Smart City Gnosys

Smart city article details

Title	A Hybrid Pso-Rr Approach For Efficient Real Time Task Scheduling In Fog & Iot Environment
ID_Doc	2208
Authors	Arora D.; Sharma O.
Year	2023
Published	ISED 2023 - International Conference on Intelligent Systems and Embedded Design
DOI	http://dx.doi.org/10.1109/ISED59382.2023.10444540
Abstract	Resource utilization in real-time systems must be optimized through effective job scheduling. In this paper, we propose a unique hybrid method for task scheduling that combines Round-Robin (RR) and Particle Swarm Optimization (PSO) algorithms. The approach attempts to satisfy real-time processing demands while achieving an optimal balance between energy consumption and total execution cost. The task scheduling process begins by initializing the PSO with a swarm of particles, each of which represents a potential solution. In order to find the best solution, these particles are iteratively updated based on their fitness and that of nearby particles. The RR method is used with the best PSO particle to further optimize scheduling of tasks. Round-robin scheduling (RR) distributes tasks fairly and prevents task starvation. This hybrid approach implies to various real time scenarios such as smart homes, smart city etc. This approach maximizes resource utilization and efficiency by prioritizing task based on priority and urgency in dynamic manner. Experimental results show hybrid approach is more efficient than individual RR and PSO algorithm in term of energy consumption and total execution cost. This hybrid technique provides a strong and adaptable solution for real time task scheduling in resource constraints environment. Therefore, this hybrid architecture that combines PSO and RR algorithms shows potential for solving challenging real-time task scheduling issues. The method excels in minimizing execution costs, energy efficiency, and satisfying real-time processing needs. Its capacity to adapt to various real-time situations strengthens its suitability for use in fog computing and improved job scheduling effectiveness in the IoT and smart technology era. © 2023 IEEE.
Author Keywords	Execution Cost; Fog Computing; Internet of Things; Particle Swam Optimization; Real Time Environment; Round- Robin; Task Scheduling

Similar Articles

Id	Similarity	Authors	Title	Published
59214	0.886	Sharma O.; Rathee G.; Kerrache C.A.; Herrera-Tapia J.	Two-Stage Optimal Task Scheduling For Smart Home Environment Using Fog Computing Infrastructures	Applied Sciences (Switzerland), 13, 5 (2023)
29804	0.878	Awotunde J.B.; Tripathy H.K.; Bandyopadhyay A.	Hybrid Particle Swarm Optimization With Firefly Based Resource Provisioning Technique For Data Fusion Fog-Cloud Computing Platforms	Fusion: Practice and Applications, 8, 2 (2022)
60657	0.877	Hoseiny F.; Azizi S.; Dabiri S.	Using The Power Of Two Choices For Real-Time Task Scheduling In Fog-Cloud Computing	Proceeding of 4th International Conference on Smart Cities, Internet of Things and Applications, SCIoT 2020 (2020)
2542	0.876	Aranguren I.; Fausto F.; González A.; L-Aguiñaga A.	A Metaheuristic Task Scheduling Of Fog Servers Using A Hybridization Of Crow Search Algorithm With Non-Monopolize Search	Studies in Computational Intelligence, 806 (2025)
647	0.874	Butt A.A.; Khan S.; Ashfaq T.; Javaid S.; Sattar N.A.; Javaid N.	A Cloud And Fog Based Architecture For Energy Management Of Smart City By Using Meta-Heuristic Techniques	2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019 (2019)
8855	0.874	Apat H.K.; Sahoo B.; Bhaisare K.; Maiti P.	An Optimal Task Scheduling Towards Minimized Cost And Response Time In Fog Computing Infrastructure	Proceedings - 2019 International Conference on Information Technology, ICIT 2019 (2019)
40757	0.872	Jayasena K.P.N.; Thisarasinghe B.S.	Optimized Task Scheduling On Fog Computing Environment Using Meta Heuristic Algorithms	Proceedings - 4th IEEE International Conference on Smart Cloud, SmartCloud 2019 and 3rd International Symposium on Reinforcement Learning, ISRL 2019 (2019)
14430	0.867	Farisi Z.	Cloud Resource Scheduling Strategy Based On Improved Particle Swarm Optimization Algorithm For Smart City System	2024 2nd International Conference on Computer, Vision and Intelligent Technology, ICCVIT 2024 - Proceedings (2024)
40900	0.862	Rahmani A.M.; Haider A.; Khoshvaght P.; Gharehchopogh F.S.; Moghaddasi K.; Rajabi S.; Hosseinzadeh M.	Optimizing Task Offloading With Metaheuristic Algorithms Across Cloud, Fog, And Edge Computing Networks: A Comprehensive Survey And State-Of-The-Art Schemes	Sustainable Computing: Informatics and Systems, 45 (2025)
46065	0.861	Jamil B.; Ijaz H.; Shojafar M.; Munir K.; Buyya R.	Resource Allocation And Task Scheduling In Fog Computing And Internet Of Everything Environments: A Taxonomy, Review, And Future Directions	ACM Computing Surveys, 54, 11s (2022)