Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource access, the macro eNodeB and UAV, both mounted with multi-access edge computing (MEC) servers, cooperatively make association...
Saved in:
| Published in | IEEE journal on selected areas in communications Vol. 39; no. 1; pp. 131 - 141 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0733-8716 1558-0008 |
| DOI | 10.1109/JSAC.2020.3036962 |
Cover
Loading…
| Abstract | In this paper, we investigate multi-dimensional resource management for unmanned aerial vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource access, the macro eNodeB and UAV, both mounted with multi-access edge computing (MEC) servers, cooperatively make association decisions and allocate proper amounts of resources to vehicles. Since there is no central controller, we formulate the resource allocation at the MEC servers as a distributive optimization problem to maximize the number of offloaded tasks while satisfying their heterogeneous quality-of-service (QoS) requirements, and then solve it with a multi-agent deep deterministic policy gradient (MADDPG)-based method. Through centrally training the MADDPG model offline, the MEC servers, acting as learning agents, then can rapidly make vehicle association and resource allocation decisions during the online execution stage. From our simulation results, the MADDPG-based method can converge within 200 training episodes, comparable to the single-agent DDPG (SADDPG)-based one. Moreover, the proposed MADDPG-based resource management scheme can achieve higher delay/QoS satisfaction ratios than the SADDPG-based and random schemes. |
|---|---|
| AbstractList | In this paper, we investigate multi-dimensional resource management for unmanned aerial vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource access, the macro eNodeB and UAV, both mounted with multi-access edge computing (MEC) servers, cooperatively make association decisions and allocate proper amounts of resources to vehicles. Since there is no central controller, we formulate the resource allocation at the MEC servers as a distributive optimization problem to maximize the number of offloaded tasks while satisfying their heterogeneous quality-of-service (QoS) requirements, and then solve it with a multi-agent deep deterministic policy gradient (MADDPG)-based method. Through centrally training the MADDPG model offline, the MEC servers, acting as learning agents, then can rapidly make vehicle association and resource allocation decisions during the online execution stage. From our simulation results, the MADDPG-based method can converge within 200 training episodes, comparable to the single-agent DDPG (SADDPG)-based one. Moreover, the proposed MADDPG-based resource management scheme can achieve higher delay/QoS satisfaction ratios than the SADDPG-based and random schemes. |
| Author | Shen, Xuemin Peng, Haixia |
