An Intelligent Scheme for Uncertainty Management of Data Synopses Management in Pervasive Computing Applications
Kostas Kolomvatsos

TL;DR
This paper introduces an uncertainty-aware fuzzy logic model for efficient data synopsis exchange in IoT and edge computing, reducing unnecessary communication while maintaining timely updates for decision-making.
Contribution
It proposes a novel fuzzy logic-based mechanism that delays data synopsis exchange unless significant changes are detected, optimizing network communication in pervasive computing.
Findings
Reduces message exchanges by filtering insignificant data changes.
Maintains timely updates for significant data fluctuations.
Enhances network efficiency in IoT and edge environments.
Abstract
Pervasive computing applications deal with the incorporation of intelligent components around end users to facilitate their activities. Such applications can be provided upon the vast infrastructures of Internet of Things (IoT) and Edge Computing (EC). IoT devices collect ambient data transferring them towards the EC and Cloud for further processing. EC nodes could become the hosts of distributed datasets where various processing activities take place. The future of EC involves numerous nodes interacting with the IoT devices and themselves in a cooperative manner to realize the desired processing. A critical issue for concluding this cooperative approach is the exchange of data synopses to have EC nodes informed about the data present in their peers. Such knowledge will be useful for decision making related to the execution of processing activities. In this paper, we propose n…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Cloud Computing and Resource Management · Data Stream Mining Techniques
