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摘要: 考虑了自供电路侧单元在分组传输过程中能量收集、车辆到达与车速的随机性, 基于受限马尔科夫决策模型建立分组调度系统模型, 研究了分组平均传输时延与能量消耗; 分析了在能量队列约束下最小分组平均传输时延的优化问题, 提出了自供电路侧单元能量-时延均衡分组调度策略, 通过仿真试验分析了最优分组调度策略性能, 并与贪婪中继方案和Q-learning算法进行对比。仿真结果表明: 该分组调度策略具有双门限结构, 系统通过自供电路侧单元的能量队列状态以及到达车辆的车速状态确定决策变量, 使系统可以在考虑能量利用效率的前提下降低监测数据分组的平均传输时延, 保证自供电路侧单元在能量存储不溢出不耗尽的同时, 最小化系统分组平均传输时延; 在单分组发送模型中, 提出的分组调度策略的平均传输时延相比贪婪中继方案降低了15.7%, 相比Q-learning算法降低了13.5%;在批量分组发送模型中, 其分组平均传输时延相比贪婪中继方案降低了20.4%, 相比Q-learning算法降低了11.5%。
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关键词:
- 车路协同系统 /
- 路侧单元 /
- 分组调度 /
- 带约束的马尔科夫决策 /
- 能量-时延均衡
Abstract: Considering the randomness of energy harvesting, vehicle arrival and vehicle speed in the process of self-powered roadside units' packet transmission, the packet scheduling system was modeled as a constrained Markov decision model to analyze the average packet transmission delay and energy consumption. The optimization problem of the minimum packet average transmission delay under the constraint of energy queue was analyzed, and packets scheduling scheme for energy-delay tradeoff in self-powered roadside unitswas proposed. The performance of the optimal packet scheduling scheme was analyzed by simulation experiments, and compared with the greedy bundle relaying scheme and Q-learning method. Simulation result shows that the packet scheduling scheme has a dual-threshold structure. The decision variables were determined by the energy queue state of the self-powered roadside units and the speed state of the arriving vehicles, so that the system can reduce the average transmission delay of the monitoring data on the premise of considering the energy utilization efficiency, and ensure non-overflow of the self-powered roadside units' energy storage to minimize the average packet transmission delay. In the single packet transmission model, the average transmission delay of the proposed packet scheduling scheme is 15.7% lower than that of greedy bundle relaying scheme, and 13.5% lower than that of Q-learning method. In the batch packet transmission model, the average transmission delay of the proposed packet scheduling scheme is 20.4% lower than that of greedy forwarding scheme, and 11.5% lower than that of Q-learning method. -
图 1 自供电路侧单元监测数据传输场景
Figure 1. Monitoring data transmission scene of self-powered roadside units
图 2 自供电路侧单元与车辆间分组调度模型
Figure 2. Packets scheduling model between self-powered roadside units and vehicle
图 5 单分组发送模型下平均传输时延随能量到达率变化曲线
Figure 5. Curves of average transmission delay with energy arrival rate under single packet transmission model
图 6 单分组发送模型下能量消耗随能量到达率变化曲线
Figure 6. Curves of energy consumption with energy arrival rate under single packet transmission model
图 7 批量分组发送模型下平均传输时延随能量到达率变化曲线
Figure 7. Curves of average transmission delay with energy arrival rate under batch packet transmission model
图 8 批量分组发送模型下能量消耗随能量到达率变化曲线
Figure 8. Curves of energy consumption curve with energy arrival rate under batch packet transmission model
表 1 仿真参数
Table 1. Simulation parameters
参数 取值 路侧单元蓄电池容量/个 100 路侧单元间隔距离/m 10 000 速度区间/(m·s-1) [16.67, 33.33] 期望速度/(m·s-1) 25 速度标准差/(m·s-1) 5.56 车辆到达率/(veh·s-1) 0.55或0.80 时隙长度/s 1 
