{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T01:04:08Z","timestamp":1743037448571,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319942940"},{"type":"electronic","value":"9783319942957"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-94295-7_16","type":"book-chapter","created":{"date-parts":[[2018,6,18]],"date-time":"2018-06-18T12:29:10Z","timestamp":1529324950000},"page":"235-247","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Feedback Prediction Model for\u00a0Resource Usage and Offloading Time in\u00a0Edge Computing"],"prefix":"10.1007","author":[{"given":"Menghan","family":"Zheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yubin","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng-Zhong","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaofan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,19]]},"reference":[{"issue":"1","key":"16_CR1","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1109\/TNSM.2018.2790081","volume":"15","author":"B Yang","year":"2018","unstructured":"Yang, B., Chai, W.K., Xu, Z., Katsaros, K.V., Pavlou, G.: Cost-efficient NFV-enabled mobile edge-cloud for low latency mobile applications. IEEE Trans. Netw. Serv. Manag. 15(1), 475\u2013488 (2018)","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"16_CR2","doi-asserted-by":"publisher","unstructured":"Barik, R.K., Dubey, H., Mankodiya, K.: SOA-FOG: secure service-oriented edge computing architecture for smart health big data analytics. In: 2017 IEEE Global Conference on Signal and Information Processing (Global SIP), pp. 477\u2013481. IEEE Press, New York (2018). https:\/\/doi.org\/10.1109\/SC2.2017.11","DOI":"10.1109\/SC2.2017.11"},{"key":"16_CR3","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1109\/JIOT.2018.2805263","volume":"5","author":"G Premsankar","year":"2018","unstructured":"Premsankar, G., Di Francesco, M., Taleb, T.: Edge computing for the Internet of Things: a case study. IEEE Internet Things J. 5, 1275\u20131284 (2018)","journal-title":"IEEE Internet Things J."},{"key":"16_CR4","unstructured":"Baike for Edge Computing. http:\/\/baike.baidu.com\/item\/%E8%BE%B9%E7%BC%98%E8%AE%A1%E7%AE%97\/9044985?fr=aladdin"},{"issue":"99","key":"16_CR5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/ACCESS.2018.2873804","volume":"pp","author":"J Zhang","year":"2018","unstructured":"Zhang, J., Xia, W., Yan, F., Shen, L.: Joint computation offloading and resource allocation optimization in heterogeneous networks with moble edge computing. IEEE Access pp(99), 1 (2018)","journal-title":"IEEE Access"},{"key":"16_CR6","first-page":"11365","volume":"6","author":"Y Hao","year":"2018","unstructured":"Hao, Y., Chen, M., Hu, L., Hossain, M.S., Ghoneim, A.: Energy efficient task caching and offloading for mobile edge computing. IEEE Access Spec. Sect. Mob. Edge Comput. 6, 11365\u201311373 (2018)","journal-title":"IEEE Access Spec. Sect. Mob. Edge Comput."},{"key":"16_CR7","doi-asserted-by":"publisher","unstructured":"Luo, C., Salinas, S., Li, M., Li, P.: Energy-effecient autonomic offloading in mobile edge computing. In: 15th International Conference on Dependable, Autonomic and Secure Computing, 15th International Conference on Pervasive Intelligence and Computing, 3rd International Conference on Big Data Intelligence and Computing and Cyber Science and Technology Congress, pp. 581\u2013588. IEEE Press, New York (2017). https:\/\/doi.org\/10.1109\/DASC-PICom-DataCom-CyberSciTec.2017.104","DOI":"10.1109\/DASC-PICom-DataCom-CyberSciTec.2017.104"},{"key":"16_CR8","doi-asserted-by":"publisher","unstructured":"Huang, S.-C., Luo, Y.-C., Chen, B.-L., Chung, Y.-C., Chou, J.: Application-aware traffic redirection: a mobile edge computing implementation toward future 5G networks. In: IEEE 7th International Symposium on Cloud and Service Computing, pp. 17\u201323. IEEE Press, New York (2017). https:\/\/doi.org\/10.1109\/SC2.2017.11","DOI":"10.1109\/SC2.2017.11"},{"issue":"1","key":"16_CR9","doi-asserted-by":"publisher","first-page":"330","DOI":"10.1109\/TNSM.2017.2777885","volume":"15","author":"Y Xia","year":"2018","unstructured":"Xia, Y., Ren, R., Cai, H., Vasilakos, A.V., Lv, Z.: Daphne: a flexible and hybrid scheduling framework in multi-tenant clusters. IEEE Trans. Netw. Serv. Manag. 