Browse > Article
http://dx.doi.org/10.3837/tiis.2022.11.010

Hierarchical Resource Management Framework and Multi-hop Task Scheduling Decision for Resource-Constrained VEC Networks  

Hu, Xi (Northeastern University at Qinhuangdao)
Zhao, Yicheng (Northeastern University at Qinhuangdao)
Huang, Yang (Northeastern University at Qinhuangdao)
Zhu, Chen (Northeastern University at Qinhuangdao)
Yao, Jun (Northeastern University at Qinhuangdao)
Fang, Nana (Northeastern University at Qinhuangdao)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.11, 2022 , pp. 3638-3657 More about this Journal
Abstract
In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.
Keywords
Vehicular Edge Computing (VEC); Multi-hop task scheduling; Resource management framework; Auction; Greedy matching;
Citations & Related Records
연도 인용수 순위
  • Reference
1 C. M. Xu, S. H. Liu, C. Zhang, "Multi-agent Reinforcement learning Based Distributed Transmission in Collaborative Cloud-Edge Systems," IEEE Transactions on Vehicular Technology, vol. 70, no. 2, pp. 1658-1672, Jan. 2021.   DOI
2 L. L. Wang, J. S. Gui, X. H. Deng, "Routing Algorithm Based on Vehicle Position Analysis for Internet of Vehicles," IEEE Internet of Things Journal., vol. 7, no. 12, pp. 11701-11712, jun. 2020.   DOI
3 H. Li, X. Li, M. Zhang, and B. Ulziinyam, "Multicast-oriented task offloading for vehicle edge computing," IEEE Access., vol. 8, pp. 187373-187383, Oct. 2020.   DOI
4 H. Zhou, K. Jiang, X. Liu, X. Li, and V. C. M. Leung, "Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing," IEEE Internet Things J., vol. 9, no. 2, pp. 1517-1530, Jan. 2022.   DOI
5 L. Tan, R. Hu, "Mobility-aware edge caching and computing in vehicle networks: a deep reinforcement learning," IEEE Transactions on Vehicular Technology, vol. 67, no. 11, pp. 10190-10203, Nov. 2018.   DOI
6 D. T. Hoang, D. Niyato and P. Wang, "Optimal admission control policy for mobile cloud computing hotspot with cloudlet," in Proc. of 2012 IEEE Wireless Communications and Networking Conference (WCNC), 2012.
7 J. Zhang et al., "Energy-latency tradeoff for energy-aware offloading in mobile edge computing networks," IEEE Internet Things J., vol. 5, no. 4, pp. 2633-2645, Aug. 2018.   DOI
8 A. Ebra and M. Maier, "Distributed cooperative computation offloading in multi-access edge computing fiber-wireless networks" Optics Communications, vol. 452, pp. 130-139, Dec. 2019.   DOI
9 J. Zjao, Q. Li, Y. Gong, K. Zhang, "Computation offloading and resource allocation for cloud assisted mobile edge computing in vehicular networks," IEEE Transactions on Vehicular Technology, vol. 68, pp.7944-7956, Jun. 2019.   DOI
10 J. Cheng, D. Guan, "Research on task-offloading decision mechanism in mobile edge computing-based Internet of Vehicle," EURASIP Journal on Wireless Communications, pp. 2-14, Apr. 2021.
11 Y. Mao, C. You, J. Zhang, K. Huang and K. B. Letaief, "A Survey on Mobile Edge Computing: The Communication Perspective," IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2322-2358, Aug. 2017.   DOI
12 T. Feng, B. Wang, H. -t. Zhao, T. Zhang, J. Tang and Z. Wang, "Task distribution offloading algorithm based on DQN for sustainable vehicle edge network," in Proc. of 2021 IEEE 7th International Conference on Network Softwarization (NetSoft), 2021.
13 X. Guo, R. Singh, T. Zhao and Z. Niu, "An index based task assignment policy for achieving optimal power-delay tradeoff in edge cloud systems," in Proc. of 2016 IEEE International Conference on Communications (ICC), 2016.
14 K. Zhang, Y. Mao, S. Leng, S. Maharjan and Y. Zhang, "Optimal delay constrained offloading for vehicular edge computing networks," in Proc. of 2017 IEEE International Conference on Communications (ICC), 2017.
