{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T10:01:57Z","timestamp":1742983317216,"version":"3.40.3"},"publisher-location":"Cham","reference-count":11,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030639402"},{"type":"electronic","value":"9783030639419"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-63941-9_1","type":"book-chapter","created":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T21:04:13Z","timestamp":1611867853000},"page":"3-15","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Collaborative Mobile Edge Caching Strategy Based on Deep Reinforcement Learning"],"prefix":"10.1007","author":[{"given":"Jianji","family":"Ren","sequence":"first","affiliation":[]},{"given":"Tingting","family":"Hou","sequence":"additional","affiliation":[]},{"given":"Shuai","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,29]]},"reference":[{"key":"1_CR1","unstructured":"ETSI. Mobile Edge Computing - Introductory Technical White Paper, September 2014"},{"key":"1_CR2","doi-asserted-by":"crossref","unstructured":"Dash, D., Kantere, V., Ailamaki, A.: An economic model for self-tuned cloud caching. In: 2009 IEEE 25th International Conference on Data Engineering. IEEE (2009)","DOI":"10.1109\/ICDE.2009.143"},{"key":"1_CR3","unstructured":"Lobo, A.R., Nadgir, D.K., Kuncolienkar, S.T.S.: Intelligent edge caching. U.S. Patent Application 13\/548,584[P]. 2014-1-16"},{"key":"1_CR4","doi-asserted-by":"crossref","unstructured":"Tran, T.X., Pandey, P., Hajisami. A., et al.: Collaborative multi-bitrate video caching and processing in mobile-edge computing networks. In: 2017 13th Annual Conference on Wireless On-Demand Network Systems and Services (WONS), pp. 165\u2013172. IEEE (2017)","DOI":"10.1109\/WONS.2017.7888772"},{"key":"1_CR5","doi-asserted-by":"crossref","unstructured":"Ndikumana, A., Ullah, S., LeAnh, T., et al.: Collaborative cache allocation and computation offloading in mobile edge computing. In: 2017 19th Asia-Pacific Network Operations and Management Symposium (APNOMS), pp. 366\u2013369. IEEE (2017)","DOI":"10.1109\/APNOMS.2017.8094149"},{"key":"1_CR6","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1007\/s11276-019-02125-0","volume":"26","author":"J Ren","year":"2020","unstructured":"Ren, J., Hou, T., Wang, H., et al.: Increasing network throughput based on dynamic caching policy at wireless access points. Wirel. Netw. 26, 1577\u20131585 (2020). https:\/\/doi.org\/10.1007\/s11276-019-02125-0","journal-title":"Wirel. Netw."},{"key":"1_CR7","doi-asserted-by":"crossref","unstructured":"Zhong, C., Gursoy, M.C., Velipasalar, S.: A deep reinforcement learning-based framework for content caching. In: 2018 52nd Annual Conference on Information Sciences and Systems (CISS), pp. 1\u20136. IEEE (2018)","DOI":"10.1109\/CISS.2018.8362276"},{"issue":"4","key":"1_CR8","doi-asserted-by":"publisher","first-page":"1024","DOI":"10.1109\/TCCN.2019.2936193","volume":"5","author":"A Sadeghi","year":"2019","unstructured":"Sadeghi, A., Wang, G., Giannakis, G.B.: Deep reinforcement learning for adaptive caching in hierarchical content delivery networks. IEEE Trans. Cogn. Commun. Netw. 5(4), 1024\u20131033 (2019). https:\/\/doi.org\/10.1109\/TCCN.2019.2936193","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"issue":"5","key":"1_CR9","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1109\/MNET.2019.1800286","volume":"33","author":"X Wang","year":"2019","unstructured":"Wang, X., Han, Y., Wang, C., et al.: In-edge AI: intelligentizing mobile edge computing, caching and communication by federated learning[J]. IEEE Netw. 33(5), 156\u2013165 (2019)","journal-title":"IEEE Netw."},{"key":"1_CR10","doi-asserted-by":"publisher","first-page":"69194","DOI":"10.1109\/ACCESS.2019.2919736","volume":"7","author":"J Ren","year":"2019","unstructured":"Ren, J., Wang, H., Hou, T., et al.: Federated Learning-Based Computation Offloading Optimization in edge computing-supported Internet of Things. IEEE Access 7, 69194\u201369201 (2019)","journal-title":"IEEE Access"},{"issue":"2","key":"1_CR11","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/MVT.2017.2668838","volume":"12","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Mao, Y., Leng, S., et al.: Mobile-edge computing for vehicular networks: a promising network paradigm with predictive off-loading. IEEE Veh. Technol. Mag. 12(2), 36\u201344 (2017)","journal-title":"IEEE Veh. Technol. Mag."}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","6GN for Future Wireless Networks"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-63941-9_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T21:07:35Z","timestamp":1611868055000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-63941-9_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030639402","9783030639419"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-63941-9_1","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"29 January 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"6GN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on 5G for Future Wireless Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"gwn2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/5gwn.eai-conferences.org\/2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}