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[1] 赵祥模, 惠飞, 史昕, 等. 泛在交通信息服务系统的概念、架构与关键技术[J]. 交通运输工程学报, 2014, 14(4): 105-115. http://transport.chd.edu.cn/article/id/201404013ZHAO Xiang-mo, HUI Fei, SHI Xin, et al. Concept, architecture and challenging technologies of ubiquitous traffic information service system[J]. Journal of Traffic and Transportation Engineering, 2014, 14(4): 105-115. (in Chinese). http://transport.chd.edu.cn/article/id/201404013 [2] LI C L, ZHANG Y, LUAN T H, et al. Building transmission backbone for highway vehicular networks: framework and analysis[J]. IEEE Transactions on Vehicular Technology, 2018, 67(9): 8709-8722. doi: 10.1109/TVT.2018.2844471 [3] HE Jian-ping, CAI Lin, PAN Jian-ping, et al. Delay analysis and routing for two dimensional VANETs using carry-and-forward mechanism[J]. IEEE Transactions on Mobile Computing, 2017, 16(7): 1830-1841. doi: 10.1109/TMC.2016.2607748 [4] WANG Yuan-jie, LIU Yin-sheng, ZHANG Jia-yi, et al. Cooperative store-carry-forward scheme for intermittently connected vehicular networks[J]. IEEE Transactions on Vehicular Technology, 2017, 66(1): 777-784. [5] 李骁驰, 徐志刚, 陈婷, 等. 考虑网络拥堵与系统公平的车载异构网络选择方法[J]. 交通运输工程学报, 2019, 19(3): 178-190. doi: 10.3969/j.issn.1671-1637.2019.03.018LI Xiao-chi, XU Zhi-gang, CHEN Ting, et al. Heterogeneous vehicular network selection method considering network congestion and system fairness[J]. Journal of Traffic and Transportation Engineering, 2019, 19(3): 178-190. (in Chinese). doi: 10.3969/j.issn.1671-1637.2019.03.018 [6] HUANG Li-jie, JIANG Hai, ZHANG Zhou, et al. Efficient data traffic forwarding for infrastructure-to-infrastructure communications in VANETs[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 19(3): 839-853. doi: 10.1109/TITS.2017.2705047 [7] CARKHUFF B G, DEMIREV P A, SRINIVASAN R. Impedance-based battery management system for safety monitoring of lithiumion batteries[J]. IEEE Transactions on Industrial Electronics, 2018, 65(8): 6497-6504. doi: 10.1109/TIE.2017.2786199 [8] ATALLAH R, KHABBAZ M, ASSI C. Energy harvesting in vehicular networks: a contemporary survey[J]. IEEE Wireless Communications, 2016, 23(2): 70-77. doi: 10.1109/MWC.2016.7462487 [9] ZHANG Shan, ZHANG Ning, FANG Xiao-jie, et al. Self-sustaining caching stations: towards cost-effective 5G-enabled vehicular networks[J]. IEEE Communications Magazine, 2017, 55(11): 202-208. doi: 10.1109/MCOM.2017.1700129 [10] KU Y J, CHIANG P H, DEY S. Quality of service optimization for vehicular edge computing with solar-powered road side units[C]//IEEE. 27th International Conference on Computer Communications and Networks. New York: IEEE, 2018: 1-10. [11] PATRA M, MURTHY C S R. Performance evaluation of joint placement and sleep scheduling of grid-connected solar powered road side units in vehicular networks[J]. IEEE Transactions on Green Communications and Networking, 2018, 2(4): 1197-1209. doi: 10.1109/TGCN.2018.2864152 [12] NIKOOKARAN N, KARAKOSTAS G, TODD T D. Combining capital and operating expenditure costs in vehicular roadside unit placement[J]. IEEE Transactions on Vehicular Technology, 2017, 66(8): 7317-7331. doi: 10.1109/TVT.2017.2665480 [13] KHEZRIAN A, TODD T D, KARAKOSTAS G, et al. Energy-efficient scheduling in green vehicular infrastructure with multiple roadside units[J]. IEEE Transactions on Vehicular Technology, 2015, 64(5): 1942-1957. doi: 10.1109/TVT.2014.2333665 [14] ATALLAH R F, ASSI C M, YU Jia-yuan. A reinforcement learning technique for optimizing downlink scheduling in an energy-limited vehicular network[J]. IEEE Transactions on Vehicular Technology, 2017, 66(6): 4592-4601. doi: 10.1109/TVT.2016.2622180 [15] WASSIM S A, WESSAM A, MOUNIR B. Offline and online scheduling algorithms for energy harvesting RSUs in VANETs[J]. IEEE Transactions on Vehicular Technology, 2018, 67(7): 6370-6382. doi: 10.1109/TVT.2018.2797002 [16] AZIMIFAR