| Author_xml | – sequence: 1 givenname: Haixia orcidid: 0000-0001-7206-4706 surname: Peng fullname: Peng, Haixia email: h27peng@uwaterloo.ca organization: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada – sequence: 2 givenname: Xuemin orcidid: 0000-0002-4140-287X surname: Shen fullname: Shen, Xuemin email: sshen@uwaterloo.ca organization: Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada |
| BookMark | eNp9kElPwzAQhS0EEqXwAxCXSJxTxmucY6hY1YLE0mvkJuPWUBywXSH-PamKOHDgNBq9783yDsiu7zwSckxhRCmUZ7eP1XjEgMGIA1elYjtkQKXUOQDoXTKAgvNcF1Ttk4MYXwCoEJoNyHK6XiWXVwv0KXtA520XGnzbdBM0wTu_yM5NxLYXY7futWxqvFlsEeez6cU4z4xvs-dqllcxuph6eIZL16xXJmR3mD678BoPyZ41q4hHP3VIni8vnsbX-eT-6mZcTfKGyzLljZWNtprqBqwBSoVqqeRsrnUJ8xIVM_1TlrbMGhQttgoLwZQEinLObSH4kJxu576H7mONMdUv_dm-X1kzUYDiUijWU8WWakIXY0BbNy6Z5DqfgnGrmkK9ibXexFpvYq1_Yu2d9I_zPbg3E77-9ZxsPQ4Rf_mSSQEl598nBoRy |
| CODEN | ISACEM |
| CitedBy_id | crossref_primary_10_1109_TAES_2024_3418944 crossref_primary_10_1109_JIOT_2023_3244783 crossref_primary_10_1016_j_phycom_2023_102240 crossref_primary_10_1109_JSAC_2023_3310048 crossref_primary_10_1109_TWC_2023_3310477 crossref_primary_10_1007_s12083_024_01730_x crossref_primary_10_1016_j_ins_2023_119523 crossref_primary_10_1109_TVT_2024_3493137 crossref_primary_10_1109_JSAC_2023_3310047 crossref_primary_10_1109_TSC_2022_3225473 crossref_primary_10_1109_TVT_2023_3338612 crossref_primary_10_1016_j_comcom_2023_06_008 crossref_primary_10_1109_OJVT_2021_3087355 crossref_primary_10_1016_j_adhoc_2023_103371 crossref_primary_10_1109_COMST_2024_3405075 crossref_primary_10_1007_s00521_023_08527_8 crossref_primary_10_1016_j_adhoc_2025_103801 crossref_primary_10_1109_TWC_2023_3342991 crossref_primary_10_1109_JIOT_2024_3366009 crossref_primary_10_1016_j_comnet_2024_110242 crossref_primary_10_1109_TWC_2023_3282909 crossref_primary_10_3390_s24165273 crossref_primary_10_1109_TWC_2023_3306880 crossref_primary_10_1109_TNSM_2024_3454758 crossref_primary_10_1109_COMST_2024_3372083 crossref_primary_10_1016_j_dcan_2023_11_010 crossref_primary_10_1109_TNSM_2024_3439389 crossref_primary_10_1109_JIOT_2021_3078514 crossref_primary_10_1109_JSEN_2024_3369038 crossref_primary_10_1109_TCOMM_2022_3220870 crossref_primary_10_1109_JSEN_2023_3283413 crossref_primary_10_1109_JIOT_2021_3128636 crossref_primary_10_1109_TCC_2021_3117604 crossref_primary_10_1109_TVT_2024_3402222 crossref_primary_10_1109_TITS_2022_3198507 crossref_primary_10_1109_MWC_121_2100071 crossref_primary_10_1109_JIOT_2023_3264253 crossref_primary_10_1109_JIOT_2024_3385414 crossref_primary_10_3390_math11061556 crossref_primary_10_1109_JIOT_2023_3326820 crossref_primary_10_1109_TIV_2022_3227367 crossref_primary_10_1038_s41598_024_67886_x crossref_primary_10_1109_TITS_2024_3422039 crossref_primary_10_1016_j_ins_2024_121790 crossref_primary_10_1145_3712599 crossref_primary_10_1007_s00521_021_05766_5 crossref_primary_10_1109_TCE_2023_3338745 crossref_primary_10_3390_fi17020050 crossref_primary_10_1109_TSC_2023_3347741 crossref_primary_10_1109_JIOT_2023_3287737 crossref_primary_10_1109_TICPS_2023_3311394 crossref_primary_10_1109_MWC_101_2100056 crossref_primary_10_1109_ACCESS_2022_3218134 crossref_primary_10_1109_JIOT_2023_3240173 crossref_primary_10_1109_JIOT_2023_3287187 