{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T06:06:09Z","timestamp":1770530769590,"version":"3.49.0"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031302282","type":"print"},{"value":"9783031302299","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-30229-9_35","type":"book-chapter","created":{"date-parts":[[2023,4,8]],"date-time":"2023-04-08T19:02:39Z","timestamp":1680980559000},"page":"539-555","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Energy-Aware Dynamic Resource Allocation in\u00a0Container-Based Clouds via\u00a0Cooperative Coevolution Genetic Programming"],"prefix":"10.1007","author":[{"given":"Chen","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Victoria","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongbo","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kameron","family":"Christopher","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,4,9]]},"reference":[{"key":"35_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113306","volume":"150","author":"AS Abohamama","year":"2020","unstructured":"Abohamama, A.S., Hamouda, E.: A hybrid energy-aware virtual machine placement algorithm for cloud environments. Expert Syst. Appl. 150, 113306 (2020)","journal-title":"Expert Syst. Appl."},{"key":"35_CR2","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1007\/978-3-030-97546-3_42","volume-title":"AI 2021: Advances in Artificial Intelligence","author":"T Akindele","year":"2022","unstructured":"Akindele, T., Tan, B., Mei, Y., Ma, H.: Hybrid grouping genetic algorithm for large-scale two-level resource allocation of containers in the cloud. In: Long, G., Yu, X., Wang, S. (eds.) AI 2022. LNCS (LNAI), vol. 13151, pp. 519\u2013530. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-97546-3_42"},{"key":"35_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113719","volume":"164","author":"A Al-Moalmi","year":"2021","unstructured":"Al-Moalmi, A., Luo, J., Salah, A., Li, K., Yin, L.: A whale optimization system for energy-efficient container placement in data centers. Expert Syst. Appl. 164, 113719 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"9","key":"35_CR4","doi-asserted-by":"publisher","first-page":"8585","DOI":"10.1007\/s13369-021-05553-3","volume":"46","author":"A Bhardwaj","year":"2021","unstructured":"Bhardwaj, A., Krishna, C.R.: Virtualization in cloud computing: moving from hypervisor to containerization-a survey. Arab. J. Sci. Eng. 46(9), 8585\u20138601 (2021)","journal-title":"Arab. J. Sci. Eng."},{"issue":"7","key":"35_CR5","doi-asserted-by":"publisher","first-page":"5192","DOI":"10.1007\/s11227-019-02801-0","volume":"76","author":"S Bhattacherjee","year":"2020","unstructured":"Bhattacherjee, S., Das, R., Khatua, S., Roy, S.: Energy-efficient migration techniques for cloud environment: a step toward green computing. J. Supercomputing 76(7), 5192\u20135220 (2020)","journal-title":"J. Supercomputing"},{"key":"35_CR6","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1109\/COMST.2015.2481183","volume":"18","author":"M Dayarathna","year":"2015","unstructured":"Dayarathna, M., Wen, Y., Fan, R.: Data center energy consumption modeling: a survey. IEEE Commun. Surv. Tutorials 18, 732\u2013794 (2015)","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"35_CR7","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1016\/j.future.2020.05.004","volume":"111","author":"W Ding","year":"2020","unstructured":"Ding, W., Luo, F., Han, L., Gu, C., Lu, H., Fuentes, J.: Adaptive virtual machine consolidation framework based on performance-to-power ratio in cloud data centers. Future Gener. Comput. Syst. 111, 254\u2013270 (2020)","journal-title":"Future Gener. Comput. Syst."},{"issue":"3","key":"35_CR8","doi-asserted-by":"publisher","first-page":"2221","DOI":"10.1007\/s10462-020-09903-9","volume":"54","author":"S Gharehpasha","year":"2021","unstructured":"Gharehpasha, S., Masdari, M., Jafarian, A.: Virtual machine placement in cloud data centers using a hybrid multi-verse optimization algorithm. Artif. Intell. Rev. 54(3), 2221\u20132257 (2021)","journal-title":"Artif. Intell. Rev."},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Guo, M., Guan, Q., Chen, W., Ji, F., Peng, Z.: Delay-optimal scheduling of VMs in a Queueing cloud computing system with heterogeneous workloads. IEEE Trans. Serv. Comput. 15(1), pp. 110\u2013123 (2022)","DOI":"10.1109\/TSC.2019.2920954"},{"issue":"1","key":"35_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13677-019-0131-1","volume":"8","author":"MK Hussein","year":"2019","unstructured":"Hussein, M.K., Mousa, M.H., Alqarni, M.A.: A placement architecture for a container as a service (CAAS) in a cloud environment. J. Cloud Comput. 8(1), 1\u201315 (2019). https:\/\/doi.org\/10.1186\/s13677-019-0131-1","journal-title":"J. Cloud Comput."},{"key":"35_CR11","doi-asserted-by":"crossref","unstructured":"Kaewkasi, C., Chuenmuneewong, K.: Improvement of container scheduling for docker using ant colony optimization. In: 2017 9th International Conference on Knowledge and Smart Technology (KST), pp. 254\u2013259. IEEE (2017)","DOI":"10.1109\/KST.2017.7886112"},{"key":"35_CR12","doi-asserted-by":"crossref","unstructured":"Kanso, A., Youssef, A.: Serverless: beyond the cloud. In: Proceedings of the 2nd International Workshop on Serverless Computing, pp. 6\u201310 (2017)","DOI":"10.1145\/3154847.3154854"},{"key":"35_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpat.2022.102521","volume":"118","author":"F Li","year":"2022","unstructured":"Li, F., Tan, W.J., Cai, W.: A wholistic optimization of containerized workflow scheduling and deployment in the cloud-edge environment. Simul. Model. Pract. Theory 118, 102521 (2022)","journal-title":"Simul. Model. Pract. Theory"},{"issue":"11","key":"35_CR14","first-page":"2752","volume":"33","author":"S Long","year":"2021","unstructured":"Long, S., Wen, W., Li, Z., Li, K., Yu, R., Zhu, J.: A global cost-aware container scheduling strategy in cloud data centers. IEEE Trans. Parallel Distrib. Syst. 33(11), 2752\u20132766 (2021)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"35_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/978-3-319-44482-6_9","volume-title":"Service-Oriented and Cloud Computing","author":"Z\u00c1 Mann","year":"2016","unstructured":"Mann, Z.