ADMin: Adaptive monitoring dissemination for the Internet of Things

Demetris Trihinas, George Pallis, Marios D. Dikaiakos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Citations (Scopus)


As more knowledge is vastly added to the devices fuelling the Internet of Things (IoT) energy efficiency and real-time data processing are great challenges that must be tackled. In this paper, we introduce ADMin, a low-cost IoT framework that reduces on device energy consumption and the volume of data disseminated across the network. This is achieved by efficiently adapting the rate at which IoT devices disseminate monitoring streams based on run-time knowledge of the stream evolution, variability and seasonal behavior. Rather than transmitting the entire stream, ADMin favors sending updates for its estimation model from which values can be inferred, triggering dissemination only when shifts in the stream evolution are detected. Results on real-life testbeds, show that ADMin is able to reduce energy consumption by at least 83%, data volume by 71%, shift detection delays by 61% while maintaining accuracy above 91% in comparison to other IoT frameworks.

Original languageEnglish
Title of host publicationINFOCOM 2017 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509053360
Publication statusPublished - 2 Oct 2017
Event2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States
Duration: 1 May 20174 May 2017

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/TerritoryUnited States


Dive into the research topics of 'ADMin: Adaptive monitoring dissemination for the Internet of Things'. Together they form a unique fingerprint.

Cite this