crossref_primary_10_1109_TWC_2023_3268082 crossref_primary_10_1016_j_jnca_2022_103439 crossref_primary_10_1109_JIOT_2024_3487913 crossref_primary_10_1109_LWC_2022_3227033 crossref_primary_10_1109_TVT_2022_3232806 crossref_primary_10_1109_JIOT_2023_3337262 crossref_primary_10_1109_TMC_2023_3247579 crossref_primary_10_1109_TVT_2022_3221485 crossref_primary_10_1016_j_adhoc_2024_103434 crossref_primary_10_1016_j_compeleceng_2022_108278 crossref_primary_10_1109_TMC_2024_3432491 crossref_primary_10_1109_TCOMM_2024_3454702 crossref_primary_10_1109_JIOT_2024_3447090 crossref_primary_10_1109_TII_2023_3292522 crossref_primary_10_1109_JIOT_2023_3292387 crossref_primary_10_1016_j_comcom_2023_07_006 crossref_primary_10_1002_dac_6107 crossref_primary_10_3390_a16070354 crossref_primary_10_1109_TCOMM_2022_3222460 crossref_primary_10_1109_TVT_2023_3335663 crossref_primary_10_1016_j_aap_2023_107179 crossref_primary_10_1109_TWC_2024_3468162 crossref_primary_10_1007_s11042_024_18176_1 crossref_primary_10_1016_j_comcom_2022_05_004 crossref_primary_10_1109_JIOT_2024_3418882 crossref_primary_10_3390_electronics13224401 crossref_primary_10_1109_JIOT_2023_3268316 crossref_primary_10_1109_TII_2022_3164395 crossref_primary_10_3390_math11030760 crossref_primary_10_1109_JIOT_2022_3161571 crossref_primary_10_1109_JIOT_2023_3241087 crossref_primary_10_1109_JIOT_2022_3228863 crossref_primary_10_1109_OJCOMS_2024_3380509 crossref_primary_10_1109_TITS_2021_3117974 crossref_primary_10_1109_TMC_2024_3383041 crossref_primary_10_1155_2021_5051328 crossref_primary_10_1109_JIOT_2022_3196842 crossref_primary_10_1016_j_cosrev_2025_100734 crossref_primary_10_26599_TST_2024_9010142 crossref_primary_10_1109_JIOT_2023_3345853 crossref_primary_10_1109_TWC_2023_3260304 crossref_primary_10_3390_computers12030063 crossref_primary_10_3390_electronics12122708 crossref_primary_10_1109_TR_2022_3192020 crossref_primary_10_1016_j_comnet_2024_110279 crossref_primary_10_1109_TIFS_2024_3423428 crossref_primary_10_1109_TVT_2023_3271613 crossref_primary_10_1155_2022_1177544 crossref_primary_10_1016_j_comnet_2024_111006 crossref_primary_10_1109_TMC_2022_3141080 crossref_primary_10_1016_j_phycom_2025_102621 crossref_primary_10_1109_TCDS_2023_3246107 crossref_primary_10_1007_s11276_021_02789_7 crossref_primary_10_1109_TWC_2024_3392608 crossref_primary_10_1007_s42486_024_00159_8 crossref_primary_10_1109_TCCN_2024_3391318 crossref_primary_10_1016_j_eswa_2023_120406 crossref_primary_10_1109_COMST_2022_3224279 crossref_primary_10_1145_3711900 crossref_primary_10_1016_j_comcom_2024_107993 crossref_primary_10_1109_TWC_2023_3245637 crossref_primary_10_1109_TWC_2023_3335597 crossref_primary_10_1109_TWC_2021_3126147 crossref_primary_10_1109_TWC_2022_3153316 crossref_primary_10_1002_sat_1517 crossref_primary_10_1109_MNET_009_2100585 crossref_primary_10_1109_TMC_2024_3439016 crossref_primary_10_1016_j_jestch_2024_101699 crossref_primary_10_1109_TR_2024_3399389 crossref_primary_10_1109_TCE_2024_3426513 crossref_primary_10_1007_s11276_024_03804_3 crossref_primary_10_3233_JIFS_233819 crossref_primary_10_1109_JIOT_2024_3373225 