Cognitive management framework for fog computing in IOT case study: Traffic control system

Mostafa, Mostafa Abdel Azim; Mohammad, Ahmad Mohammad Khater

doi:10.1109/icitech.2017.8079962

Cited by 6 publications

(1 citation statement)

References 9 publications

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“…We are taking into consideration the challenges and demands for meeting real-time system requirements, guaranteeing large scale system network stability, and a lightweight management protocol. These solutions will be useful in scenarios such as traffic management in smart cities [1], smart greenhouses in agriculture [2,3], intelligent fire alarms in smart homes [4], for instance. The key contributions of this paper in-clude:…”

Section: Introductionmentioning

confidence: 99%

Autonomic Management of Power Consumption with IoT and Fog Computing

Sampaio,

Koch,

Westphall

et al. 2021

Preprint

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We introduce a system for Autonomic Management of Power Consumption in setups that involve Internet of Things (IoT) and Fog Computing. The Central IoT (CIoT) is a Fog Computing based solution to provide advanced orchestration mechanisms to manage dynamic duty cycles for extra energy savings. The solution works by adjusting Home (H) and Away (A) cycles based on contextual information, like environmental conditions, user behavior, behavior variation, regulations on energy and network resources utilization, among others. Performance analysis through a proof of concept present average energy savings of 58.4%, reaching up to 61.51% when augmenting with a scheduling system and variable long sleep cycles (LS). However, there is no linear relation increasing LS time and more savings. The significance of this research is to promote autonomic management as a solution to develop more energy efficient buildings and smarter cities, towards sustainable goals.

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