Smart City Gnosys
Smart city article details
| Title | A Fog-Cluster Based Load-Balancing Technique |
|---|---|
| ID_Doc | 1722 |
| Authors | Singh P.; Kaur R.; Rashid J.; Juneja S.; Dhiman G.; Kim J.; Ouaissa M. |
| Year | 2022 |
| Published | Sustainability (Switzerland), 14, 13 |
| DOI | http://dx.doi.org/10.3390/su14137961 |
| Abstract | The Internet of Things has recently been a popular topic of study for developing smart homes and smart cities. Most IoT applications are very sensitive to delays, and IoT sensors provide a constant stream of data. The cloud-based IoT services that were first employed suffer from increased latency and inefficient resource use. Fog computing is used to address these issues by moving cloud services closer to the edge in a small-scale, dispersed fashion. Fog computing is quickly gaining popularity as an effective paradigm for providing customers with real-time processing, platforms, and software services. Real-time applications may be supported at a reduced operating cost using an integrated fog-cloud environment that minimizes resources and reduces delays. Load balancing is a critical problem in fog computing because it ensures that the dynamic load is distributed evenly across all fog nodes, avoiding the situation where some nodes are overloaded while others are underloaded. Numerous algorithms have been proposed to accomplish this goal. In this paper, a framework was proposed that contains three subsystems named user subsystem, cloud subsystem, and fog subsystem. The goal of the proposed framework is to decrease bandwidth costs while providing load balancing at the same time. To optimize the use of all the resources in the fog sub-system, a Fog-Cluster-Based Load-Balancing approach along with a refresh period was proposed. The simulation results show that “Fog-Cluster-Based Load Balancing” decreases energy consumption, the number of Virtual Machines (VMs) migrations, and the number of shutdown hosts compared with existing algorithms for the proposed framework. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
| Author Keywords | cloud computing; fog computing; load balancing |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
4114  | 0.946 | Mahdi R.M.; Hassan H.J.; Abdulsaheb G.M. | A Review Load Balancing Algorithms In Fog Computing | BIO Web of Conferences, 97 (2024) |
| 20661 | 0.909 | Beraldi R.; Canali C.; Lancellotti R.; Mattia G.P. | Distributed Load Balancing For Heterogeneous Fog Computing Infrastructures In Smart Cities | Pervasive and Mobile Computing, 67 (2020) |
| 26743 | 0.903 | Hazra A.; Rana P.; Adhikari M.; Amgoth T. | Fog Computing For Next-Generation Internet Of Things: Fundamental, State-Of-The-Art And Research Challenges | Computer Science Review, 48 (2023) |
| 3954 | 0.902 | Beraldi R.; Canali C.; Lancellotti R.; Mattia G.P. | A Random Walk Based Load Balancing Algorithm For Fog Computing | 2020 5th International Conference on Fog and Mobile Edge Computing, FMEC 2020 (2020) |
| 4182 | 0.9 | Kumar S.; Singh P.; Singh A. | A Review Of Optimized Computational Strategies For Iot: Cloud, Fog, And Edge Computing Approaches | Proceedings of 5th International Conference on Pervasive Computing and Social Networking, ICPCSN 2025 (2025) |
| 1522 | 0.899 | Shamsa Z.; Rezaee A.; Adabi S.; Rahimabadi A.M.; Rahmani A.M. | A Distributed Load Balancing Method For Iot/Fog/Cloud Environments With Volatile Resource Support | Cluster Computing, 27, 4 (2024) |
| 55549 | 0.899 | Alli A.A.; Alam M.M. | The Fog Cloud Of Things: A Survey On Concepts, Architecture, Standards, Tools, And Applications | Internet of Things (Netherlands), 9 (2020) |
| 7894 | 0.898 | Puttaswamy N.G.; Murthy A.N. | An Efficient Reconfigurable Workload Balancing Scheme For Fog Computing Network Using Internet Of Things Devices | International Journal of Electrical and Computer Engineering, 13, 6 (2023) |
| 14378 | 0.897 | Javaid N.; Butt A.A.; Latif K.; Rehman A. | Cloud And Fog Based Integrated Environment For Load Balancing Using Cuckoo Levy Distribution And Flower Pollination For Smart Homes | 2019 International Conference on Computer and Information Sciences, ICCIS 2019 (2019) |
| 40664 | 0.891 | Prasad C.R.; Sandeep Kumar V.; Rao P.R.; Kollem S.; Yalabaka S.; Samala S. | Optimization Of Task Offloading For Smart Cities Using Iot With Fog Computing- A Survey | 2022 International Conference on Signal and Information Processing, IConSIP 2022 (2022) |