crossref_primary_10_3390_electronics14010192 crossref_primary_10_1016_j_adhoc_2023_103341 crossref_primary_10_3390_app12010426 crossref_primary_10_1109_LWC_2023_3294749 crossref_primary_10_1109_TITS_2023_3342271 crossref_primary_10_1109_JIOT_2022_3155667 crossref_primary_10_1109_TMC_2024_3366186 crossref_primary_10_1109_TVT_2021_3134272 crossref_primary_10_1109_JSYST_2024_3439746 crossref_primary_10_1016_j_comnet_2024_110615 crossref_primary_10_1109_TWC_2023_3248962 crossref_primary_10_1109_JSAC_2021_3118352 crossref_primary_10_1109_TCOMM_2022_3208113 crossref_primary_10_1109_TCOMM_2023_3274165 crossref_primary_10_1109_TNSM_2024_3434997 crossref_primary_10_1109_TITS_2022_3190280 crossref_primary_10_1109_ACCESS_2022_3202956 crossref_primary_10_1109_JSAC_2024_3460053 crossref_primary_10_1109_JIOT_2023_3327656 crossref_primary_10_1109_JIOT_2022_3156100 crossref_primary_10_1109_TITS_2023_3314929 crossref_primary_10_1109_TNSE_2022_3153172 crossref_primary_10_1109_TSC_2023_3247049 crossref_primary_10_1016_j_iot_2024_101342 crossref_primary_10_3390_rs15164046 crossref_primary_10_3390_drones8090485 crossref_primary_10_1109_JIOT_2023_3339514 crossref_primary_10_1109_ACCESS_2021_3070336 crossref_primary_10_1109_TMC_2023_3289940 crossref_primary_10_1109_TCOMM_2022_3211083 crossref_primary_10_1109_TGCN_2021_3099523 crossref_primary_10_1109_TII_2022_3224986 crossref_primary_10_1016_j_jksuci_2022_05_016 crossref_primary_10_1109_TMC_2024_3470831 crossref_primary_10_3390_s23167083 crossref_primary_10_1109_ACCESS_2023_3331752 crossref_primary_10_1109_TWC_2022_3210955 crossref_primary_10_3390_s24227328 crossref_primary_10_1109_TSC_2024_3377156 crossref_primary_10_1109_JIOT_2023_3294535 crossref_primary_10_1109_OJCOMS_2023_3243870 crossref_primary_10_1109_TWC_2022_3216049 crossref_primary_10_3390_electronics12061304 crossref_primary_10_1016_j_comnet_2024_110873 crossref_primary_10_1109_JIOT_2023_3263574 crossref_primary_10_3390_s24248014 crossref_primary_10_1109_MRA_2022_3163081 crossref_primary_10_1109_TVT_2024_3429507 crossref_primary_10_1109_TVT_2023_3347744 crossref_primary_10_26599_TST_2024_9010071 crossref_primary_10_1016_j_dcan_2023_04_004 crossref_primary_10_1109_JSAC_2024_3459089 crossref_primary_10_3390_drones7100619 crossref_primary_10_1109_TITS_2021_3082539 crossref_primary_10_1109_TVT_2022_3163430 crossref_primary_10_1109_TCOMM_2022_3229033 crossref_primary_10_1109_MWC_010_2300200 crossref_primary_10_1109_JIOT_2023_3285950 crossref_primary_10_1016_j_future_2023_03_038 crossref_primary_10_1109_TMC_2024_3367124 crossref_primary_10_1109_TWC_2023_3235997 crossref_primary_10_1109_TVT_2023_3262261 crossref_primary_10_1016_j_comcom_2024_107953 crossref_primary_10_1016_j_jksuci_2022_10_011 crossref_primary_10_1109_TCOMM_2023_3331029 crossref_primary_10_1016_j_comcom_2023_01_009 crossref_primary_10_1109_TNSM_2023_3300962 crossref_primary_10_1109_TGCN_2023_3298039 crossref_primary_10_1109_TITS_2021_3088862 crossref_primary_10_1109_TITS_2021_3129837 crossref_primary_10_1109_JIOT_2022_3228246 crossref_primary_10_1145_3604933 