Smart City Gnosys

Smart city article details

Title	Edge Assisted, Forecast Integrated Ensemble Learning Based Service Management Scheme For Delay Minimization In Smart Cities Applications
ID_Doc	21738
Authors	Hemant Kumar Reddy K.; Goswami R.S.; Roy D.S.
Year	2023
Published	Journal of King Saud University - Computer and Information Sciences, 35, 10
DOI	http://dx.doi.org/10.1016/j.jksuci.2023.101806
Abstract	As the Internet of Things (IoT) is maturing as a technology, innovative and cross-domain IoT applications have seen smart cities being conceived and designed across the globe, though with data and resource management challenges, Quality of Service (QoS) fulfilment challenges among others. These could also be addressed by means of context-aware fog computing at the edge of the network and also by incorporating intelligence at the network edge. Since workload at fog nodes can anytime see sudden changes in demand, hence load migration among fog nodes becomes viable. However, improper migration can lead to further migrations, eventually decreasing performance. In this paper, we present a multi-channel queuing model based smart distributed service management approach and an intelligent resource-aware forecasting technique to predict the required context and resource management. The scheme accomplishes live migration by a resource-aware ensemble forecast method that used current and predicted resource utilization and their context availabilities to address the delay requirement for cross-domain IoT applications. The proposed management algorithms are simulated using CloudSim simulator and the efficacy of the obtained results confirm the superiority of the proposed methods. © 2023 The Authors
Author Keywords	Context awareness; Context sharing; Ensemble model; Resource management; Service delay; Unified IoT applications

Similar Articles

Id	Similarity	Authors	Title	Published
2203	0.934	Reddy K.H.K.; Srivastava G.; Goswami R.S.; Roy D.S.	A Hybrid Optimized Intelligent Resource-Constrained Service Scheduling For Unified Iot Applications In Smart Cities	IEEE Transactions on Network and Service Management, 21, 2 (2024)
22450	0.894	Reddy K.H.K.; Goswami R.S.; Luhach A.K.; Chatterjee P.; Alnumay M.; Roy D.S.	Eflsm:- An Intelligent Resource Manager For Fog Layer Service Management In Smart Cities	IEEE Transactions on Consumer Electronics, 70, 1 (2024)
1849	0.882	Kumar Reddy K.H.; Goswami R.S.; Sinha Roy D.	A Futuristic Green Service Computing Approach For Smart City: A Fog Layered Intelligent Service Management Model For Smart Transport System	Computer Communications, 212 (2023)
26795	0.87	Cheng, B; Solmaz, G; Cirillo, F; Kovacs, E; Terasawa, K; Kitazawa, A	Fogflow: Easy Programming Of Iot Services Over Cloud And Edges For Smart Cities	IEEE INTERNET OF THINGS JOURNAL, 5, 2 (2018)
48508	0.868	Wang Y.; Shafik W.; Seong J.-T.; Al Mutairi A.; SidAhmed Mustafa M.; Mouhamed M.R.	Service Delay And Optimization Of The Energy Efficiency Of A System In Fog-Enabled Smart Cities	Alexandria Engineering Journal, 84 (2023)
2802	0.867	Liu Z.R.	A Multi-Joint Optimisation Method For Distributed Edge Computing Resources In Iot-Based Smart Cities	Journal of Grid Computing, 21, 4 (2023)
20630	0.867	Mahmood O.A.; Abdellah A.R.; Muthanna A.; Koucheryavy A.	Distributed Edge Computing For Resource Allocation In Smart Cities Based On The Iot	Information (Switzerland), 13, 7 (2022)
26767	0.865	Gokulkannan S.; Kiranshankar S.; Kishore S.; Lanitha B.	Fog Environment For Smart Cities With Multi-Level Resource Sharing Framework	Proceedings of the 2023 2nd International Conference on Electronics and Renewable Systems, ICEARS 2023 (2023)
2288	0.864	Sahoo S.; Sahoo K.S.; Sahoo B.; Gandomi A.H.	A Learning Automata Based Edge Resource Allocation Approach For Iot-Enabled Smart Cities	Digital Communications and Networks, 10, 5 (2024)
26780	0.864	Apat H.K.; Goswami V.; Sahoo B.; Barik R.K.; Saikia M.J.	Fog Service Placement Optimization: A Survey Of State-Of-The-Art Strategies And Techniques	Computers, 14, 3 (2025)