15 W. He, S. Guo, Y. Liang, and X. Qiu, "Markov approximation method for optimal service orchestration in IoT network," IEEE Access, vol. 7, pp. 49538-49548, Apr. 2019.   DOI
16 Z. Wang, S. Zheng, Q. Ge, K. Q. Li, "Online Offloading Scheduling and Resource Allocation Algorithms for Vehicular Edge Computing System," IEEE Access, vol. 8, pp. 52428-52442, Mar. 2020.   DOI
17 Y. Cao and Y. Chen, "QoE-based node selection strategy for edge computing enabled Internet-of-Vehicle(EC-lov)," in Proc. of 2017 IEEE Visual Communications and Image Processing (VCIP), pp. 1-4, Mar. 2018.
18 L. Liu, M. Zhao, M. A. Jan, A. Tah, "Mobility-Aware Multi-Hop Task Offloading for Autonomous Driving in Vehicular Edge Computing and Networks," IEEE Transactions on Intelligent Transportation Systems, pp. 1-14, Jan. 2022.
19 X. Zhang, M. Peng, S. Y an, and Y. Sun, "Deep-reinforcement-learning-based mode selection and resource allocation for cellular V2X communications," IEEE Internet Things J., vol. 7, no. 7, pp. 6380-6391, Jul. 2020.   DOI
20 M. Sal, P. Fan, G. Liu, "A cluster-based cooperative computation offloading scheme for C-V2X networks," Ad Hoc Networks., vol. 132, pp. 1-12, Apr. 2022.
21 H. Guo, J. Zhang, J. Liu, "Fiwi-enhanced vehicular edge computing networks: Collaborative task offloading," IEEE Vehicular Technology Magazine., vol. 14, pp.45-53, Mar. 2019.   DOI
22 Z. Hong, W. Chen, H. Huang, S. Guo, Z. Zheng, "Multi-hop cooperative computation offloading for industrial IoT-edge-cloud computing environments," IEEE Transactions on Parallel and Distributed Systems, vol. 30, pp. 2759-2774, Jul. 2019.   DOI
23 G. S. Li, Q. Y. Lin, J. H. Wu, "Dynamic computation offloading based on Graph partitioning in Mobile Edge Computing" IEEE Access, vol. 7, pp.185131-185139, Dec. 2019.   DOI
24 J. Xu, L. Chen and S. Ren, "Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing," IEEE Transactions on Cognitive Communications and Networking., vol. 3, no. 3, pp. 361-373, jul. 2017.   DOI
25 C. Lee and A. Fumagalli, "Internet of Things Security - Multilayered Method For End to End Data Communications Over Cellular Networks," in Proc. of 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), 2019.
26 A. Kiani, N. Ansari, "Toward hierarchical mobile edge computing: an auction-based profit maximization approach," IEEE Internet of Things Journal., vol. 4, no. 6, pp.2082-2091, Dec. 2017.   DOI
27 G. H. Qiao, S. P. Leng, K. Zhang, "Collaborative Task Offloading in Vehicular Edge Multi-Access Networks," IEEE Access, vol. 8, pp. 51-59, Oct. 2020.
28 L. Liang, H. Ye, and G. Y. Li, "Spectrum sharing in vehicular networks based on multi-agent reinforcement learning," IEEE J. Sel. Areas Commun., vol. 37, no. 10, pp. 2282-2292, Oct. 2019.   DOI
29 H. Zhang, Z. Wang, and K. Liu, "V2X offloading and resource allocation in SDN-assisted MEC-based vehicular networks," China Communications., vol. 17, no. 5, pp. 266-283, May. 2020.   DOI
30 Y. Liu, H. M. Yu, Y. Zhang, "Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks," IEEE Transactions on Vehicular Technology., vol. 68, no. 11, pp. 11158-11168, Nov. 2019.   DOI
31 K. Zhang, Y. Mao, S. Leng, Y. He and Y. ZHANG, "Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading," IEEE Vehicular Technology Magazine, vol. 12, no. 2, pp. 36-44, Apr. 2017.   DOI