\u00c1.: Interplay of virtual machine selection and virtual machine placement. In: Aiello, M., Johnsen, E.B., Dustdar, S., Georgievski, I. (eds.) ESOCC 2016. LNCS, vol. 9846, pp. 137\u2013151. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-44482-6_9"},{"key":"35_CR16","doi-asserted-by":"crossref","unstructured":"Nardelli, M., Hochreiner, C., Schulte, S.: Elastic provisioning of virtual machines for container deployment. In: Proceedings of the 8th ACM\/SPEC on International Conference on Performance Engineering Companion, pp. 5\u201310 (2017)","DOI":"10.1145\/3053600.3053602"},{"key":"35_CR17","doi-asserted-by":"crossref","unstructured":"Piraghaj, S.F., Dastjerdi, A.V., Calheiros, R.N., Buyya, R.: Efficient virtual machine sizing for hosting containers as a service (SERVICES 2015). In: 2015 IEEE World Congress on Services, pp. 31\u201338. IEEE (2015)","DOI":"10.1109\/SERVICES.2015.14"},{"key":"35_CR18","doi-asserted-by":"crossref","unstructured":"Piraghaj, S.F., Dastjerdi, A.V., Calheiros, R.N., Buyya, R.: A framework and algorithm for energy efficient container consolidation in cloud data centers. In: 2015 IEEE International Conference on Data Science and Data Intensive Systems, pp. 368\u2013375. IEEE (2015)","DOI":"10.1109\/DSDIS.2015.67"},{"key":"35_CR19","doi-asserted-by":"crossref","unstructured":"Shen, S., Van Beek, V., Iosup, A.: Statistical characterization of business-critical workloads hosted in cloud datacenters. In: 2015 15th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 465\u2013474. IEEE (2015)","DOI":"10.1109\/CCGrid.2015.60"},{"key":"35_CR20","doi-asserted-by":"crossref","unstructured":"Shi, T., Ma, H., Chen, G.: Energy-aware container consolidation based on PSO in cloud data centers. In: IEEE CE, pp. 1\u20138 (2018)","DOI":"10.1109\/CEC.2018.8477708"},{"key":"35_CR21","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1007\/978-3-030-03991-2_15","volume-title":"AI 2018: Advances in Artificial Intelligence","author":"B Tan","year":"2018","unstructured":"Tan, B., Ma, H., Mei, Y.: A genetic programming hyper-heuristic approach for online resource allocation in container-based clouds. In: Mitrovic, T., Xue, B., Li, X. (eds.) AI 2018. LNCS (LNAI), vol. 11320, pp. 146\u2013152. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-03991-2_15"},{"key":"35_CR22","doi-asserted-by":"publisher","first-page":"1500","DOI":"10.1109\/TCC.2020.3026338","volume":"10","author":"B Tan","year":"2022","unstructured":"Tan, B., Ma, H., Mei, Y., Zhang, M.: A cooperative coevolution genetic programming hyper-heuristics approach for on-line resource allocation in container-based clouds. IEEE Trans. Cloud Comput. 10, 1500\u20131514 (2022)","journal-title":"IEEE Trans. Cloud Comput."},{"issue":"2","key":"35_CR23","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1007\/s10586-020-03152-9","volume":"24","author":"M Tarahomi","year":"2021","unstructured":"Tarahomi, M., Izadi, M., Ghobaei-Arani, M.: An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach. Clust. Comput. 24(2), 919\u2013934 (2021)","journal-title":"Clust. Comput."},{"key":"35_CR24","unstructured":"Taylor, P.: Global market share held by operating systems for desktop PCs, from Jan 2013 to Dec 2021. Tech. rep. (2022). https:\/\/www.statista.com\/statistics\/218089\/global-market-share-of-windows-7"},{"key":"35_CR25","doi-asserted-by":"publisher","first-page":"3526","DOI":"10.1109\/ACCESS.2020.3047803","volume":"9","author":"C Zhang","year":"2020","unstructured":"Zhang, C., Wang, Y., Wu, H., Guo, H.: An energy-aware host resource management framework for two-tier virtualized cloud data centers. IEEE Access 9, 3526\u20133544 (2020)","journal-title":"IEEE Access"},{"key":"35_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1007\/978-3-319-94295-7_9","volume-title":"Cloud Computing \u2013 CLOUD 2018","author":"R Zhang","year":"2018","unstructured":"Zhang, R., Zhong, A., Dong, B., Tian, F., Li, R.: Container-VM-PM Architecture: a novel architecture for docker container placement. In: Luo, M., Zhang, L.-J. (eds.) CLOUD 2018. LNCS, vol. 10967, pp. 128\u2013140. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-94295-7_9"}],"container-title":["Lecture Notes in Computer Science","Applications of Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-30229-9_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,9]],"date-time":"2023-04-09T23:10:39Z","timestamp":1681081839000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-30229-9_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031302282","9783031302299"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-30229-9_35","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"9 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoApplications","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on the Applications of Evolutionary Computation (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brno","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Czech Republic","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 April 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 April 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evoapplications2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2023\/evoapps\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-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":"78","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":"37","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":"14","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":"47% - 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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}