Modeling Dew Computing in DISSECT-CF-Fog

Fog computing provides an effective solution to various problems by extending the cloud’s functionality to typically more limited computing units closer to user devices. Fog computing can provide a higher level of user experience due to its geographic and network topology location and distribution....

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Márkus András
Bíró Máté
Skala Karolj
Šojat Zorislav
Kertész Attila
Dokumentumtípus: Cikk
Megjelent: 2022
Sorozat:APPLIED SCIENCES-BASEL 12 No. 17
Tárgyszavak:
doi:10.3390/app12178809

mtmt:33079396
Online Access:http://publicatio.bibl.u-szeged.hu/25011
Leíró adatok
Tartalmi kivonat:Fog computing provides an effective solution to various problems by extending the cloud’s functionality to typically more limited computing units closer to user devices. Fog computing can provide a higher level of user experience due to its geographic and network topology location and distribution. IoT services also need to be managed seamlessly to ensure adequate QoS (due to the mobility of devices or the temporary periods without an internet connection). Such domains are combined under the auspices of Dew computing, as in critical cases, extending an IoT service to the end user’s device is a feasible task. Such scenarios can hardly be investigated at a large scale due to the lack of dedicated simulation environments. In this paper, we present an extension of the DISSECT-CF-Fog simulator with a Dew computing model, to enable the simulation of IoT-Dew-Fog systems in a cost-effective manner. In particular, we focus on service migration options for mobile devices and cases with temporary internet access limitations. Finally, we performed measurements of real-world use cases with the extended simulator as an evaluation. Our simulation results show that the proposed proactive strategy reduces the processing time of IoT data, exploiting an IoT-Dew-Fog environment.
Terjedelem/Fizikai jellemzők:Terjedelem: 12 p.-Azonosító: 8809
ISSN:2076-3417