An Edge Computing Collaboration Solution for Internet of Vehicles
Vu Khanh Quy, Dang Van Anh, Vi Hoai Nam, Nguyen Minh Quy, Anh-Ngoc Le
Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 37–41 (2022)
Abstract. The advent of 5th generation communication systems (5G) in the early 21st century has realized real-time Internet of Things applications. 5G has capable of providing network services with extremely-high throughput and extremely low delay and allows a huge device number to connect together based on Internet infrastructure, forming the Internet of Things (IoT). In recent years, IoT has been applied in a variety of fields serving humans, such as smart cities, smart agriculture, e-healthcare, smart education, military, and IoT ecosystems. One of the main challenges of IoT applications is computing solutions to reduce service response times. In this study, we propose an Edge Computing Collaboration Solution for the Internet of Vehicles (IoV). Our solution proposes a small database that allows edge computing servers of IoVs to store each other's information. When the mobile end-users move to the new edge servers' managed coverage, properties related to the EC service are exchanged between the edge servers. The results have shown that our proposed solution improves significantly service response time, by up to 10-20\%, compared to the existing solutions.
- S. V. Balkus, H. Wang, B. D. Cornet, C. Mahabal, H. Ngo, H. Fang, “A Survey of Collaborative Machine Learning Using 5G Vehicular Communications,” IEEE Communications Surveys & Tutorials, 24(2), pp. 1280-1303, 2022.
- M. A. Jamshed, K. Ali, Q. H. Abbasi, M. A. Imran, M. Ur-Rehman, “Challenges, Applications, and Future of Wireless Sensors in Internet of Things: A Review,” IEEE Sensors Journal, 22(6), pp. 5482-5494, 2022.
- Y. B. Zikria, R. Ali, M. K. Afzal, et al., “Next-Generation Internet of Things (IoT): Opportunities, Challenges, and Solutions,” Sensors, vol. 2021, Article ID 1174, 21 pages, 2021.
- B. Liu, Z. Luo, H. Chen and C. Li, “A Survey of State-of-the-art on Edge Computing: Theoretical Models, Technologies, Directions, and Development Paths,” IEEE Access, vol. 10, pp. 54038-54063, 2022.
- S. Xu, Y. Li, S. Guo, C. Lei, D. Liu, X. Qiu, “Cloud–Edge Collaborative SFC Mapping for Industrial IoT Using Deep Reinforcement Learning,” IEEE Transactions on Industrial Informatics, 18(6), pp. 4158-4168, 2022.
- J. Du, C. Jiang, A. Benslimane, S. Guo and Y. Ren, "SDN-Based Resource Allocation in Edge and Cloud Computing Systems: An Evolutionary Stackelberg Differential Game Approach," IEEE/ACM Transactions on Networking, 30(4), pp. 1613-1628, 2022.
- L. U. Khan et al., “Edge-Computing-Enabled Smart Cities: A Comprehensive Survey,” IEEE Internet of Things Journal, 7(10), pp. 10200-10232, 2020.
- A. Kirimtat, O. Krejcar, A. Kertesz, et al., “Future Trends and Current State of Smart City Concepts: A Survey,” IEEE Access, vol. 8, pp. 86448-86467, 2020.
- H. Zhao, Y. Zhang, X. Huang, Y. Xiang, C. Su, “A Physical-Layer Key Generation Approach Based on Received Signal Strength in Smart Homes,” IEEE Internet of Things Journal, 9(7), pp. 4917-4927, 2022.
- A. Mitra, D. Bigioi, S. P. Mohanty, P. Corcoran, E. Kougianos, “iFace 1.1: A Proof-of-Concept of a Facial Authentication Based Digital ID for Smart Cities,” IEEE Access, vol. 10, pp. 71791-71804, 2022.
- K. Zhang, H. Chen, H. -N. Dai, H. Liu and Z. Lin, “SpoVis: Decision Support System for Site Selection of Sports Facilities in Digital Twinning Cities,” IEEE Transactions on Industrial Informatics, 18(2), pp. 1424-1434, 2022.
- K. L. A. Yau, S. Peng, J. Qadir, et al., “Towards Smart Port Infrastructures: Enhancing Port Activities Using Information and Communications Technology,” IEEE Access, vol. 8, pp. 83387 - 83404, 2020.
- S. Chavhan, N. Dubey, A. Lal, et al., “Next-Generation Smart Electric Vehicles Cyber Physical System for Charging Slots Booking in Charging Stations,” IEEE Access, vol. 8, pp. 160145 - 160157, 2020.
- E. ElGhanam, H. Sharf et al., “On the Coordination of Charging Demand of Electric Vehicles in a Network of Dynamic Wireless Charging Systems,” IEEE Access, vol. 10, pp. 62879 - 62892, 2022.
- J. Qiu, L. Du, D. Zhang, et al., “Nei-TTE: Intelligent Traffic Time Estimation Based on Fine-Grained Time Derivation of Road Segments for Smart City,” IEEE Transactions on Industrial Informatics, vol. 16, pp. 2659 - 2666, 2020.
- E. Ghaffari, A. M. Rahmani, M. Saberikamarposhti, “An Optimal Path-Finding Algorithm in Smart Cities by Considering Traffic Congestion and Air Pollution,” IEEE Access, vol. 10, pp. 55126 - 55135, 2022.
- A. Aldegheishem, N. Alrajeh, L. García, et al., “SWAP: Smart WAter Protocol for the Irrigation of Urban Gardens in Smart Cities,” IEEE Access, vol. 10, pp. 39239 - 39247, 2022.
- M. Ghahramani, M. C. Zhou, A. Molter, F. Pilla, “IoT-Based Route Recommendation for an Intelligent Waste Management System,” IEEE Internet of Things Journal, vol. 9, pp. 11883 - 11892, 2022.
- F. Huang, J. Xu, J. Weng, “Multi-Task Travel Route Planning With A Flexible Deep Learning Framework,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 7, pp. 3907-3918, 2021.
- J. R. Santana, L. Sánchez, P. Sotres, et al., “A Privacy-Aware Crowd Management System for Smart Cities and Smart Buildings,” IEEE Access, vol. 8, pp. 135394 - 135405, 2020.
- R. Zhou, X. Zhang, X. Wang, G. Yang, N. Guizani and X. Du, “Efficient and Traceable Patient Health Data Search System for Hospital Management in Smart Cities,” IEEE Internet of Things Journal, 8(8), pp. 6425-6436, 2021.
- Y. Bai, Q. Hu, S. H. Seo, et al., “Public Participation Consortium Blockchain for Smart City Governance,” IEEE Internet of Things Journal, vol. 9, pp. 2094 - 2108, 2020.
- B. Khazael, H. T. Malazi, S. Clarke, “Complex Event Processing in Smart City Monitoring Applications,” IEEE Access, vol. 9, pp. 143150 - 143165, 2020.
- G. Rathee et al., “On the Design and Implementation of a Blockchain Enabled E-Voting Application Within IoT-Oriented Smart Cities,” IEEE Access, vol. 9, pp. 34165 - 34176, 2021.
- H. Wang et al., “Architectural Design Alternatives Based on Cloud/Edge/Fog Computing for Connected Vehicles,” IEEE Communications Surveys & Tutorials, 22(4), pp. 2349-2377, 2020.