New platform for IoT Application Management based on fog computing

Kalantary, S.; Akbari Torkestani, J.; Shahidinejad, A.

doi:10.22061/jecei.2023.9489.626

تعداد نشریات	13
تعداد شماره‌ها	238
تعداد مقالات	2,420
تعداد مشاهده مقاله	3,966,092
تعداد دریافت فایل اصل مقاله	2,876,669

	New platform for IoT Application Management based on fog computing
Journal of Electrical and Computer Engineering Innovations (JECEI)
دوره 11، شماره 2، مهر 2023، صفحه 399-408 اصل مقاله (738.52 K)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22061/jecei.2023.9489.626
نویسندگان
S. Kalantary¹؛ J. Akbari Torkestani^* ²؛ A. Shahidinejad³
¹Department of Computer Science, Qom branch, Islamic Azad University, Qom, Iran.
²Department of Computer Science, Arak Branch, Islamic Azad University, Arak, Iran.
³Department of Computer Science, Faculty of Engineering, Qom branch, Islamic Azad University, Qom, Iran.
تاریخ دریافت: 23 آذر 1401، تاریخ بازنگری: 10 اسفند 1401، تاریخ پذیرش: 20 اسفند 1401
چکیده
Background and Objectives: With the great growth of applications sensitive to latency, and efforts to reduce latency and cost and to improve the quality of service on the Internet of Things ecosystem, cloud computing and communication between things and the cloud are costly and inefficient; Therefore, fog computing has been proposed to prevent sending large volumes of data generated by things to cloud centers and, if possible, to process some requests. Today's advances in 5G networks and the Internet of Things show the benefits of fog computing more than ever before, so that services can be delivered with very little delay as resources and features of fog nodes approach the end user. Methods: Since the cloud-fog paradigm is a layered architecture, to reduce the overall delay, the fog layer is divided into two sub-layers in this paper, including super nodes and ordinary nodes in order to use the coverage of super peer networks to use the connections between fog nodes in addition to taking advantage of the features of that network and improving the performance of large-scale systems. It causes fog nodes to interact with each other in processing requests and fewer data will be sent to the cloud, resulting in a reduction in overall latency. To reduce the cost of bandwidth used among fog nodes, we have organized a sub-layer of super nodes in the form of a Perfect Difference Graph (PDG). The new platform proposed for aggregation of fog computing and Internet of Things (FOT) is called the P2P-based Fog supported Platform (PFP). Results: We evaluate the utility of our proposed method by applying ifogsim simulator and the results achieved are as follows: (1) power consumption parameter in our proposed method 24% and 38% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; (2) network usage parameter in our proposed method 26% and 32% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; (3) average response time parameter in our proposed method 17% and 58% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively; and (4) delay parameter in our proposed method 1% and 0.4% have improved compared to the structure three-layer fog computing architecture and without fog layer respectively. Conclusion: Numerical results obtained from the simulation show that the delay and cost parameters are significantly improved compared to the structure without fog layer and three-layer fog computing architecture. Also, the results show that increasing number of things has the same effect in all cases.
کلیدواژه‌ها
Internet of Things؛ Fog Computing؛ Perfect Difference Graph؛ Layered Architecture