crossref_primary_10_32604_cmc_2023_037154 crossref_primary_10_1016_j_vehcom_2025_100895 crossref_primary_10_1109_JIOT_2023_3320796 crossref_primary_10_1109_COMST_2022_3199544 crossref_primary_10_1142_S2301385024420019 crossref_primary_10_1109_COMST_2021_3106401 crossref_primary_10_1109_JIOT_2021_3063686 crossref_primary_10_1109_COMST_2023_3312221 crossref_primary_10_1109_TMC_2023_3276314 crossref_primary_10_1016_j_dsp_2023_104127 crossref_primary_10_1109_TNSM_2022_3217320 crossref_primary_10_3390_electronics12234763 crossref_primary_10_1109_JIOT_2022_3199382 crossref_primary_10_1109_JIOT_2024_3418488 crossref_primary_10_1109_TMC_2024_3439556 crossref_primary_10_1109_JIOT_2023_3305708 crossref_primary_10_1016_j_vehcom_2025_100889 crossref_primary_10_2139_ssrn_4111779 crossref_primary_10_3390_drones7090579 crossref_primary_10_1109_COMST_2022_3175453 crossref_primary_10_1109_TNSE_2023_3310055 crossref_primary_10_1109_JSTSP_2021_3120872 crossref_primary_10_1109_TWC_2024_3458194 crossref_primary_10_1016_j_dcan_2024_10_005 crossref_primary_10_1109_JIOT_2022_3230786 crossref_primary_10_1109_TWC_2022_3215795 crossref_primary_10_3390_drones7080534 crossref_primary_10_1109_MWC_003_2100690 crossref_primary_10_1109_JIOT_2021_3095677 crossref_primary_10_1016_j_icte_2022_07_002 crossref_primary_10_1109_ACCESS_2024_3418900 crossref_primary_10_1109_COMST_2023_3323344 crossref_primary_10_1109_JIOT_2022_3155608 crossref_primary_10_1109_JIOT_2024_3445171 crossref_primary_10_1109_JIOT_2023_3300700 crossref_primary_10_1109_TVT_2023_3259688 crossref_primary_10_1109_TWC_2023_3291692 crossref_primary_10_1109_TNSE_2024_3391289 crossref_primary_10_3390_en16124655 crossref_primary_10_1109_JIOT_2023_3290145 crossref_primary_10_1109_TNSE_2024_3371434 crossref_primary_10_1109_JSAC_2023_3310062 crossref_primary_10_1360_SSI_2023_0177 crossref_primary_10_1016_j_neucom_2022_09_154 crossref_primary_10_1109_TCCN_2023_3234290 crossref_primary_10_1109_TVT_2021_3083255 crossref_primary_10_1007_s42486_023_00146_5 crossref_primary_10_1109_TVT_2024_3435393 crossref_primary_10_1109_TITS_2024_3440391 crossref_primary_10_1007_s12083_021_01235_x crossref_primary_10_1016_j_eswa_2024_123152 crossref_primary_10_1016_j_comnet_2024_110469 crossref_primary_10_1109_TVT_2023_3256067 crossref_primary_10_1109_IOTM_001_2300067 crossref_primary_10_1109_TVT_2023_3327604 crossref_primary_10_1109_JIOT_2024_3421529 crossref_primary_10_1186_s13677_025_00738_9 crossref_primary_10_1109_TNET_2023_3342020 crossref_primary_10_1109_JIOT_2024_3441236 crossref_primary_10_1016_j_dcan_2022_12_016 crossref_primary_10_1109_JIOT_2021_3081626 crossref_primary_10_1109_JSAC_2023_3310080 crossref_primary_10_1016_j_jnca_2024_103834 crossref_primary_10_1145_3715319 crossref_primary_10_1109_ACCESS_2022_3210337 crossref_primary_10_1109_ACCESS_2021_3112963 crossref_primary_10_3390_rs15164059 crossref_primary_10_1109_TVT_2022_3232841 crossref_primary_10_1016_j_comnet_2022_109430 crossref_primary_10_1109_TVT_2023_3272648 crossref_primary_10_1007_s12083_021_01245_9 crossref_primary_10_1109_TCOMM_2024_3356795 |
