{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T21:17:37Z","timestamp":1726003057329},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030050627"},{"type":"electronic","value":"9783030050634"}],"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\/978-3-030-05063-4_2","type":"book-chapter","created":{"date-parts":[[2018,12,7]],"date-time":"2018-12-07T00:23:45Z","timestamp":1544142225000},"page":"12-20","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["CGAN Based Cloud Computing Server Power Curve Generating"],"prefix":"10.1007","author":[{"given":"Longchuan","family":"Yan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wantao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yin","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Songlin","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,12,7]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Baliga, J., Ayre, R.W.A., Hinton, K., Tucker, R.S.: Green cloud computing: balancing energy in processing, storage, and transport. In: Proceedings of the IEEE, pp. 149\u2013167. IEEE (2010)","DOI":"10.1109\/JPROC.2010.2060451"},{"key":"2_CR2","doi-asserted-by":"publisher","DOI":"10.2172\/1372902","volume-title":"United States Data Center Energy Usage Report","author":"A Shehabi","year":"2016","unstructured":"Shehabi, A., et al.: United States Data Center Energy Usage Report. Lawrence Berkeley National Laboratory, Berkeley (2016)"},{"issue":"7","key":"2_CR3","first-page":"1371","volume":"25","author":"L Liang","year":"2014","unstructured":"Liang, L., Wenjun, W., Fei, Z.: Energy modeling based on cloud data center. J. Softw. 25(7), 1371\u20131387 (2014). (in Chinese)","journal-title":"J. Softw."},{"key":"2_CR4","doi-asserted-by":"crossref","unstructured":"Goel, B., Mckee, S.A.: A methodology for modeling dynamic and static power consumption for multicore processors. In: Proceedings of IEEE International Parallel and Distributed Processing Symposium, pp. 273\u2013282. IEEE (2016)","DOI":"10.1109\/IPDPS.2016.118"},{"key":"2_CR5","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27, pp. 2672\u20132680. NIPS (2014)"},{"key":"2_CR6","unstructured":"Mirza, M., Osindero, S.: Conditional Generative Adversarial Nets, arxiv:1411.1784 (2014)"},{"key":"2_CR7","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. In: Proceedings of International Conference on Learning Representations, arxiv:1511.06434 (2016)"},{"key":"2_CR8","unstructured":"Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: Infogan: interpretable representation learning by information maximizing generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 29, pp. 2172\u20132180. NIPS (2016)"},{"key":"2_CR9","unstructured":"Zhao, J., Mathieu M., Lecun, Y.: Energy-based generative adversarial network. In: Proceedings of International Conference on Learning Representations, arxiv:1609.03126 (2017)"},{"key":"2_CR10","unstructured":"Berthelot, D., Schumm, T., Metz, L.: BEGAN: boundary equilibrium generative adversarial networks, arxiv:1703.10717 (2017)"},{"issue":"3","key":"2_CR11","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1145\/3007787.3001188","volume":"44","author":"Daniel Wong","year":"2016","unstructured":"Wong, D.: Peak efficiency aware scheduling for highly energy proportional servers. In: Proceedings of International Symposium on Computer Architecture, pp. 481\u2013492. IEEE (2016)","journal-title":"ACM SIGARCH Computer Architecture News"},{"key":"2_CR12","doi-asserted-by":"crossref","unstructured":"Wu, Q., et al.: Dynamo: facebook\u2019s data center-wide power management system. In: Proceedings of ACM\/IEEE International Symposium on Computer Architecture, pp. 469\u2013480. IEEE (2016)","DOI":"10.1145\/3007787.3001187"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Hsu, C.-H., Deng, Q., Mars, J., Tang, L.: SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters. In: Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 535\u2013548. ACM (2018)","DOI":"10.1145\/3173162.3173190"}],"container-title":["Lecture Notes in Computer Science","Algorithms and Architectures for Parallel Processing"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-05063-4_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,11,6]],"date-time":"2019-11-06T23:17:18Z","timestamp":1573082238000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-05063-4_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030050627","9783030050634"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-05063-4_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ICA3PP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Algorithms and Architectures for Parallel Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","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":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ica3pp2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/nsclab.org\/ica3pp2018\/authors.html","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"}},{"value":"Easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"407","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"141","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"50","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"35% - 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"}},{"value":"2.3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"7.3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}