Computation Offloading in Edge Computing for Internet of Vehicles via Game Theory
Source abstract
Abstract
With the rapid advancement of Internet of Vehicles (IoV) technology, the demands for real-time navigation, advanced driver-assistance systems (ADAS), vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: IoT and Edge/Fog Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (47)
Show source-provided references
1. Application of internet of things technology based on artificial intelligence in electronic information engineering
2. Research on intelligent campus and visual teaching system based on internet of things10.1155/2022/6508811 ↗
3. Design of distributed collection model of student development information based on internet of things technology
4. The design of the exercise load monitoring system based on internet of things
5. Information-centric networking: Research and standardization status10.1109/ACCESS.2019.2938586 ↗
6. Auto-adaptive trust measurement model based on multidimensional decision-making attributes for internet of vehicles10.1155/2022/3537771 ↗
7. A blockchain based privacy-preserving incentive mechanism for internet of vehicles in satellite-terrestrial crowdsensing
8. Modeling analysis of improved minimum safe following distance under internet of vehicles10.1155/2022/8005601 ↗
9. Driver’s face pose estimation using fine-grained Wi-Fi signals for next-generation internet of vehicles10.1155/2022/7353080 ↗
10. Survey of interoperability challenges in the internet of vehicles10.1109/TITS.2022.3194413 ↗
11. A lightweight authenticated key agreement protocol using fog nodes in social internet of vehicles
12. The future of autonomous vehicles: How data and connectivity will transform mobility
13. Streaming-viability analysis and packet scheduling for video over in-vehicle wireless networks10.1109/TVT.2007.901927 ↗
14. Resource allocation in D2D-based V2V communication for maximizing the number of concurrent transmissions
15. Optimal weighting factor design of finite control set model predictive control based on multi objective ant colony optimization10.1109/TIE.2023.3301534 ↗
16. Stepping ahead firefly algorithm and hybridization with evolution strategy for global optimization problems10.1016/j.asoc.2021.107517 ↗
17. Optimization of 3D trajectory of UAV patrol inspection transmission tower based on hybrid genetic-simulated annealing algorithm
18. Y. Liu, S. Wang, J. Huang, and F. Yang, “A computation offloading algorithm based on game theory for vehicular edge networks,” presented at the 2018 ICC, Kansas City, MO, USA, May 20–24, 2018.10.1109/ICC.2018.8422240 ↗
19. Joint allocation of wireless resource and computing capability in MEC-enabled vehicular network10.23919/JCC.2021.06.006 ↗
20. PPRU: A privacy-preserving reputation updating scheme for cloud-assisted vehicular networks
21. PPTM: A privacy-preserving trust management scheme for emergency message dissemination in space–air–ground-integrated vehicular networks10.1109/JIOT.2021.3060751 ↗
22. M. Zhu, Y. Hou, X. Tao, T. Sui, and L. Gao, “Joint optimal allocation of wireless resource and MEC computation capability in vehicular network,” presented at the 2020 WCNCW, Republic of Korea, Apr. 6–9, 2020.10.1109/WCNCW48565.2020.9124737 ↗
23. Energy-delay minimization of task migration based on game theory in mec-assisted vehicular networks10.1109/TVT.2022.3175238 ↗
24. Task offloading strategy and simulation platform construction in multi-user edge computing scenario10.3390/electronics10233038 ↗
25. Internet of vehicles resource scheduling based on blockchain and game theory
26. A survey of game theory in unmanned aerial vehicles communications10.1109/COMST.2019.2919613 ↗
27. Energy-latency tradeoff for computation offloading in UAV-assisted multi-access edge computing system10.1109/JIOT.2020.2999063 ↗
28. Y. Jang, J. Na, S. Jeong, and J. Kang, “Energy-efficient task offloading for vehicular edge computing: Joint optimization of offloading and bit allocation,” presented at the 2020 VTC2020-Spring, Antwerp, Belgium, May 25–28, 2020. doi: 10.1109/VTC2020-Spring48590.2020.9128785.10.1109/VTC2020-Spring48590.2020.9128785 ↗
29. Task offloading for mobile edge computing in software defined ultra-dense network10.1109/JSAC.2018.2815360 ↗
30. Collaborate edge and cloud computing with distributed deep learning for smart city internet of things10.1109/JIOT.2020.2996784 ↗
31. Y. Zhang, X. Qin, and X. Song, “Mobility-aware cooperative task offloading and resource allocation in vehicular edge computing,” presented at the 2020 WCNCW, Seoul, Republic of Korea, Apr. 6–9, 2020.10.1109/WCNCW48565.2020.9124825 ↗
32. H. Wang, Z. Lin, K. Guo, and T. Lv, “Computation offloading based on game theory in MEC-assisted v2x networks,” presented at the 2021 ICC Workshops, Montreal, QC, Canada, Jun. 14–23, 2021.10.1109/ICCWorkshops50388.2021.9473788 ↗
33. Energy-efficient offloading decision-making for mobile edge computing in vehicular networks10.1186/s13638-020-1652-5 ↗
34. Joint task offloading and resource allocation for energy-constrained mobile edge computing10.1109/TMC.2022.3150432 ↗
35. Deep reinforcement learning based computation offloading and trajectory planning for multi-UAV cooperative target search10.1109/JSAC.2022.3228558 ↗
36. Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing10.1109/TWC.2022.3153316 ↗
37. A resource allocation strategy for internet of vehicles using reinforcement learning in edge computing environment10.1007/s00500-022-07544-4 ↗
38. Task offloading strategy based on reinforcement learning computing in edge computing architecture of internet of vehicles10.1109/ACCESS.2020.3023939 ↗
39. A computing offloading resource allocation scheme using deep reinforcement learning in mobile edge computing systems10.1007/s10723-021-09568-w ↗
40. An improved method of artificial bee colony algorithm10.4028/www.scientific.net/AMM.187.315 ↗
41. Non-cooperative and cooperative optimization of scheduling with vehicle-to-grid regulation services10.1109/TVT.2019.2952712 ↗
42. An optimal edge detection using modified artificial bee colony algorithm10.1007/s40010-015-0256-7 ↗
43. A bee colony-based algorithm for task offloading in vehicular edge computing10.1109/JSYST.2023.3237363 ↗
44. An enhanced greedy resource allocation algorithm for localized SC-FDMA systems10.1109/LCOMM.2013.052013.130716 ↗
45. Hierarchically partitioned coordinated operation of distributed integrated energy system based on a master-slave game10.1016/j.energy.2020.119006 ↗
46. Fuzzy Kakutani-Fan-Glicksberg fixed point theorem and existence of Nash equilibria for fuzzy games10.1016/j.fss.2022.02.002 ↗
47. Incentive mechanism for computation offloading using edge computing: A stackelberg game approach10.1016/j.comnet.2017.03.015 ↗