15(1), 330\u2013343 (2018)","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"issue":"21","key":"16_CR10","doi-asserted-by":"publisher","first-page":"7190","DOI":"10.1109\/ACCESS.2017.2785280","volume":"pp","author":"SB Melhem","year":"2018","unstructured":"Melhem, S.B., Agarwal, A., Goel, N., Zaman, M.: Markov prediction model for host load detection and VM placement in live migration. IEEE Access pp(21), 7190\u20137205 (2018)","journal-title":"IEEE Access"},{"key":"16_CR11","doi-asserted-by":"crossref","unstructured":"Yang, X., Chen, Z., Li, K., Sun, Y., Liu, N., Xie, W., Zhao, Y.: Communication-constrained mobile edge computing systems for wireless virtual reality: scheduling and tradeoff. IEEE Access 1\u201313 (2018)","DOI":"10.1109\/ACCESS.2018.2817288"},{"issue":"11","key":"16_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TVT.2018.2800777","volume":"pp","author":"L Yang","year":"2018","unstructured":"Yang, L., Zhang, H., Li, M., Guo, J., Ji, H.: Mobile edge computing empowered energy efficient task offloading in 5G. IEEE Trans. Veh. Technol. pp(11), 1\u201312 (2018)","journal-title":"IEEE Trans. Veh. Technol."},{"key":"16_CR13","doi-asserted-by":"crossref","unstructured":"Zhao, P., Tian, H., Fan, S., Paulraj, A.: Information prediction and dynamic programming based RAN slicing for mobile edge computing. IEEE Wirel. Commun. Lett. 1\u20134 (2018)","DOI":"10.1109\/LWC.2018.2802522"},{"issue":"4","key":"16_CR14","doi-asserted-by":"publisher","first-page":"2852","DOI":"10.1109\/JSYST.2016.2548423","volume":"11","author":"Y Kryftis","year":"2017","unstructured":"Kryftis, Y., Mastorakis, G., Mavromoustakis, C.X., Batall, J.M., Rodrigues, J.J.P.C., Dobre, C.: Resource usage prediction models for optimal multimedia content provision. IEEE Syst. J. 11(4), 2852\u20132863 (2017)","journal-title":"IEEE Syst. J."},{"issue":"3","key":"16_CR15","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1109\/TCC.2015.2415776","volume":"3","author":"X Wang","year":"2015","unstructured":"Wang, X., Wang, X., Che, H., Li, K., Huang, M., Gao, C.: An intelligent economic approach for dynamic resource allocation in cloud services. IEEE Trans. Cloud Comput. 3(3), 275\u2013289 (2015)","journal-title":"IEEE Trans. Cloud Comput."},{"issue":"4","key":"16_CR16","first-page":"1943","volume":"8","author":"Z Cao","year":"2017","unstructured":"Cao, Z., Lin, J., Wan, C., Song, Y., Zhang, Y., Wang, X.: Optimal cloud computing resource allocation for demand side management in smart grid. IEEE Trans. Smart Grid 8(4), 1943\u20131955 (2017)","journal-title":"IEEE Trans. Smart Grid"},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Bouet, M., Conan, V.: Mobile edge computing resources optimization: a geo-clustering approach. IEEE Trans. Netw. Serv. Manag. (2018)","DOI":"10.1109\/TNSM.2018.2816263"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Yu, S., Wang, X., Langar, R.: Computation offloading for mobile edge computing: a deep learning approach. In: IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1\u20136 (2017)","DOI":"10.1109\/PIMRC.2017.8292514"}],"container-title":["Lecture Notes in Computer Science","Cloud Computing \u2013 CLOUD 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-94295-7_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,19]],"date-time":"2022-06-19T00:09:53Z","timestamp":1655597393000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-94295-7_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319942940","9783319942957"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-94295-7_16","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":"19 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CLOUD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Cloud Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Seattle, WA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","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":"25 June 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cloud2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.thecloudcomputing.org\/2018\/","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":"www.confhub.com","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"108","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":"26","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":"3","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":"24% - 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":"3","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":"4","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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}