Smart City Gnosys

Smart city article details

Title	An Efficient Task Offloading Strategy In Cloud-Edge Computing Under Deadline Constraints
ID_Doc	7910
Authors	Liu Y.; Wang X.; Cheng M.; Wang J.; Zhang Y.
Year	2020
Published	Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020
DOI	http://dx.doi.org/10.1109/HPCC-SmartCity-DSS50907.2020.00085
Abstract	Cloud-edge computing is a new paradigm that can offer sufficient resources and low latency for mobile users, by means of offloading computation tasks from mobile devices to cloud/edge servers. This paper aims at scheduling security-critical tasks in cloud-edge environments by proposing a novel firefly algorithm. The optimization goal of the scheduling problem is to minimize the energy consumption of the cloud-edge system under a deadline constraint upon task completion time. The proposed algorithm uses a position-based mapping method to map a firefly onto a high-quality solution depending on the best solution and a probability model. In addition, we develop a linear movement scheme to replace the standard movement scheme for the purpose of efficient update of firefly positions. Experimental results show that, compared with the standard firefly algorithm, our proposed algorithm achieves not only higher scheduling effectiveness but also lower computational complexity. © 2020 IEEE.
Author Keywords	cloud-edge computing; firefly algorithm; mapping operator; movement scheme; task offloading

Similar Articles

Id	Similarity	Authors	Title	Published
21323	0.892	Wang J.	Dynamic Multiworkflow Offloading And Scheduling Under Soft Deadlines In The Cloud-Edge Environment	IEEE Systems Journal, 17, 2 (2023)
40900	0.878	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)
20723	0.865	Samarneh A.A.; Alma'aitah A.Y.	Distributed Task Offloading In Mobile Edge Computing Using Metaheuristics	2024 6th International Conference on Communications, Signal Processing, and their Applications, ICCSPA 2024 (2024)
34383	0.863	Liang J.; Liu C.; Tan G.; Yang L.	Joint Offloading And Frequency Scaling Technology For Mobile Edge Computing	Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 (2019)
8787	0.862	Yang L.; Dai Z.; Li K.	An Offloading Strategy Based On Cloud And Edge Computing For Industrial Internet	Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 (2019)
23414	0.861	Su Q.; Zhang Q.; Zhang X.	Energy-Aware Cloud-Edge Collaborative Task Offloading With Adjustable Base Station Radii In Smart Cities	Mathematics, 10, 21 (2022)
45588	0.859	Wang Y.; Wang D.; Lin G.; Zheng B.; Luo L.; Li S.	Research On Resource Scheduling And Optimization Strategies Of Edge Computing-Based 5G Networks In Smart City Applications	2023 4th International Symposium on Computer Engineering and Intelligent Communications, ISCEIC 2023 (2023)
2871	0.858	Ma B.; Xu Y.; Pan Y.; Liu S.; Li C.	A Multi-User Mobile Edge Computing Task Offloading And Trajectory Management Based On Proximal Policy Optimization	Peer-to-Peer Networking and Applications, 17, 6 (2024)
27955	0.857	Chen Y.; Ding Y.; Hu Z.-Z.; Ren Z.	Geometrized Task Scheduling And Adaptive Resource Allocation For Large-Scale Edge Computing In Smart Cities	IEEE Internet of Things Journal (2025)
23421	0.856	Zhu G.; Li Q.; Li W.; Lv D.; Guo Y.	Energy-Aware Edge Computing Resource Scheduling Method	Proceedings of SPIE - The International Society for Optical Engineering, 12941 (2023)