{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T18:11:09Z","timestamp":1771956669868,"version":"3.50.1"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030977764","type":"print"},{"value":"9783030977771","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":[[2022]]},"DOI":"10.1007\/978-3-030-97777-1_25","type":"book-chapter","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T17:03:05Z","timestamp":1647363785000},"page":"297-309","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Predicting Energy Consumption for UAV-Enabled MEC Using Machine Learning Algorithm"],"prefix":"10.1007","author":[{"given":"Abbas","family":"Alzaghir","sequence":"first","affiliation":[]},{"given":"Ali R.","family":"Abdellah","sequence":"additional","affiliation":[]},{"given":"Andrey","family":"Koucheryavy","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,3,16]]},"reference":[{"key":"25_CR1","doi-asserted-by":"crossref","unstructured":"Trung, Q., Duong, Chu, X., Suraweera, H.A.: Ultra-Dense Networks for 5G and Beyond: Modelling, Analysis, and Applications. Wiley, New York (2019)","DOI":"10.1002\/9781119473756"},{"key":"25_CR2","doi-asserted-by":"crossref","unstructured":"Abdellah, A., Koucheryavy, A.: Survey on artificial intelligence techniques in 5G networks. J. Inf. Technol. Telecommun. 8(1), 1\u201310 (2020). SPbSUT, Russia. http:\/\/www.sut.ru\/doci\/nauka\/1AEA\/ITT\/2020_1\/1-10.pdf","DOI":"10.31854\/2307-1303-2020-8-1-1-10"},{"key":"25_CR3","doi-asserted-by":"crossref","unstructured":"Kovalenko, V., Alzaghir, A., Volkov, A., Muthanna, A., Koucheryavy, A.: Clustering algorithms for UAV placement in 5G and beyond networks. In:\u00a02020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 301\u2013307. IEEE, October 2020","DOI":"10.1109\/ICUMT51630.2020.9222415"},{"issue":"23","key":"25_CR4","doi-asserted-by":"publisher","first-page":"5170","DOI":"10.3390\/s19235170","volume":"19","author":"PS Bithas","year":"2019","unstructured":"Bithas, P.S., et al.: A survey on machine-learning techniques for UAV-based communications. Sensors 19(23), 5170 (2019)","journal-title":"Sensors"},{"key":"25_CR5","doi-asserted-by":"publisher","unstructured":"Abdellah, A.R., Mahmood, O.A., Koucheryavy, A.: Delay prediction in IoT using machine learning approach. In: 2020 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) Brno, Czech Republic, pp. 275\u2013279 (2020). https:\/\/doi.org\/10.1109\/ICUMT51630.2020.9222245","DOI":"10.1109\/ICUMT51630.2020.9222245"},{"key":"25_CR6","doi-asserted-by":"publisher","first-page":"187498","DOI":"10.1109\/ACCESS.2020.3029903","volume":"8","author":"A Mughees","year":"2020","unstructured":"Mughees, A., et al.: Towards energy efficient 5G networks using machine learning: taxonomy, research challenges, and future research directions. IEEE Access 8, 187498\u2013187522 (2020)","journal-title":"IEEE Access"},{"key":"25_CR7","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1109\/OJCOMS.2021.3075201","volume":"2","author":"M-A Lahmeri","year":"2021","unstructured":"Lahmeri, M.-A., Kishk, M.A., Alouini, M.-S.: Artificial Intelligence for UAV-enabled wireless networks: a survey. IEEE Open J. Commun. Soc. 2, 1015\u20131040 (2021)","journal-title":"IEEE Open J. Commun. Soc."},{"key":"25_CR8","doi-asserted-by":"publisher","first-page":"53841","DOI":"10.1109\/ACCESS.2020.2981430","volume":"8","author":"B Brik","year":"2020","unstructured":"Brik, B., Ksentini, A., Bouaziz, M.: Federated learning for UAVs-enabled wireless networks: use cases, challenges, and open problems. IEEE Access 8, 53841\u201355384 (2020)","journal-title":"IEEE Access"},{"key":"25_CR9","doi-asserted-by":"crossref","unstructured":"Zhang, Q., et al.: Machine learning for predictive on-demand deployment of UAVs for wireless communications. In:\u00a02018 IEEE Global Communications Conference (GLOBECOM). IEEE (2018)","DOI":"10.1109\/GLOCOM.2018.8647209"},{"key":"25_CR10","doi-asserted-by":"publisher","unstructured":"Abdellah, A., Mahmood, O.A.K., Paramonov, A., Koucheryavy, A.: IoT traffic prediction using multi-step ahead prediction with neural network. In: 2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Dublin, Ireland, pp. 1\u20134 (2019). https:\/\/doi.org\/10.1109\/ICUMT48472.2019.8970675","DOI":"10.1109\/ICUMT48472.2019.8970675"},{"key":"25_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1007\/978-3-030-66471-8_6","volume-title":"Distributed Computer and Communication Networks","author":"A Volkov","year":"2020","unstructured":"Volkov, A., Abdellah, A.R., Muthanna, A., Makolkina, M., Paramonov, A., Koucheryavy, A.: IoT traffic prediction with neural networks learning based on SDN infrastructure. