Efficient Monitoring of CPS and IoT Systems: A Deployment Guide for Empirical Evaluations
Paper in proceeding, 2024

As the digitalization of our world continues, the volume of data produced escalates rapidly. Communication often constitutes the most energy-intensive aspect of applications, making it a prime target for optimization. This paper studies the efficiency and precision of monitoring Cyber-Physical Systems (CPS) and Internet of Things (IoT) devices in real experimental deployment scenarios. We evaluate in this work the performance of six different monitoring algorithms concerning CPU utilization, memory usage, network traffic, energy consumption, and monitoring accuracy. Our experimental setup is a network consisting of 38 Raspberry Pis connected to a single host computer via Ethernet. Monitoring was conducted both on the devices themselves and on the host computer, which served as the metrics-receiving stack. We offer here a comprehensive deployment guide serving as a valuable resource for reproducing similar monitoring experiments on IoT devices. Additionally, our own empirical evaluation indicate notable differences among the tested algorithms, highlighting the importance of application constraints on the selection of a monitoring algorithm. Seeking those real-world experiments aim to add substantial value to existing surveys by offering deeper insights, practical findings and empirical evidence.

adaptive filtering

LMS

PLA

static filter

adaptive sampling

monitoring

SIP

CPS

IoT

Author

Jan Korner

Student at Chalmers

Samuel Bach

Student at Chalmers

Albin Karlsson

Student at Chalmers

Linus Sundkvist

Student at Chalmers

Romaric Duvignau

Network and Systems

2024 13th Mediterranean Conference on Embedded Computing, MECO 2024


9798350387568 (ISBN)

13th Mediterranean Conference on Embedded Computing, MECO 2024
Budva, Montenegro,

Subject Categories

Computer Science

DOI

10.1109/MECO62516.2024.10577823

More information

Latest update

8/1/2024 5