Smart City Gnosys
Smart city article details
| Title | Dynamic Edge Server Placement For Computation Offloading In Vehicular Edge Computing |
|---|---|
| ID_Doc | 21262 |
| Authors | Nakrani D.; Khuman J.; Yadav R.N. |
| Year | 2023 |
| Published | International Conference on Information Networking, 2023-January |
| DOI | http://dx.doi.org/10.1109/ICOIN56518.2023.10049001 |
| Abstract | Edge Computing is a distributed computing architecture where the computing process takes place near the user's physical location or at the source where the data originates. By placing the edge servers (ES) closer to the user's location, the services received are faster and more reliable while benefiting from edge computing. Various Internet of Vehicle (IoV) applications in smart cities including assisted and autonomous driving, real-time accidents monitoring require huge data processing and low-latency communication. Since the user's devices are resource constrained, an effective approach to address this constraint is to offload their tasks to nearby ES. So, an adaptive placements (to respond continuously changing environment) of these edge computing devices play a major role in the performance of various IoV applications. So, an efficient placement of ES is considered a critical issue in vehicular edge computing (VEC). To address the efficient and cost aware dynamic ES placement problem (CADEP), we developed two greedy algorithms. First, is cost aware and vehicle density based deployment of ES (static) that ensures that each vehicle's demand is covered by at least by one ES (coverage constraint), called Greedy_static. Second, is based on vehicle density and is dynamic as per changing environment, called Greedy_dynamic which updates ES locations periodically based on change in the environment. To minimize the relocation cost, we formulated an optimization problem and used Hungarian matching to find optimal cost. For various vehicle densities, we found that our algorithms outperform uniform strategies in terms of cost-effectiveness and ES utilization. Further, for dynamic relocation of ES, we have shown that the cost required to relocate ES randomly is more as compared to our proposed algorithm Greedy_dynamic. © 2023 IEEE. |
| Author Keywords | Computation offloading; Edge Computing; Internet of vehicles; Matching |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
22296  | 0.912 | Khamari S.; Ahmed T.; Mosbah M. | Efficient Edge Server Placement Under Latency And Load Balancing Constraints For Vehicular Networks | Proceedings - IEEE Global Communications Conference, GLOBECOM (2022) |
| 5238 | 0.889 | Yuan S.; Fan Y.; Cai Y. | A Survey On Computation Offloading For Vehicular Edge Computing | ACM International Conference Proceeding Series (2019) |
| 32466 | 0.885 | Wu Y.; Fang X.; Min G.; Chen H.; Luo C. | Intelligent Offloading Balance For Vehicular Edge Computing And Networks | IEEE Transactions on Intelligent Transportation Systems, 26, 5 (2025) |
| 60992 | 0.882 | Meneguette R.; De Grande R.; Ueyama J.; Filho G.P.R.; Madeira E. | Vehicular Edge Computing: Architecture, Resource Management, Security, And Challenges | ACM Computing Surveys, 55, 1 (2022) |
| 21801 | 0.874 | Laha M.; Kamble S.; Datta R. | Edge Nodes Placement In 5G Enabled Urban Vehicular Networks: A Centrality-Based Approach | 26th National Conference on Communications, NCC 2020 (2020) |
| 38362 | 0.87 | Bréhon–Grataloup L.; Kacimi R.; Beylot A.-L. | Multi-Rat-Enabled Edge Computing For Vehicle-To-Everything Architectures | Ad Hoc Networks, 154 (2024) |
| 26799 | 0.862 | Rehman M.A.U.; Salah Ud Din M.; Mastorakis S.; Kim B.-S. | Foggyedge: An Information-Centric Computation Offloading And Management Framework For Edge-Based Vehicular Fog Computing | IEEE Intelligent Transportation Systems Magazine, 15, 5 (2023) |
| 7252 | 0.858 | Guo H.; Shi R.-C.; Gu P.-L.; Li J.-L.; Wang S.-L. | Allocating Edge Service Resources To The Up-Offloaded Vehicle Tasks In Icv Environment | Computer Networks, 227 (2023) |
| 34289 | 0.858 | Khdr S.O.; Azizi S.; Hassan H.O. | Iterative Weighted Randomized Algorithm For Edge Server Deployment In Mobile Edge Computing | Passer Journal of Basic and Applied Sciences, 7, 1 (2025) |
| 23454 | 0.856 | Elgendy I.A. | Energy-Efficient And Secure Framework For Computation Offloading In Sustainable Vehicular Edge-Cloud Networks | 2024 IEEE Sustainable Power and Energy Conference, iSPEC 2024 (2024) |