M, TODD T D, AMIR K, et al. Vehicle-to-vehicle forwarding in green roadside infrastructure[J]. IEEE Transactions on Vehicular Technology, 2016, 65(2): 780-795. doi: 10.1109/TVT.2015.2402177 [17] HAMMAD A A, TODD T D, KARAKOSTA S. Variable-bit-rate transmission schedule generation in green vehicular roadside units[J]. IEEE Transactions on Vehicular Technology, 2016, 65(3): 1590-1604. doi: 10.1109/TVT.2015.2410798 [18] ALI Q I. Event driven duty cycling: an efficient power management scheme for a solar-energy harvested road side unit[J]. IET Electrical Systems in Transportation, 2016, 6(3): 222-235. doi: 10.1049/iet-est.2015.0036 [19] ALI Q I. Enhanced power management scheme for embedded road side units[J]. IET Computers and Digital Techniques, 2016, 10(4): 174-185. doi: 10.1049/iet-cdt.2015.0135 [20] ALI Q I. GVANET project: an efficient deployment of a self-powered, reliable and secured VANET infrastructure[J]. IET Wireless Sensor Systems, 2018, 8(6): 313-322. doi: 10.1049/iet-wss.2018.5112 [21] ATALLAH R F, KHABBAZ M J, ASSI C M. Modeling and performance analysis of medium access control schemes for drive-thru internet access provisioning systems[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(6): 3238-3248. doi: 10.1109/TITS.2015.2440447 [22] KHABBAZ M J, ALAZEMI H M K, ASSI C M. Delay-aware data delivery in vehicular intermittently connected networks[J]. IEEE Transactions on Communications, 2013, 61(3): 1134-1143. doi: 10.1109/TCOMM.2012.122712.120222 [23] RAMAIYAN V, ALTMAN E, KUMAR A. Delay optimal scheduling in a two-hop vehicular relay network[J]. Mobile Networks and Applications, 2010, 15(1): 97-111. doi: 10.1007/s11036-009-0172-7 [24] KHABBAZ M J, FAWAZ W F, ASSI C M. A simple free-flow traffic model for vehicular intermittently connected networks[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(3): 1312-1326. doi: 10.1109/TITS.2012.2188519 [25] 代亮, 张亚楠, 钱超, 等. 基于车辆载带中继的路边单元突发业务分组调度最优策略[J]. 自动化学报, DOI: 10.16383/j.aas.c190054.DA.I Liang, ZHANG Ya-nan, QIAN Chao, et al. Optimal packet scheduling strategy for roadside units' bursty traffic based on relaying vehicles[J]. Acta Automatica Sinica, DOI: 10.16383/j.aas.c190054.(inChinese). [26] PATRA M, THAKUR R, MURTHY C S R. Improving delay and energy efficiency of vehicular networks using mobile femto access points[J]. IEEE Transactions on Vehicular Technology, 2017, 66(2): 1496-1505. doi: 10.1109/TVT.2016.2563980 [27] ATALLAH R, KHABBAZ M, ASSI C. Multihop V2I communications: a feasibility study, modelling and performance analysis[J]. IEEE Transactions on Vehicular Technology, 2017, 66(3): 2801-2810. doi: 10.1109/TVT.2016.2586758 [28] 席利贺, 张欣, 耿聪, 等. 基于动态规划算法的增程式电动汽车能量管理策略优化[J]. 交通运输工程学报, 2018, 18(3): 148-156. http://transport.chd.edu.cn/article/id/201803015XI Li-he, ZHANG Xin, GENG Cong, et al. Energy management strategy optimization of extended-range electric vehicle based on dynamic programming[J]. Journal of Traffic and Transportation Engineering, 2018, 18(3): 148-156. (in Chinese). http://transport.chd.edu.cn/article/id/201803015 [29] WANG Meng, LIU Juan, CHEN Wei. On delay-power tradeoff of rate adaptive wireless communications with random arrivals[C]//IEEE. 2017 IEEE Global Communications Conference. New York: IEEE, 2017: 1-6. [30] KHABBAZ M J, FAWAZ W F, ASSI C M. Probabilistic bundle relaying schemes in two-hop vehicular delay tolerant networks[J]. IEEE Communications Letters, 2011, 15(3): 281-283. doi: 10.1109/LCOMM.2011.011011.102512 -
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