{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T09:16:17Z","timestamp":1768814177157,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,2,21]],"date-time":"2019-02-21T00:00:00Z","timestamp":1550707200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The space information networks (SIN) have a series of characteristics, such as strong heterogeneity, multiple types of resources, and difficulty in management. Aiming at the problem of resource allocation in SIN, this paper firstly establishes a hierarchical and domain-controlled SIN architecture based on software-defined networking (SDN). On this basis, the transmission, caching, and computing resources of the whole network are managed uniformly. The Asynchronous Advantage Actor-Critic (A3C) algorithm in deep reinforcement learning is introduced to model the process of resource allocation. The simulation results show that the proposed scheme can effectively improve the expected benefits of unit resources and improve the resource utilization efficiency of the SIN.<\/jats:p>","DOI":"10.3390\/rs11040448","type":"journal-article","created":{"date-parts":[[2019,2,22]],"date-time":"2019-02-22T03:49:44Z","timestamp":1550807384000},"page":"448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Research on Resource Allocation Method of Space Information Networks Based on Deep Reinforcement Learning"],"prefix":"10.3390","volume":"11","author":[{"given":"Xiangli","family":"Meng","sequence":"first","affiliation":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"}]},{"given":"Lingda","family":"Wu","sequence":"additional","affiliation":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5296-1917","authenticated-orcid":false,"given":"Shaobo","family":"Yu","sequence":"additional","affiliation":[{"name":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,21]]},"reference":[{"key":"ref_1","unstructured":"Zhang, W. (2016). Topological Control Theory and Method of Space Information Network, PLA University Science and Technology."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1109\/JSAC.2018.2804045","article-title":"Multi-Resource Coordinate Scheduling for Earth Observation in Space Information Networks","volume":"36","author":"Wang","year":"2018","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_3","unstructured":"National Natural Science Foundation (2016, March 25). The Program Guidance of the Basic Theory and Key Technology Research of Space Information Network in 2016, Available online: http:\/\/www.nsfc.gov.cn\/publish\/portal0\/tab38\/info51946.htm."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1109\/MWC.2016.7422411","article-title":"Virtual multi-beamforming for distributed satellite clusters in space information networks","volume":"23","author":"Yu","year":"2016","journal-title":"IEEE Wirel. Commun."},{"key":"ref_5","first-page":"711","article-title":"On construction of China\u2019s space information network","volume":"40","author":"Li","year":"2015","journal-title":"Wuhan Univ. Inf. Sci. Ed."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/MNET.2016.7389832","article-title":"When big data meets software-defined networking: SDN for big data and big data for SDN","volume":"30","author":"Cui","year":"2016","journal-title":"IEEE Netw."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"14952","DOI":"10.1109\/ACCESS.2017.2726114","article-title":"SAT-FLOW: Multi-Strategy Flow Table Management for Software Defined Satellite Networks","volume":"5","author":"Li","year":"2017","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11235-017-0309-0","article-title":"Towards SDN\/NFV-enabled satellite networks","volume":"66","author":"Gardikis","year":"2017","journal-title":"Telecommun. Syst."},{"key":"ref_9","first-page":"1","article-title":"A Survey on Deep Reinforcement Learing","volume":"1","author":"Liu","year":"2018","journal-title":"Chin. J. Comp."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"Mnih","year":"2015","journal-title":"Nature"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Jennings, E., and Heckman, D. (2008, January 1\u20138). Performance Characterization of Space Communications and Navigation (SCaN) Network by Simulation. Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO.2008.4526335"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Vanderpoorten, J., Cohen, J., Moody, J., Cornell, C., Streland, A., and Breese, S. (November, January 29). Transformational Satellite Communications System (TSAT) lessons learned: Perspectives from TSAT program leaders. Proceedings of the 2012 IEEE Military Communications Conference, Orlando, FL, USA.","DOI":"10.1109\/MILCOM.2012.6415865"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sesena, J., Alfaro, A., and Munoz, S. (2009, January 9\u201311). Regulatory environment for the successful ISICOM development. Proceedings of the 2009 International Workshop on Satellite and Space Communications, Tuscany, Italy.","DOI":"10.1109\/IWSSC.2009.5286410"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Axford, R., Short, S., Shchupak, P., and Muhammad, N. (2008, January 16\u201319). Wideband Global SATCOM (WGS) earth terminal interoperability demonstrations. Proceedings of the 2012 IEEE Military Communications Conference, San Diego, CA, USA.","DOI":"10.1109\/MILCOM.2008.4753495"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Schroth, K., Burkhardt, N., Che, T.S., and Pisano, D. (November, January 29). IP networking over the AEHF MILSATCOM system. Proceedings of the 2012 IEEE Military Communications Conference, Orlando, FL, USA.","DOI":"10.1109\/MILCOM.2012.6415800"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/0952-1976(94)00062-R","article-title":"Heuristic scheduling of the DRS communication system","volume":"8","author":"Adinolfi","year":"1995","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1057\/palgrave.jors.2601575","article-title":"Algorithms for parallel machine scheduling: A case study of the tracking and data relay satellite system","volume":"54","author":"Rojanasoonthon","year":"2003","journal-title":"J. Oper. Res. Soc."