dc.creator | Kolomvatsos K. | en |
dc.date.accessioned | 2023-01-31T08:43:42Z | |
dc.date.available | 2023-01-31T08:43:42Z | |
dc.date.issued | 2020 | |
dc.identifier | 10.1109/HPCC-SmartCity-DSS50907.2020.00164 | |
dc.identifier.isbn | 9781728176499 | |
dc.identifier.uri | http://hdl.handle.net/11615/75005 | |
dc.description.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 the 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 an uncertainty driven model for the exchange of data synopses. We argue that EC nodes should delay the exchange of synopses especially when no significant differences with historical values are present. Our mechanism adopts a Fuzzy Logic (FL) system to decide when there is a significant difference with the previous reported synopses to decide the exchange of the new one. Our scheme is capable of alleviating the network from numerous messages retrieved even for low fluctuations in synopses. We analytically describe our model and evaluate it through a large set of experiments. Our experimental evaluation targets to detect the efficiency of the approach based on the elimination of unnecessary messages while keeping immediately informed peer nodes for significant statistical changes in the distributed datasets. © 2020 IEEE. | en |
dc.language.iso | en | en |
dc.source | Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020 | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102843531&doi=10.1109%2fHPCC-SmartCity-DSS50907.2020.00164&partnerID=40&md5=9c9b1914d980d595a173282d30ef83c1 | |
dc.subject | Data communication systems | en |
dc.subject | Data Science | en |
dc.subject | Decision making | en |
dc.subject | Fuzzy logic | en |
dc.subject | Smart city | en |
dc.subject | Ubiquitous computing | en |
dc.subject | Critical issues | en |
dc.subject | Data transferring | en |
dc.subject | Experimental evaluation | en |
dc.subject | Intelligent components | en |
dc.subject | Internet of thing (IOT) | en |
dc.subject | Pervasive applications | en |
dc.subject | Pervasive computing applications | en |
dc.subject | Processing activity | en |
dc.subject | Internet of things | en |
dc.subject | Institute of Electrical and Electronics Engineers Inc. | en |
dc.title | A Proactive Uncertainty Driven Model for Data Synopses Management in Pervasive Applications | en |
dc.type | conferenceItem | en |