{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T03:50:15Z","timestamp":1775274615868,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030041816","type":"print"},{"value":"9783030041823","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","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":[[2018]]},"DOI":"10.1007\/978-3-030-04182-3_26","type":"book-chapter","created":{"date-parts":[[2018,11,17]],"date-time":"2018-11-17T05:19:48Z","timestamp":1542431988000},"page":"289-302","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Deep Reinforcement Learning for Multi-resource Cloud Job Scheduling"],"prefix":"10.1007","author":[{"given":"Jianpeng","family":"Lin","sequence":"first","affiliation":[]},{"given":"Zhiping","family":"Peng","sequence":"additional","affiliation":[]},{"given":"Delong","family":"Cui","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,11,18]]},"reference":[{"key":"26_CR1","doi-asserted-by":"crossref","unstructured":"Wang, T., Liu, Z., Chen, Y., Xu, Y., Dai, X.: Load balancing task scheduling based on genetic algorithm in cloud computing. In: Proceedings of the 12th International Conference on Dependable, Autonomic and Secure Computing, pp. 146\u2013152 (2014)","DOI":"10.1109\/DASC.2014.35"},{"key":"26_CR2","doi-asserted-by":"publisher","first-page":"926","DOI":"10.1007\/s11227-016-1626-x","volume":"72","author":"S Singh","year":"2016","unstructured":"Singh, S., Chana, I.: Resource provisioning and scheduling in clouds. QoS perspective. J. Supercomput. 72, 926\u2013960 (2016)","journal-title":"QoS perspective. J. Supercomput."},{"key":"26_CR3","doi-asserted-by":"publisher","first-page":"2687","DOI":"10.1109\/ACCESS.2015.2508940","volume":"3","author":"L Zuo","year":"2017","unstructured":"Zuo, L., Shu, L., Dong, S.: A multi-objective optimization scheduling method based on the ant colony algorithm in cloud computing. IEEE Access 3, 2687\u20132699 (2017)","journal-title":"IEEE Access"},{"key":"26_CR4","volume-title":"Reinforcement Learning: An Introduction","author":"RS Sutton","year":"1998","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)"},{"key":"26_CR5","unstructured":"Dutreilh, X., Kirgizov, S., Melekhova, O.: Using reinforcement learning for autonomic resource allocation in clouds: towards a fully automated workflow, pp. 67\u201374 (2011)"},{"key":"26_CR6","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.1002\/cpe.2864","volume":"25","author":"E Barrett","year":"2013","unstructured":"Barrett, E., Howley, E., Duggan, J.: Applying reinforcement learning towards automating resource allocation and application scalability in the cloud. Concurr. Comput. Pract. Exp. 25, 1656\u20131674 (2013)","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Galstyan, A., Czajkowski, K., Lerman, K.: Resource allocation in the grid using reinforcement learning. In: International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1314\u20131315 (2004)","DOI":"10.65109\/EFOJ3501"},{"key":"26_CR8","doi-asserted-by":"publisher","first-page":"1595","DOI":"10.1007\/s10586-015-0484-2","volume":"18","author":"Z Peng","year":"2015","unstructured":"Peng, Z., Cui, D., Zuo, J.: Random task scheduling scheme based on reinforcement learning in cloud computing. Cluster Comput. 18, 1595\u20131607 (2015)","journal-title":"Cluster Comput."},{"key":"26_CR9","first-page":"1","volume":"2015","author":"Z Peng","year":"2015","unstructured":"Peng, Z., Cui, D., Zuo, J.: Research on cloud computing resources provisioning based on reinforcement learning. Math. Prob. Eng. 2015, 1\u201312 (2015)","journal-title":"Math. Prob. Eng."},{"key":"26_CR10","doi-asserted-by":"crossref","unstructured":"Peng, Z., Cui, D., Ma, Y., Xiong, J., Xu, B., Lin, W.: A reinforcement learning-based mixed job scheduler scheme for cloud computing under SLA constraint. In: International Conference on Cyber Security and Cloud Computing, pp. 142\u2013147 (2016)","DOI":"10.1109\/CSCloud.2016.16"},{"key":"26_CR11","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1038\/nature14236","volume":"518","author":"V Mnih","year":"2015","unstructured":"Mnih, V., Kavukcuoglu, K., Silver, D.: Human-level control through deep reinforcement learning. Nature 518, 529 (2015)","journal-title":"Nature"},{"key":"26_CR12","doi-asserted-by":"crossref","unstructured":"Mao, H., Alizadeh, M., Menache, I.: Resource management with deep reinforcement learning. In: ACM Workshop on Hot Topics in Networks, pp. 50\u201356 (2016)","DOI":"10.1145\/3005745.3005750"},{"key":"26_CR13","unstructured":"Mnih, V., Kavukcuoglu, K., Silver, D.: Playing Atari with deep reinforcement learning. Computer Science (2013)"},{"key":"26_CR14","unstructured":"Hinton, G.: Overview of mini-batch gradient descent. Neural Networks for Machine Learning. https:\/\/www.coursera.org\/learn\/neural-networks. Accessed 13 June 2018"},{"key":"26_CR15","unstructured":"Schulman, J., Levine, S., Moritz, P.: Trust region policy optimization. In: Computer Science, pp. 1889\u20131897 (2015)"},{"issue":"4","key":"26_CR16","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1145\/2740070.2626334","volume":"44","author":"R Grandl","year":"2014","unstructured":"Grandl, R., Ananthanarayanan, G., Kandula, S.: Multi-resource packing for cluster schedulers. ACM Sigcomm Comput. Commun. Rev. 44(4), 455\u2013466 (2014)","journal-title":"ACM Sigcomm Comput. Commun. Rev."},{"key":"26_CR17","first-page":"1","volume":"40","author":"Q Liu","year":"2018","unstructured":"Liu, Q., Zhai, J.W., Zhang, Z.Z.: A survey on deep reinforcement learning. Chin. J. Comput. 40, 1\u201328 (2018)","journal-title":"Chin. J. Comput."}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04182-3_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T02:57:03Z","timestamp":1775271423000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-04182-3_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030041816","9783030041823"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04182-3_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"18 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Siem Reap","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambodia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.cs.cityu.edu.hk\/iconip\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"575","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"401","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"70% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}