مراجع
[1] Y. Hajjaji et al., “Big data and IoT-based applications in smart environments: A systematic review,” Compu. Sci. Rev., 39: 100318, 2021. [2] F. E. F. Samann et al., “IoT provisioning QoS based on cloud and fog computing,” J. App. Sci. Tech. Trends, 2(01): 29-40, 2021. [3] I. Lee, K. Lee, “The Internet of Things (IoT): Applications, investments, and challenges for enterprises,” Bus. Horiz., 58(4): 431-440, 2015. [4] T. Wang et al., “Coupling resource management based on fog computing in smart city systems,” J. Network Compu. Appl., 135: 11-19, 2019. [5] M. Etemadi et al., “Resource provisioning for IoT services in the fog computing environment: An autonomic approach,” Comput. Commun., 161: 109-131, 2020. [6] S. Kalantary et al., “Resource discovery in the Internet of Things integrated with fog computing using Markov learning model,” J. Supercompu., 77: 13806-13827, 2021. [7] M. Ghobaei et al., “Resource elasticity management using fuzzy controller based on threshold changes in the cloud computing environment,” Electron. Cyber Def., 8(3): 63-81, 2020. [8] A. Cenedese et al., “Padova smart city: An urban internet of things experimentation,” in Proc. IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, 2014. [9] H. A. Khattak et al., “Toward integrating vehicular clouds with IoT for smart city services,” IEEE Network, 33(2): 65-71, 2019. [10] P. G. V. Naranjo et al., “FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments,” J. Parallel Distrib. Comput., 132: 274-283, 2019. [11] C. Thota et al., “Centralized fog computing security platform for IoT and cloud in healthcare system, in Fog computing: Breakthroughs in research and practice,” IGI global: 365-378, 2018. [12] D. Bruneo et al., “Stack4Things as a fog computing platform for Smart City applications,” in 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2016. [13] J. Grover et al., “Real-time vanet applications using fog computing,” in Proc. First International Conference on Smart System, Innovations and Computing, 2018. [14] F. J. Ferrández-Pastor et al., “Deployment of IoT edge and fog computing technologies to develop smart building services,” Sustainability, 10(11): 3832, 2018. [15] B. Tang et al., “A hierarchical distributed fog computing architecture for big data analysis in smart cities,” in Proc. the ASE BigData & SocialInformatics: 1-6, 2015. [16] K. Skala et al., “Scalable distributed computing hierarchy: Cloud, fog and dew computing,” Open J. Cloud Comput. (OJCC), 2(1): 16-24, 2015. [17] C. Prazeres, M. Serrano, “Soft-iot: Self-organizing fog of things,” in Proc. 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA), 2016. [18] R. Tandon, P. Gupta, “Optimizing smart parking system by using fog computing,” in Proc. International Conference on Advances in Computing and Data Sciences, 2019. [19] A. M. Rahmani et al., “Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach,” Future Gener. Comput. Syst., 78: 641-658, 2018. [20] X. Masip-Bruin et al., “Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems,” IEEE Wireless Commun., 23(5): 120-128, 2016. [21] G. M. Dias, Prediction-based strategies for reducing data transmissions in the loT, Universitat Pompeu Fabra, 2016. [22] V. B. Souza et al., “Towards distributed service allocation in fog-to-cloud (f2c) scenarios,” in Proc. 2016 IEEE global communications conference (GLOBECOM), 2016. [23] M. Ramachandra, “Optimization of the data transactions and computations in IoT sensors,” in Proc. 2016 International Conference on Internet of Things and Applications (IOTA), 2016. [24] A. Kumar, N. C. Narendra and U. Bellur, “Uploading and replicating internet of things (IoT) data on distributed cloud storage,” in Proc. 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), 2016. [25] J. S. Li, C. H. Chao, “An efficient superpeer overlay construction and broadcasting scheme based on perfect difference graph,” IEEE Trans. Parallel Distrib. Syst., 21(5): 594-606, 2009. [26] N. Singh et al., Study of Topological Analogies of Perfect difference Network and Complete Graph, 2019. [27] M. Ghobaei-Arani et al., “Resource management approaches in fog computing: a comprehensive review,” J. Grid Comput., 18: 1-42, 2019. [28] E. M. Tordera et al., “What is a fog node a tutorial on current concepts towards a common definition,” arXiv preprint arXiv:1611.09193, 2016. [29] H. Gupta et al., “iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments,” Softw. Pract. Exper., 2017. 47(9): 1275-1296, 2017. [30] R. Mahmud, R. Buyya, “Modelling and simulation of fog and edge computing environments using iFogSim toolkit,” Fog and edge computing: Principles and paradigms: 433-465, 2019. [31] R. N. Calheiros et al., “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” Softw. Pract. Exper., 41(1): 23-50, 2011. [32] P. Maiti et al., “Mathematical modeling of qos-aware fog computing architecture for iot services,” in Proc. Emerging Technologies in Data Mining and Information Security: 13-21, 2019. [33] T. H. Kim et al., Smart city and IoT, Elsevier: 159-162, 2017. [34] A. Yousefpour et al., “All one needs to know about fog computing and related edge computing paradigms: A complete survey,” J. Syst. Archit., 98: 289-330, 2019. [35] A. Yousefpour et al., “Fog computing: Towards minimizing delay in the internet of things,” in Proc. 2017 IEEE international conference on edge computing (EDGE), 2017. [36] Z. Wan et al., “KFIML: Kubernetes-based fog computing iot platform for online machine learning,” IEEE Internet Things J., 9(19): 19463-19476, 2022. [37] H. Zahmatkesh, F. Al-Turjman, “Fog computing for sustainable smart cities in the IoT era: Caching techniques and enabling technologies-an overview,” Sustainable Cities Soc., 59: 102139, 2020. [38] O. Skarlat, S. Schulte, “FogFrame: a framework for IoT application execution in the fog,” PeerJ Comput. Sci., 7(22): e588, 2021. [39] D. A. Chekired, L. Khoukhi, “Multi-tier fog architecture: A new delay-tolerant network for IoT data processing,” in Proc. 2018 IEEE International Conference on Communications (ICC), 2018.
آمار تعداد مشاهده مقاله: 660 تعداد دریافت فایل اصل مقاله: 480

سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب

پیوندهای مفید

آمار

New platform for IoT Application Management based on fog computing