Abstract
The evolution of fog computing plays a vital role in the field of computing paradigms. The fog computing alone cannot do all the processes so that to be interlinked with cloud computing. One of the significant drawbacks in the fog computing environment is performance degradation, which occurs due to fog device placement. The improper placement of fog nodes leads to delays concerning the execution and response time due to the fog application’s critical nature. So, the placement of fog devices plays a vital role in improving the Quality of the Service (QoS) to the user. The proposed method uses a machine learning technique to place the fog node. The paper evaluates the proposed approach using the iFogSim simulation environment and concludes that the proposed method has a better performance ranges from 15 to 50%.
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References
Sangeetha KS, Prakash P (2015) Big data and cloud: a survey. Artif Intell Evol Algorithms Eng Syst (Springer, India) 773–778
Prakash P, Darshaun K, Ganesh MV, Vasudha B (2017) Fog computing: issues, challenges and future directions. Int J Electr Comput Eng (IJECE) 7(6):3669–3673
Yuan X, He Y, Fang Q, Tong X, Du C, Ding Y (2017) An improved fast search and find of density peaks-based fog node location of fog computing system. In: 2017 IEEE international conference on internet of things (iThings) and IEEE green computing and communications (GreenCom) and IEEE cyber, physical and social computing (CPSCom) and IEEE smart data (SmartData), Exeter, pp 635–642. https://doi.org/10.1109/iThings-GreenCom-CPSCom-SmartData.2017.100
Sarkar S, Chatterjee S, Misra S (2018) Assessment of the suitability of fog computing in the context of internet of things. IEEE Trans Cloud Comput 6(1):46–59. https://doi.org/10.1109/TCC.2015.2485206
Aazam M, Huh E (2015) Dynamic resource provisioning through Fog micro datacenter. In: 2015 IEEE international conference on pervasive computing and communication workshops (PerCom workshops), St. Louis, MO, pp 105–110. https://doi.org/10.1109/PERCOMW.2015.7134002
Mayer R, Graser L, Gupta H, Saurez E, Ramachandran U (2017) EmuFog: extensible and scalable emulation of large-scale fog computing infrastructures. In: 2017 IEEE fog world congress (FWC), Santa Clara, CA, pp 1–6. https://doi.org/10.1109/FWC.2017.8368525
Aazam M, Huh E (2014) Fog computing and smart gateway based communication for cloud of things. In: 2014 international conference on future internet of things and cloud, Barcelona, pp 464–470. https://doi.org/10.1109/FiCloud.2014.83
Mahmud R, Srirama SN, Ramamohanarao K, Buyya R (2019) Quality of experience (QoE)-aware placement of applications in fog computing environments. J Parallel Distrib Comput 132:190–203
Taneja M, Davy A (2016) Resource aware placement of data analytics platform in fog computing. Procedia Comput Sci 97:153–156. ISSN 1877–0509. https://doi.org/10.1016/j.procs.2016.08.295
Sun Y, Zhang N (2017) A resource-sharing model based on a repeated game in fog computing. Saudi J Biol Sci 24(3):687–694. ISSN 1319–562X. https://doi.org/10.1016/j.sjbs.2017.01.043
Gupta H, Vahid Dastjerdi A, Ghosh SK, Buyya R (2017) iFogSim: a toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Softw Pract Experience 47(9):1275–1296
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Prakash, P., Sakthivel, V. (2022). Efficient Node Placement Approach in Fog Computing Environment Using Machine Learning Model. In: Kumar, A., Mozar, S. (eds) ICCCE 2021. Lecture Notes in Electrical Engineering, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-16-7985-8_31
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DOI: https://doi.org/10.1007/978-981-16-7985-8_31
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