Page 345 - 《软件学报》2026年第1期
P. 345

342                                                        软件学报  2026  年第  37  卷第  1  期


                     28th ACM Int’l Conf. on Architectural Support for Programming Languages and Operating Systems, Vol. 3. Vancouver: ACM, 2023.
                     392–403. [doi: 10.1145/3582016.3582043]
                 [51]   Tao B, Chabra O, Janveja I, Gupta I, Vasisht D. Known knowns and unknowns: Near-realtime earth observation via query bifurcation in
                     serval. In: Proc. of the 21st USENIX Symp. on Networked Systems Design and Implementation. Santa: USENIX, 2024. 809–824.
                 [52]   Wang SG, Zhang QY, Xing RL, Qi F, Xu MW. The first verification test of space-ground collaborative intelligence via cloud-native
                     satellites. China Communications, 2024, 21(4): 208–217. [doi: 10.23919/JCC.fa.2022-0422.202404]
                 [53]   Ji JH, Zhong BJ, Wu QH, Ma KK. A channel-wise multi-scale network for single image super-resolution. IEEE Signal Processing Letters,
                     2024, 31: 805–809. [doi: 10.1109/LSP.2024.3372781]
                 [54]   Wang XD, Li SF, Kallidromitis K, Kato Y, Kozuka K, Darrell T. Hierarchical open-vocabulary universal image segmentation. In: Proc.
                     of  the  37th  Int’l  Conf.  on  Neural  Information  Processing  Systems.  New  Orleans:  Curran  Associates  Inc.,  2023.  936.  [doi:  10.5555/
                     3666122.3667058]
                 [55]   Zhang QY, Yuan X, Xing RL, Zhang YR, Zheng ZM, Ma X, Xu MW, Dustdar S, Wang SG. Resource-efficient in-orbit detection of earth
                     objects.  In:  Proc.  of  the  2024  IEEE  Conf.  on  Computer  Communications.  Vancouver:  IEEE,  2024.  551–560.  [doi:  10.1109/
                     INFOCOM52122.2024]
                 [56]   So J, Hsieh K, Arzani B, Noghabi S, Avestimehr S, Chandra R. FedSpace: An efficient federated learning framework at satellites and
                     ground stations. arXiv:2202.01267, 2022.
                 [57]   Nguyen J, Malik K, Zhan HY, Yousefpour A, Rabbat M, Malek M, Huba D. Federated learning with buffered asynchronous aggregation.
                     In: Proc. of the 25th Int’l Conf. on Artificial Intelligence and Statistics. Valencia: PMLR, 2022. 3581–3607.
                 [58]   Yang C, Yuan JL, Wu YZ, Sun QB, Zhou A, Wang SG, Xu MW. Communication-efficient satellite-ground federated learning through
                     progressive weight quantization. IEEE Trans. on Mobile Computing, 2024, 23(9): 8999–9011. [doi: 10.1109/TMC.2024.3358804]
                 [59]   Razmi  N,  Matthiesen  B,  Dekorsy  A,  Popovski  P.  Ground-assisted  federated  learning  in  LEO  satellite  constellations.  IEEE  Wireless
                     Communications Letters, 2022, 11(4): 717–721. [doi: 10.1109/LWC.2022.3141120]
                 [60]   Tang FX, Wen C, Chen XH, Kato N. Federated learning for intelligent transmission with space-air-ground integrated network toward 6G.
                     IEEE Network, 2023, 37(2): 198–204. [doi: 10.1109/MNET.104.2100615]
                 [61]   Zhang HY, Zhao HB, Liu RK, Gao XQ, Xu SZ. Leader federated learning optimization using deep reinforcement learning for distributed
                     satellite edge intelligence. IEEE Trans. on Services Computing, 2024, 17(5): 2544–2557. [doi: 10.1109/TSC.2024.3376256]
                 [62]   Xiang  S,  Chen  YG,  Li  GL,  Xing  LN.  Review  on  satellite  autonomous  and  collaborative  task  scheduling  planning.  Acta  Automatica
                     Sinica, 2019, 45(2): 252–264 (in Chinese with English abstract). [doi: 10.16383/j.aas.c180068]
                 [63]   Zhao P, Chen ZM. An adapted genetic algorithm applied to satellite autonomous task scheduling. Chinese Space Science and Technology,
                     2016, 36(6): 47–54 (in Chinese with English abstract). [doi: 10.16708/j.cnki.1000-758X.2016.0064]
                 [64]   Damiani S, Verfaillie G, Charmeau MC. An earth watching satellite constellation: How to manage a team of watching agents with limited
                     communications. In: Proc. of the 4th Int’l Joint Conf. on Autonomous Agents and Multiagent Systems. New York: ACM, 2005. 455–462.
                     [doi: 10.1145/1082473.1082543]
                 [65]   Cao XL, Yang B, Shen YL, Yuen C, Zhang Y, Han Z, Poor HV, Hanzo L. Edge-assisted multi-layer offloading optimization of LEO
                     satellite-terrestrial integrated networks. IEEE Journal on Selected Areas in Communications, 2023, 41(2): 381–398. [doi: 10.1109/JSAC.
                     2022.3227032]
                 [66]   Zhu XM, Jiang CX. Delay optimization for cooperative multi-tier computing in integrated satellite-terrestrial networks. IEEE Journal on
                     Selected Areas in Communications, 2023, 41(2): 366–380. [doi: 10.1109/JSAC.2022.3227083]
                 [67]   Pang ZH. Research on collaborative mission planning method for high and low earth observation satellites [MS. Thesis]. Harbin: Harbin
                     Institute of Technology, 2013 (in Chinese).
                 [68]   Li JT, Zhang S, Liu XL, He RJ. Multi–objective evolutionary optimization for geostationary orbit satellite mission planning. Journal of
                     Systems Engineering and Electronics, 2017, 28(5): 934–945. [doi: 10.21629/JSEE.2017.05.11]
                 [69]   Zhang XY, Liu J, Zhang R, Huang YD, Tong JC, Xin N, Liu L, Xiong ZH. Energy-efficient computation peer offloading in satellite edge
                     computing networks. IEEE Trans. on Mobile Computing, 2024, 23(4): 3077–3091. [doi: 10.1109/TMC.2023.3269801]
                 [70]   Chen  Q,  Meng  WX,  Quek  TQS,  Chen  SY.  Multi-tier  hybrid  offloading  for  computation-aware  IoT  applications  in  civil  aircraft-
                     augmented SAGIN. IEEE Journal on Selected Areas in Communications, 2023, 41(2): 399–417. [doi: 10.1109/JSAC.2022.3227031]
                 [71]   Bensana E, Verfaillie G, Agnese J C, Bataille N. Exact and inexact methods for daily management of earth observation satellite. In: Proc.
                     of the 1996 Conf. on Space Mission Operations and Ground Data Systems. 1996. 394–507.
                 [72]   Sarkheyli A, Bagheri A, Ghorbani-Vaghei B, Askari-Moghadam R. Using an effective tabu search in interactive resources scheduling
                     problem for LEO satellites missions. Aerospace Science and Technology, 2013, 29(1): 287–295. [doi: 10.1016/j.ast.2013.04.001]
   340   341   342   343   344   345   346   347   348   349   350