool was validated for home-based and ambulatory respiratory rehabilitation scenarios for COPD patients.
Conclusions:
- Benchmark results aid eHealth developers in selecting appropriate M2M technologies.
- The DFC framework provides a robust platform for deploying specific benchmark tests.