| Cites_doi | 10.1109/TWC.2019.2928539 10.1109/ACCESS.2018.2878552 10.1109/TVT.2019.2929741 10.1109/TVT.2018.2859740 10.1109/TWC.2019.2935201 10.1109/ACCESS.2018.2872753 10.1109/JSAC.2020.3000416 10.1109/TNSE.2020.2978856 10.1109/TVT.2019.2897134 10.1109/JIOT.2018.2878435 10.1109/JSAC.2019.2933973 10.1109/TVT.2020.2993849 10.1109/AiDAS47888.2019.8970890 10.1109/TVT.2019.2935877 10.1109/JIOT.2018.2878876 10.1109/TMC.2020.2984261 10.1109/JSAC.2018.2864426 10.1109/TITS.2019.2922656 10.1109/TVT.2018.2833427 10.1109/TVT.2017.2723430 10.1109/JPROC.2019.2951169 10.1109/TWC.2019.2927313 10.1109/TITS.2019.2893067 10.1109/JSAC.2019.2933962 10.1109/MNET.2019.1800222 10.1109/OJVT.2020.2965100 10.1109/TVT.2018.2890685 10.1109/JSAC.2020.2986615 10.1109/MCOM.2018.1701092 10.1109/JPROC.2019.2957798 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 |
| DBID | 97E RIA RIE AAYXX CITATION 7SP 8FD L7M |
| DOI | 10.1109/JSAC.2020.3036962 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Electronics & Communications Abstracts Technology Research Database Advanced Technologies Database with Aerospace |
| DatabaseTitle | CrossRef Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts |
| DatabaseTitleList | Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1558-0008 |
| EndPage | 141 |
| ExternalDocumentID | 10_1109_JSAC_2020_3036962 9254093 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: research grants from the Natural Sciences and Engineering Research Council (NSERC) of Canada funderid: 10.13039/501100000038 |
| GroupedDBID | -~X .DC 0R~ 29I 3EH 4.4 41~ 5GY 5VS 6IK 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACGFO ACGFS ACIWK ACNCT ADRHT AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 DU5 EBS EJD HZ~ H~9 IBMZZ ICLAB IES IFIPE IFJZH IPLJI JAVBF LAI M43 O9- OCL P2P RIA RIE RNS TN5 VH1 AAYOK AAYXX CITATION RIG 7SP 8FD L7M |
| ID | FETCH-LOGICAL-c359t-cf5c8f818c0fa01146d1532b8890b9e62a558f1d2fae4ded6e7426501e5b3f743 |
| IEDL.DBID | RIE |
| ISSN | 0733-8716 |
| IngestDate | Mon Jun 30 10:23:54 EDT 2025 Tue Jul 01 02:06:31 EDT 2025 Thu Apr 24 23:05:03 EDT 2025 Wed Aug 27 02:32:19 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c359t-cf5c8f818c0fa01146d1532b8890b9e62a558f1d2fae4ded6e7426501e5b3f743 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ORCID | 0000-0002-4140-287X 0000-0001-7206-4706 |
| PQID | 2470635462 |
| PQPubID | 85481 |
| PageCount | 11 |
| ParticipantIDs | crossref_citationtrail_10_1109_JSAC_2020_3036962 crossref_primary_10_1109_JSAC_2020_3036962 proquest_journals_2470635462 ieee_primary_9254093 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2021-Jan. 2021-1-00 20210101 |
| PublicationDateYYYYMMDD | 2021-01-01 |
| PublicationDate_xml | – month: 01 year: 2021 text: 2021-Jan. |
| PublicationDecade | 2020 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | IEEE journal on selected areas in communications |
| PublicationTitleAbbrev | J-SAC |