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds.) DCCN 2020. LNCS, vol. 12563, pp. 64\u201376. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-66471-8_6"},{"issue":"2","key":"25_CR12","doi-asserted-by":"publisher","first-page":"3743","DOI":"10.1109\/JIOT.2018.2890563","volume":"6","author":"L Ruan","year":"2019","unstructured":"Ruan, L., Dias, M.P.I., Wong, E.: Machine learning-based bandwidth prediction for low-latency H2M applications. IEEE Internet Things J. 6(2), 3743\u20133752 (2019). https:\/\/doi.org\/10.1109\/JIOT.2018.2890563","journal-title":"IEEE Internet Things J."},{"key":"25_CR13","doi-asserted-by":"crossref","unstructured":"White, G., Palade, A., Cabrera, C., Clarke, S.: IoTPredict: collaborative QoS prediction in IoT. In: IEEE PerCom, pp. 1\u201310, March 2018","DOI":"10.1109\/PERCOM.2018.8444598"},{"key":"25_CR14","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/978-3-030-66242-4_2","volume-title":"Distributed Computer and Communication Networks: Control, Computation, Communications","author":"AR Abdellah","year":"2020","unstructured":"Abdellah, A.R., Artem, V., Muthanna, A., Gallyamov, D., Koucheryavy, A.: Deep learning for IoT traffic prediction based on edge computing. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds.) DCCN 2020. CCIS, vol. 1337, pp. 18\u201329. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-66242-4_2"},{"key":"25_CR15","doi-asserted-by":"publisher","unstructured":"Abdellah, A.R., Koucheryavy, A.: Deep learning with long short-term memory for IoT traffic prediction. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) Internet of Things, Smart Spaces, and Next Generation Networks and Systems, NEW2AN 2020, ruSMART 2020. LNCS, vol. 12525, pp. 267\u2013280. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-65726-0_24","DOI":"10.1007\/978-3-030-65726-0_24"},{"key":"25_CR16","doi-asserted-by":"publisher","unstructured":"Abdellah, A.R., Koucheryavy, A.: VANET traffic prediction using LSTM with deep neural network learning. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds.) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN 2020, ruSMART 2020. LNCS, vol. 12525, pp. 281\u2013294. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-65726-0_25","DOI":"10.1007\/978-3-030-65726-0_25"}],"updated-by":[{"DOI":"10.1007\/978-3-030-97777-1_42","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T00:00:00Z","timestamp":1651708800000}}],"container-title":["Lecture Notes in Computer Science","Internet of Things, Smart Spaces, and Next Generation Networks and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-97777-1_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,4]],"date-time":"2022-05-04T02:05:57Z","timestamp":1651629957000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-97777-1_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030977764","9783030977771"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-97777-1_25","relation":{"correction":[{"id-type":"doi","id":"10.1007\/978-3-030-97777-1_42","asserted-by":"object"}]},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"16 March 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"5 May 2022","order":2,"name":"change_date","label":"Change Date","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Correction","order":3,"name":"change_type","label":"Change Type","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"In an older version of chapters 4, 24, and 25, there was an orthographical error in the name of one of the co-authors. This has been corrected.","order":4,"name":"change_details","label":"Change Details","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"NEW2AN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Next Generation Wired\/Wireless Networking","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"St. Petersburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Russia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 August 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 August 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"new2an2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/new2an.info\/#\/","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":"EDAS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"118","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":"35","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":"30% - 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":"2","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":"1.27","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)"}},{"value":"Conference was held online due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}