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Smart city article details
| Title | Reduce Energy Consumption By Intelligent Decision-Making In A Fog-Cloud Environment |
|---|---|
| ID_Doc | 44748 |
| Authors | Ghaleb Abdkhaleq M.H.; Zamanifar K. |
| Year | 2023 |
| Published | Wireless Personal Communications |
| DOI | http://dx.doi.org/10.1007/s11277-023-10707-7 |
| Abstract | Numerous Internet of Things (IoT) devices, such as drones, robots, smart cities, wearables, and many others, are now widespread in our society and indispensable to our daily lives. Cloud computing is no longer adequate to meet the requirements of the IoT. Fog computing has emerged to address this issue by bringing computing resources closer to the point of use. The heterogeneity of devices, application types, and application priority deployed in the network are the factors that increase the complexity of the fog-cloud environment. Many fog nodes are expected to be deployed in the network due to the increasing number of IoT devices. Inefficient use of fog resources increases energy consumption, which increases the cost and releases more carbon dioxide into the atmosphere, harming the planet. Therefore, it is essential to develop new technologies that can determine how to consume the least amount of energy whereas ensuring that application delay is not violated by considering the factors in a natural fog-cloud computing environment. This research proposes an applications services placement strategy that reduces the total energy consumption and guarantees that the application's delay is not violated, taking into account the factors of the fog-cloud computing environment. Decentralized solutions are used for time-sensitive applications, while centralized solutions are used for applications with time tolerance. iFogsim simulator was used to perform the simulation. As seen from the outcomes, the proposed approach intelligently exploits nodes' specifications by efficiently running applications' services within the response time and with minimal energy consumption. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
| Author Keywords | Energy consumption; Fog computing; Intelligent decision making; Internet of Things (IoT); Service placement |
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