| PublicationYear | 2021 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | ref13 ref12 ref15 ref11 ref32 ref10 (ref21) 2020 ref2 ref1 ref39 ref17 ref38 ref16 ref19 ref18 (ref34) 2020 (ref37) 2020 foerster (ref36) 2016 ref24 ref23 ref26 ref20 ref22 puterman (ref30) 2014 (ref14) 2020 ng (ref33) 1999; 99 ref28 lowe (ref31) 2017 ref27 ref29 ref7 ref9 ref4 ref3 ref6 ref5 lillicrap (ref35) 2016 ref40 peng (ref25) 2020 peng (ref8) 2020 |
| References_xml | – start-page: 1 year: 2020 ident: ref25 article-title: DDPG-based resource management for MEC/UAV-assisted vehicular networks publication-title: Proc IEEE VTC Fall – volume: 99 start-page: 278 year: 1999 ident: ref33 article-title: Policy invariance under reward transformations: Theory and application to reward shaping publication-title: Proc ICML – ident: ref10 doi: 10.1109/TWC.2019.2928539 – ident: ref7 doi: 10.1109/ACCESS.2018.2878552 – ident: ref3 doi: 10.1109/TVT.2019.2929741 – ident: ref39 doi: 10.1109/TVT.2018.2859740 – ident: ref28 doi: 10.1109/TWC.2019.2935201 – ident: ref12 doi: 10.1109/ACCESS.2018.2872753 – ident: ref24 doi: 10.1109/JSAC.2020.3000416 – year: 2020 ident: ref8 article-title: Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks publication-title: IEEE Transactions on Network Science and Engineering doi: 10.1109/TNSE.2020.2978856 – ident: ref4 doi: 10.1109/TVT.2019.2897134 – ident: ref27 doi: 10.1109/JIOT.2018.2878435 – ident: ref26 doi: 10.1109/JSAC.2019.2933973 – start-page: 6379 year: 2017 ident: ref31 article-title: Multi-agent actor-critic for mixed cooperative-competitive environments publication-title: Proc Adv Neural Inf Process Syst – ident: ref23 doi: 10.1109/TVT.2020.2993849 – ident: ref40 doi: 10.1109/AiDAS47888.2019.8970890 – ident: ref16 doi: 10.1109/TVT.2019.2935877 – ident: ref9 doi: 10.1109/JIOT.2018.2878876 – year: 2014 ident: ref30 publication-title: Markov Decision Processes Discrete Stochastic Dynamic Programming – ident: ref15 doi: 10.1109/TMC.2020.2984261 – ident: ref29 doi: 10.1109/JSAC.2018.2864426 – ident: ref13 doi: 10.1109/TITS.2019.2922656 – start-page: 2137 year: 2016 ident: ref36 article-title: Learning to communicate with deep multi-agent reinforcement learning publication-title: Proc Adv Neural Inf Process Syst – ident: ref5 doi: 10.1109/TVT.2018.2833427 – ident: ref38 doi: 10.1109/TVT.2017.2723430 – ident: ref17 doi: 10.1109/JPROC.2019.2951169 – start-page: 1 year: 2016 ident: ref35 article-title: Continuous control with deep reinforcement learning publication-title: Proc ICLR – ident: ref20 doi: 10.1109/TWC.2019.2927313 – ident: ref1 doi: 10.1109/TITS.2019.2893067 – year: 2020 ident: ref21 publication-title: Building an Ecosystem for Responsible Drone Use and Development on Microsoft Azure – ident: ref6 doi: 10.1109/JSAC.2019.2933962 – ident: ref11 doi: 10.1109/MNET.2019.1800222 – ident: ref32 doi: 10.1109/OJVT.2020.2965100 – year: 2020 ident: ref37 publication-title: PTV Vissim – ident: ref19 doi: 10.1109/TVT.2018.2890685 – year: 2020 ident: ref34 publication-title: Deep Reinforcement Learning Models Tips & Tricks for Writing Reward Functions – ident: ref18 doi: 10.1109/JSAC.2020.2986615 – year: 2020 ident: ref14 publication-title: Why Autonomous Vehicles Will Rely on Edge Computing and Not the Cloud? – ident: ref22 doi: 10.1109/MCOM.2018.1701092 – ident: ref2 doi: 10.1109/JPROC.2019.2957798 |
