Retrieving Monitoring and Accounting Information from Constrained Devices in Internet-of-Things Applications
Mazhelis, O., Waldburger, M., Machado, G. S., Stiller, B., & Tyrväinen, P. (2013). Retrieving Monitoring and Accounting Information from Constrained Devices in Internet-of-Things Applications. In G. Doyen, M. Waldburger, P. Celeda, A. Sperotto, & B. Stiller (Eds.), Emerging Management Mechanisms for the Future Internet (pp. 136-147). Springer. Lecture Notes in Computer Science, 7943. https://doi.org/10.1007/978-3-642-38998-6_17
Julkaistu sarjassa
Lecture Notes in Computer ScienceTekijät
Toimittajat
Päivämäärä
2013Tekijänoikeudet
© IFIP International Federation for Information Processing 2013. This is a final draft version of an article whose final and definitive form has been published by Springer. Published in this repository with the kind permission of the publisher.
Internet-of-Things (IoT) is envisioned to provide connectivity
to a vast number of sensing or actuating devices with limited computational
and communication capabilities. For the organizations that
manage these constrained devices, the monitoring of each device’s operational
status and performance level as well as the accounting of their resource
usage are of great importance. However, monitoring and accounting
support is lacking in today’s IoT platforms. Hence, this paper studies
the applicability of the Constrained Application Protocol (CoAP), a
lightweight transfer protocol under development by IETF, for efficiently
retrieving monitoring and accounting data from constrained devices. On
the infrastructure side, the developed prototype relies on using standard
building blocks offered by the AMAAIS project in order to collect,
pre-process, distribute, and persistently store monitoring and accounting
information. Necessary on-device and infrastructure components are
prototypically implemented and empirically evaluated in a realistic simulation
environment. Experiment results indicate that CoAP is suited
for efficiently transferring monitoring and accounting data, both due to
a small energy footprint and a memory-wise compact implementation.
...
Julkaisija
SpringerEmojulkaisun ISBN
978-3-642-38998-6Konferenssi
International Conference on Autonomous Infrastructure, Management, and SecurityKuuluu julkaisuun
Emerging Management Mechanisms for the Future InternetISSN Hae Julkaisufoorumista
0302-9743Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/23027342
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Internet-of-things market, value networks, and business models : state of the art report
Okkonen, Hanna; Mazhelis, Oleksiy; Ahokangas, Petri; Pussinen, Pasi; Rajahonka, Mervi; Siuruainen, Riikka; Leminen, Seppo; Shveykovskiy, Alexey; Myllykoski, Jenni; Warma, Henna (University of Jyväskylä, Department of Computer Science and Information Systems, 2013) -
A gap analysis of Internet-of-Things platforms
Mineraud, Julien; Mazhelis, Oleksiy; Su, Xiang; Tarkoma, Sasu (Elsevier BV, 2016)We are experiencing an abundance of Internet-of-Things (IoT) middleware solutions that provide connectivity for sensors and actuators to the Internet. To gain a widespread adoption, these middleware solutions, referred to ... -
How do startups develop internet-of-things systems : a multiple exploratory case study
Duc, Anh Nguyen; Khalid, Khan; Lønnestad, Tor; Bajwa, Sohaib Shahid; Wang, Xiaofeng; Abrahamsson, Pekka (IEEE, 2019)Internet-of-Things applications are not only the new opportunity for digital businesses but also a major driving force for the modification and creation of software systems in all industries and businesses. Compared to ... -
HALE-IoT : HArdening LEgacy Internet-of-Things devices by retrofitting defensive firmware modifications and implants
Carrillo-Mondejar, J.; Turtiainen, Hannu; Costin, Andrei; Martinez, J.L.; Suarez-Tangil, G. (IEEE, 2022)Internet-Of-Things (IoT) devices and their firmware are notorious for their lifelong vulnerabilities. As device infection increases, vendors also fail to release patches at a competitive pace. Despite security in IoT being ... -
Communication-Efficient Federated Learning in Channel Constrained Internet of Things
Hu, Tao; Zhang, Xinran; Chang, Zheng; Hu, Fengye; Hämäläinen, Timo (IEEE, 2022)Federated learning (FL) is able to utilize the computing capability and maintain the privacy of the end devices by collecting and aggregating the locally trained learning model parameters while keeping the local personal ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.