},{"key":"ref_18","unstructured":"Gu, Z.S. (2008). Research on the Relay Satellite Dynamic Scheduling Problem Modeling and Optimizational Technology, National University of Defense Technology."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MCOM.2015.7060482","article-title":"Software defined networking and virtualization for broadband satellite networks","volume":"53","author":"Bertaux","year":"2015","journal-title":"IEEE Commun. Mag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.phycom.2015.10.007","article-title":"SDN\/NFV-enabled satellite communications networks: Opportunities, scenarios and challenges","volume":"18","author":"Koumaras","year":"2016","journal-title":"Phys. Commun."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Gopal, R., and Ravishankar, C. (2013, January 24\u201327). Software Defined Satellite Networks. Proceedings of the Aiaa International Communications Satellite Systems Conference, San Diego, CA, USA.","DOI":"10.2514\/6.2014-4480"},{"key":"ref_22","first-page":"224","article-title":"A framework of SDN-based satellits on-board switching networks","volume":"18","author":"Yu","year":"2017","journal-title":"J. PLA Univ. Sci. Tech. (Nat. Sci. Ed.)"},{"key":"ref_23","unstructured":"Zhu, S.Y. (2017). Research on Routing Algorithm of Space Network Based on SDN, Harbin Institute of Technology."},{"key":"ref_24","first-page":"63","article-title":"Multi-path Carrying Strategy in SDN-based Space Information Networks","volume":"46","author":"Tian","year":"2016","journal-title":"Radio Eng."},{"key":"ref_25","unstructured":"Tian, R. (2017). Research on Control Protocol and Routing Algorithms of Software Defined Space-Terrestrial Network, Beijing University of Posts and Telecommunications."},{"key":"ref_26","first-page":"2246","article-title":"Survey on software defined network research","volume":"30","author":"Zhang","year":"2013","journal-title":"Appl. Res. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1109\/COMST.2015.2506984","article-title":"Rules Placement Problem in OpenFlow Networks: A Survey","volume":"18","author":"Nguyen","year":"2016","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.physa.2017.09.042","article-title":"Measure the structure similarity of nodes in complex networks based on relative entropy","volume":"491","author":"Zhang","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_29","first-page":"804","article-title":"Analysis of Coverage Time and Handoff Number on LEO Satellite Comunication Systems","volume":"36","author":"Yang","year":"2014","journal-title":"J. Electron. Inf. Technol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1782","DOI":"10.1109\/TVT.2017.2763150","article-title":"Two-Phase Task Scheduling in Data Relay Satellite Systems","volume":"67","author":"Deng","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1472","DOI":"10.1109\/TNET.2012.2227338","article-title":"Estimating Instantaneous Cache Hit Ratio Using Markov Chain Analysis","volume":"21","author":"Gomaa","year":"2013","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_32","first-page":"126","article-title":"Web caching and Zipf-like distributions: Evidence and implications","volume":"1","author":"Breslau","year":"1999","journal-title":"Proc. IEEE INFOCOM"},{"key":"ref_33","unstructured":"Li, H.Q. (2008). Hardware Implementation of LEO Satellite Channel Characteristic Emulation, Harbin Institute of Technology."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.simpat.2018.06.003","article-title":"Caching Hit Probability and Compressive Sensing Perspective for Mobile Cellular Networks","volume":"87","author":"Theofanis","year":"2018","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_35","unstructured":"Daniel, G., Gerson, S., and Jordi, C. (2018). Advanced prefetching and caching of models with PrefetchML. Softw. Syst. Model., 1\u201322."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"11339","DOI":"10.1109\/TVT.2017.2737028","article-title":"Resource Allocation for Information-Centric Virtualized Heterogeneous Networks with In-Network Caching and Mobile Edge Computing","volume":"66","author":"Zhou","year":"2017","journal-title":"IEEE Trans Veh. Technol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/TVT.2017.2760281","article-title":"Integrated Networking, Caching and Computing for Connected Vehicles: A Deep Reinforcement Learning Approach","volume":"67","author":"He","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_38","first-page":"1402","article-title":"Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds","volume":"35","author":"Helma","year":"2018","journal-title":"J. Chem. Inf. Comput. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3306","DOI":"10.1364\/BOE.9.003306","article-title":"Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow","volume":"9","author":"Jiang","year":"2018","journal-title":"Biomed. Opt. Express"},{"key":"ref_40","unstructured":"Ying, H., Cheng, C.L., Richard, Y., and Zhu, H. (2018). Trust-based Social Networks with Computing, Caching and Communications: A Deep Reinforcement Learning Approach. IEEE Trans. Netw. Sci. Eng., 1\u201314."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/4\/448\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:33:46Z","timestamp":1760186026000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/4\/448"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,21]]},"references-count":40,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["rs11040448"],"URL":"https:\/\/doi.org\/10.3390\/rs11040448","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,21]]}}}