{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T18:01:56Z","timestamp":1774893716949,"version":"3.50.1"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819584109","type":"print"},{"value":"9789819584116","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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":[[2026]]},"DOI":"10.1007\/978-981-95-8411-6_27","type":"book-chapter","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:09:56Z","timestamp":1774890596000},"page":"352-366","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Neural Network-Enhanced Monte Carlo Tree Search for\u00a0Adaptive Resource Scheduling in\u00a0Heterogeneous Spark Environments"],"prefix":"10.1007","author":[{"given":"Xiaoyong","family":"Tang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weilong","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenzheng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronghui","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tan","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,31]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","unstructured":"Ahmad, F., Chakradhar, S.T., Raghunathan, A., Vijaykumar, T.N.: Tarazu: optimizing mapreduce on heterogeneous clusters. In: Proceedings of the ASPLOS, pp. 61\u201374. ASPLOS XVII (2012). https:\/\/doi.org\/10.1145\/2150976.2150984","DOI":"10.1145\/2150976.2150984"},{"key":"27_CR2","doi-asserted-by":"publisher","first-page":"639","DOI":"10.1109\/TCC.2021.3108043","volume":"11","author":"D Cheng","year":"2023","unstructured":"Cheng, D., Wang, Y., Dai, D.: Dynamic resource provisioning for iterative workloads on Apache Spark. IEEE Trans. Cloud Comput. 11, 639\u2013652 (2023)","journal-title":"IEEE Trans. Cloud Comput."},{"key":"27_CR3","unstructured":"Ghodsi, A., Zaharia, M., Hindman, B., et\u00a0al.: Dominant resource fairness: fair allocation of multiple resource types. In: 8th USENIX Symposium on Networked Systems Design and Implementation (NSDI 11), pp. 323\u2013336 (2011)"},{"key":"27_CR4","doi-asserted-by":"crossref","unstructured":"Hu, Z., Tu, J., Li, B.: Spear: Optimized dependency-aware task scheduling with deep reinforcement learning. In: 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS), pp. 2037\u20132046 (2019)","DOI":"10.1109\/ICDCS.2019.00201"},{"key":"27_CR5","unstructured":"Intel BigData Team: Hibench: a big data micro benchmark suite (2010). https:\/\/github.com\/Intel-bigdata\/HiBench. Accessed Mar 2025"},{"key":"27_CR6","doi-asserted-by":"crossref","unstructured":"Islam, M.T., Karunasekera, S., Buyya, R.: dSpark: deadline-based resource allocation for big data applications in Apache Spark. In: 2017 IEEE 13th International Conference on E-Science (e-Science), pp. 89\u201398. IEEE (2017)","DOI":"10.1109\/eScience.2017.21"},{"issue":"7","key":"27_CR7","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1109\/TPDS.2021.3124670","volume":"33","author":"MT Islam","year":"2022","unstructured":"Islam, M.T., Karunasekera, S., Buyya, R.: Performance and cost-efficient Spark job scheduling based on deep reinforcement learning in cloud computing environments. IEEE Trans. Parallel Distrib. Syst. 33(7), 1695\u20131710 (2022)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"27_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2019.110515","volume":"162","author":"MT Islam","year":"2020","unstructured":"Islam, M.T., Srirama, S.N., Karunasekera, S., Buyya, R.: Cost-efficient dynamic scheduling of big data applications in Apache Spark on cloud. J. Syst. Softw. 162, 110515 (2020)","journal-title":"J. Syst. Softw."},{"issue":"5","key":"27_CR9","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1109\/TC.2021.3075625","volume":"71","author":"MT Islam","year":"2022","unstructured":"Islam, M.T., Wu, H., Karunasekera, S., Buyya, R.: SLA-based scheduling of Spark jobs in hybrid cloud computing environments. IEEE Trans. Comput. 71(5), 1117\u20131132 (2022). https:\/\/doi.org\/10.1109\/TC.2021.3075625","journal-title":"IEEE Trans. Comput."},{"issue":"1","key":"27_CR10","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/s10723-024-09756-4","volume":"22","author":"H Li","year":"2024","unstructured":"Li, H., Luo, W., Xie, W., Ye, H., Duan, X.: Adaptive scheduling framework of streaming applications based on resource demand prediction with hybrid algorithms. J. Grid Comput. 22(1), 39 (2024)","journal-title":"J. Grid Comput."},{"issue":"2","key":"27_CR11","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1109\/TNET.2021.3050927","volume":"29","author":"L Liu","year":"2021","unstructured":"Liu, L., Xu, H.: Elasecutor: elastic executor scheduling in data analytics systems. IEEE\/ACM Trans. Networking 29(2), 681\u2013694 (2021)","journal-title":"IEEE\/ACM Trans. Networking"},{"key":"27_CR12","doi-asserted-by":"crossref","unstructured":"Mao, H., Schwarzkopf, M., Venkatakrishnan, S.B., Meng, Z., Alizadeh, M.: Learning scheduling algorithms for data processing clusters. In: Proceedings of the ACM Special Interest Group on Data Communication, pp. 270\u2013288 (2019)","DOI":"10.1145\/3341302.3342080"},{"issue":"7839","key":"27_CR13","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1038\/s41586-020-03051-4","volume":"588","author":"J Schrittwieser","year":"2020","unstructured":"Schrittwieser, J., Antonoglou, I., Hubert, T., Simonyan, K., Sifre, L., et al.: Mastering Atari, Go, Chess and Shogi by planning with a learned model. Nature 588(7839), 604\u2013609 (2020). https:\/\/doi.org\/10.1038\/s41586-020-03051-4","journal-title":"Nature"},{"issue":"7676","key":"27_CR14","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1038\/nature24270","volume":"550","author":"D Silver","year":"2017","unstructured":"Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., et al.: Mastering the game of Go without human knowledge. Nature 550(7676), 354\u2013359 (2017)","journal-title":"Nature"},{"key":"27_CR15","doi-asserted-by":"crossref","unstructured":"Yang, H., Liu, X., Chen, S., Lei, Z., Du, H., Zhu, C.: Improving Spark performance with MPTE in heterogeneous environments. In: 2016 International Conference on Audio, Language and Image Processing (ICALIP), pp. 28\u201333 (2016)","DOI":"10.1109\/ICALIP.2016.7846627"},{"key":"27_CR16","doi-asserted-by":"publisher","unstructured":"Zaharia, M., Borthakur, D., Sen\u00a0Sarma, J., Elmeleegy, K., Shenker, S., Stoica, I.: Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling. In: Proceedings of the 5th European Conference on Computer Systems, pp. 265\u2013278 (2010). https:\/\/doi.org\/10.1145\/1755913.1755940","DOI":"10.1145\/1755913.1755940"},{"issue":"11","key":"27_CR17","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1145\/2934664","volume":"59","author":"M Zaharia","year":"2016","unstructured":"Zaharia, M., Xin, R.S., Wendell, P., Das, T., Armbrust, M., et al.: Apache Spark: a unified engine for big data processing. Commun. ACM 59(11), 56\u201365 (2016)","journal-title":"Commun. ACM"}],"container-title":["Lecture Notes in Computer Science","Algorithms and Architectures for Parallel Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-8411-6_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:09:57Z","timestamp":1774890597000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-8411-6_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819584109","9789819584116"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-8411-6_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"31 March 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"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":"Zhengzhou","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 November 2025","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":"ica3pp2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ieee-cybermatics.org\/2025\/ica3pp\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}