| SSID | ssj0014482 |
| Score | 2.7055008 |
| Snippet | In this paper, we investigate multi-dimensional resource management for unmanned aerial vehicles (UAVs) assisted vehicular networks. To efficiently provide... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 131 |
| SubjectTerms | Decisions Delays Edge computing Learning Mobile computing multi-access edge computing multi-agent DDPG multi-dimensional resource management Multiagent systems Optimization Quality of service Resource allocation Resource management Servers Task analysis Training unmanned aerial vehicle Unmanned aerial vehicles Vehicles Vehicular networks Wireless communication |
| Title | Multi-Agent Reinforcement Learning Based Resource Management in MEC- and UAV-Assisted Vehicular Networks |
| URI | https://ieeexplore.ieee.org/document/9254093 https://www.proquest.com/docview/2470635462 |
| Volume | 39 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV07T8MwED5BJxh4FUR5yQMTwiV1YjceS0WFkMoAFLFFiX0GBAoI2oVfz9lJy1OILYMdWfkuvvvuCbDv_CATpSRHqSOeKEP3YAcJkFSjcCkpnDBjaXiuTkfJ2Y28mYPDWS0MIobkM2z7xxDLt09m4l1lR5rYDDHweZgn4lbVas0iBkQzQsSgG8fck4A6gtmJ9NHZZa9PTFAQQY38-DrxRQeFoSo_buKgXgbLMJwerMoqeWhPxkXbvH3r2fjfk6_AUm1nsl4lGKswh-UaLH7qPtiEu1B8y3u-uIpdYGihaoK3kNVdV2_ZMSk5y6Y-fvaRLMPuSzY86XOWl5aNeteccPYSY9k13t2H5FZ2XqWYv67DaHBy1T_l9eAFbmKpx9w4aVICKjWRyz1jUpYuRlGkqY4KjUrkUqauY4XLMbFoFRLBJlOvg7KIHdkkG9Aon0rcBEbvE06niUssfYFI5prWS3RK5mTK2bgF0RSKzNRdyf1wjMcssJNIZx69zKOX1ei14GC25blqyfHX4qZHY7awBqIFO1O8s_qnfc1E0iWDTSZKbP2-axsWhE9pCR6YHWiMXya4SzbJuNgLwvgOgXvbGA |
| linkProvider | IEEE |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1LT-MwEB7xOCx74LEs2vL0gRNal9SJTXwsFag82gNQxC1K7DEgVmEF7YVfz9hJy1OIWw52ZOWbeOabJ8C284NMlJIcpY54ogzdgy0kQFKNwqWkcMKMpV5fdQfJ8ZW8moK_k1oYRAzJZ9j0jyGWb-_NyLvKdjWxGWLg0zBLej_RVbXWJGZARCPEDPbimHsaUMcwW5HePT5vd4gLCqKokR9gJ95ooTBW5cNdHBTM4QL0xker8krumqNh0TRP77o2fvfsizBfW5qsXYnGEkxh-Qt-vuo_uAw3ofyWt315FTvD0ETVBH8hq_uuXrN9UnOWjb387CVdht2WrHfQ4SwvLRu0Lzkh7WXGsku8uQ3praxfJZk__obB4cFFp8vr0QvcxFIPuXHSpARVaiKXe86kLF2NokhTHRUalcilTF3LCpdjYtEqJIpNxl4LZRE7skpWYKa8L_EPMHqfcDpNXGLpC0Qy17ReolMyJ2POxg2IxlBkpu5L7sdj_MsCP4l05tHLPHpZjV4DdiZb_ldNOb5avOzRmCysgWjA-hjvrP5tHzOR7JHJJhMlVj_ftQU_uhe90-z0qH-yBnPCJ7gEf8w6zAwfRrhBFsqw2AyC-Qwrqd5o |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multi-Agent+Reinforcement+Learning+Based+Resource+Management+in+MEC-+and+UAV-Assisted+Vehicular+Networks&rft.jtitle=IEEE+journal+on+selected+areas+in+communications&rft.au=Peng%2C+Haixia&rft.au=Shen%2C+Xuemin&rft.date=2021-01-01&rft.issn=0733-8716&rft.eissn=1558-0008&rft.volume=39&rft.issue=1&rft.spage=131&rft.epage=141&rft_id=info:doi/10.1109%2FJSAC.2020.3036962&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_JSAC_2020_3036962 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0733-8716&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0733-8716&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0733-8716&client=summon |