A novel fog-based multi-level energy-efficient framework for IoT-enabled smart environments

Muhammad Ammad, Munam Ali Shah, Saif Ul Islam, Carsten Maple, Abdullah A. Alaulamie, Joel J. P. C. Rodrigues, Shafaq Mussadiq, Usman Tariq
2020 IEEE Access  
The Internet of Things (IoT) has emerged as a promising paradigm to enhance the living standard of human life by employing varied smart devices including smart phones, smart watches, sensors, on-board units and other networking equipment. However, these devices consume a considerable amount of energy to perform their operations that has a significant impact on the environment, product cost and life of the device. Given this fact, energy-efficient solutions for smart environments have gained
more » ... nts have gained great attention from researchers and the industrial community. In this context, a novel fog-based multi-level energyefficient framework for IoT-enabled smart environments has been proposed. To achieve this, the proposed framework adds additional two layers in the existing IoT-fog-cloud architecture -sensors-based energyefficient hardware layer and policy layer, to monitor the energy consumption and to enable the energy-aware decision making. Initially, the main sources of energy consumption in an IoT-enabled smart environment are identified. Further, the energy requirements of a device to perform a specific task are estimated. Moreover, the alternative devices to perform the same task using less energy are searched out. Finally, a device or a set of devices, to process the job consuming lower energy while ensuring the job requirements, is selected. To validate the proposed framework, four case studies are considered -smart parking, smart hospital specifically ICU, smart agriculture and smart airport. Simulations are conducted using iFogsim toolkit and results show that a significant amount of energy can be conserved by employing the proposed framework. INDEX TERMS Energy efficiency, IoT, fog, cloud, energy constraint devices, smart environment.
doi:10.1109/access.2020.3010157 fatcat:6yisj6e2ojafjnuzsyct2sswmy