Application Performance Monitoring in Wireless Sensor Networks

Fabien Graf

Fabian Graf is doing his PhD on “Application Performance Monitoring in Wireless Sensor Networks” as part of the OpenSwarm project.

He works at Siemens in Erlangen and his PhD is supervised by Thomas Watteyne (Inria) and Michael Villnow (Siemens).

Wireless Sensor Systems (WSNs) are widely deployed in industrial environments to ensure the flawless operation of all entities in a factory. It is therefore crucial to install a WSN that the user can count on. In fact, the overwhelming majority of people talks about reliability when asked for the most important features in a WSN [1]. Because the sensors inside a WSN are usually extremely limited in terms of size and cost, they only offer a limited amount of battery lifetime. This makes it understandable that vendors tend to completely neglect Application Performance Monitoring (APM) capabilities in such constrained devices. Isn’t this inconsistent when recalling that reliability is the most important feature from a customer’s point of view? – Yes, it is! 


The IEEE802.15.4e standard [2] has proven to be a very reliable and robust basis for industrial IoT networks [3]. We want to find methods to introduce APM in such constrained systems while keeping the impact on the performance in terms of latency, storage, and power consumption as low as possible. A common method is to periodically collect performance metrics [4] in fixed time intervals and deliver them to the user.  This concept is implemented in different state-of-the-art applications under various names, such as “health reports” [5], “snapshots” [6] or “heartbeats” [7]. In our research, we evaluate these approaches and develop new strategies that optimize the balance between the verbosity of APM and the benefits from the visibility that it brings. 


Once the user is equipped with a powerful monitoring tool of their WSN, they have the opportunity to detect crucial trends, find root causes of failures, or even foresee critical events. Having full visibility of the network and its “health condition” is an essential feature when it comes to WSNs with moving elements in a dynamic sensor swarm. Since APM is a topic which is unsatisfactorily addressed in the research community until now, we work on closing this gap with our contributions to the OpenSwarm project. 


Figure article

[1] M. Hatler, „Wireless Sensor Networks: Expanding Opportunities for Industrial IoT,“ ISA’s Flagship Publications, 2017. [Online]. Available: 

[2] „802.15.4e-2012: IEEE Standard for Local and Metropolitan Area Networks–Part 15.4: Low-Rate Wireless Personal Area Networks (LRWPANs) Amendment 1: MAC sublayer,“ IEEE Std., 2012.  

[3] W. Thomas, J. Weiss, L. Doherty und J. Simon, „Industrial IEEE802.15.4e networks: Performance and Trade-offs,“ Proceedings of IEEE International Conference on Communications (ICC), pp. 8-12, 2015.  

[4] D. Yuan, S. Kanhere und M. Hollick, „Instrumenting Wireless Sensor Networks : A Survey on the Metrics That Matter,“ Pervasive and Mobile Computing, Bd. 37, pp. 45-62, 2017.  

[5] T. Watteyne, L. Doherty und K. Pister, „Technical Overview of SmartMesh IP,“ Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, 2013.  

[6] M. Khomenko und O. Velihorskyi, „The Use of Percepio Tracealyzer for the Development of FreeRTOS-based Applications,“ II International Scientific and Practical Conference Theoretical and Applied Aspects of Device Development on Microcontrollers and FPGAs (MC&FPGA), Kharkiv, Ukraine, pp. 26-29, 2020.  

[7] Memfault Inc., „Memfault,“ [Online]. Available: