{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T14:03:28Z","timestamp":1743084208704,"version":"3.40.3"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030727918"},{"type":"electronic","value":"9783030727925"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-72792-5_59","type":"book-chapter","created":{"date-parts":[[2021,4,26]],"date-time":"2021-04-26T20:34:22Z","timestamp":1619469262000},"page":"748-758","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Stability Analysis of Communication System Under Certain Session Arrival Rate"],"prefix":"10.1007","author":[{"given":"Jiamin","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Cui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kailiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"An","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,27]]},"reference":[{"key":"59_CR1","doi-asserted-by":"publisher","unstructured":"Zhang, K., Chen, L., An, Y., et al.: A QoE test system for vehicular voice cloud services. Mob. Netw. Appl. (2019). https:\/\/doi.org\/10.1007\/s11036-019-01415-3","DOI":"10.1007\/s11036-019-01415-3"},{"issue":"1","key":"59_CR2","first-page":"196","volume":"7","author":"F Wang","year":"2019","unstructured":"Wang, F., Jiang, D., Qi, S.: An adaptive routing algorithm for integrated information networks. China Commun. 7(1), 196\u2013207 (2019)","journal-title":"China Commun."},{"key":"59_CR3","first-page":"1","volume":"36","author":"L Huo","year":"2019","unstructured":"Huo, L., Jiang, D., Lv, Z., et al.: An intelligent optimization-based traffic information acquirement approach to software-defined networking. Comput. Intell. 36, 1\u201321 (2019)","journal-title":"Comput. Intell."},{"issue":"5","key":"59_CR4","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1049\/cje.2017.07.018","volume":"26","author":"L Chen","year":"2017","unstructured":"Chen, L., Jiang, D., Bao, R., Xiong, J., Liu, F., Bei, L.: MIMO scheduling effectiveness analysis for bursty data service from view of QoE. Chin. J. Electron. 26(5), 1079\u20131085 (2017)","journal-title":"Chin. J. Electron."},{"issue":"2","key":"59_CR5","doi-asserted-by":"publisher","first-page":"1310","DOI":"10.1109\/TII.2019.2930226","volume":"16","author":"D Jiang","year":"2020","unstructured":"Jiang, D., Wang, Y., Lv, Z., et al.: Big data analysis-based network behavior insight of cellular networks for industry 4.0 applications. IEEE Trans. Ind. Inf. 16(2), 1310\u20131320 (2020)","journal-title":"IEEE Trans. Ind. Inf."},{"issue":"1","key":"59_CR6","first-page":"1","volume":"1","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Huo, L., Song, H.: Rethinking behaviors and activities of base stations in mobile cellular networks based on big data analysis. IEEE Trans. Netw. Sci. Eng. 1(1), 1\u201312 (2018)","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"issue":"1","key":"59_CR7","doi-asserted-by":"publisher","first-page":"15408","DOI":"10.1109\/ACCESS.2018.2794354","volume":"6","author":"L Chen","year":"2018","unstructured":"Chen, L., et al.: A lightweight end-side user experience data collection system for quality evaluation of multimedia communications. IEEE Access 6(1), 15408\u201315419 (2018)","journal-title":"IEEE Access"},{"key":"59_CR8","doi-asserted-by":"publisher","unstructured":"Chen, L., Zhang, L.: Spectral efficiency analysis for massive MIMO system under QoS constraint: an effective capacity perspective. Mob. Netw. Appl. (2020). https:\/\/doi.org\/10.1007\/s11036-019-01414-4","DOI":"10.1007\/s11036-019-01414-4"},{"key":"59_CR9","doi-asserted-by":"crossref","unstructured":"Wang, F., Jiang, D., Qi, S., et al.: A dynamic resource scheduling scheme in edge computing satellite networks. Mob. Netw. Appl. (2019)","DOI":"10.1007\/s11036-019-01421-5"},{"issue":"10","key":"59_CR10","doi-asserted-by":"publisher","first-page":"3305","DOI":"10.1109\/TITS.2017.2778939","volume":"19","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Huo, L., Lv, Z., et al.: A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Trans. Intell. Transp. Syst. 19(10), 3305\u20133319 (2018)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"6","key":"59_CR11","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1109\/JIOT.2016.2613111","volume":"3","author":"D Jiang","year":"2016","unstructured":"Jiang, D., Zhang, P., Lv, Z., et al.: Energy-efficient multi-constraint routing algorithm with load balancing for smart city applications. IEEE Internet Things J. 3(6), 1437\u20131447 (2016)","journal-title":"IEEE Internet Things J."},{"issue":"2017","key":"59_CR12","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1016\/j.neucom.2016.07.056","volume":"220","author":"D Jiang","year":"2017","unstructured":"Jiang, D., Li, W., Lv, H.: An energy-efficient cooperative multicast routing in multi-hop wireless networks for smart medical applications. Neurocomputing 220(2017), 160\u2013169 (2017)","journal-title":"Neurocomputing"},{"key":"59_CR13","doi-asserted-by":"crossref","unstructured":"Jiang, D., Wang, Y., Lv, Z., et al.: Intelligent optimization-based reliable energy-efficient networking in cloud services for IIoT networks. IEEE J. Selected Areas Commun. (2019)","DOI":"10.1109\/JSAC.2020.2980919"},{"issue":"2","key":"59_CR14","doi-asserted-by":"publisher","first-page":"3186","DOI":"10.1109\/JIOT.2018.2880190","volume":"6","author":"A Shahini","year":"2019","unstructured":"Shahini, A., Kiani, A., Ansari, N.: Energy efficient resource allocation in EH-Enabled CR networks for IoT. IEEE Internet Things J. 6(2), 3186\u20133193 (2019)","journal-title":"IEEE Internet Things J."},{"issue":"3","key":"59_CR15","first-page":"1","volume":"5","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Wang, W., Shi, L., et al.: A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Trans. Netw. Sci. Eng. 5(3), 1\u20132 (2018)","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"key":"59_CR16","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Qi, Z., Chen, W. Huang, Y.: TEST: an end-to-end network traffic classification system with spatio-temporal features extraction. In: 2019 IEEE International Conference on Smart Cloud (SmartCloud), Tokyo, Japan, pp. 131\u2013136 (2019)","DOI":"10.1109\/SmartCloud.2019.00032"},{"key":"59_CR17","doi-asserted-by":"crossref","unstructured":"Qi, S., Jiang, D., Huo, L.: A prediction approach to end-to-end traffic in space information networks. Mob. Netw. Appl. (2019)","DOI":"10.1007\/s11036-019-01424-2"},{"key":"59_CR18","unstructured":"Kim, E., Choi, Y.: Traffic monitoring system for 5G core network. In: 2019 Eleventh International Conference on Ubiquitous and Future Networks (ICUFN), Zagreb, Croatia, pp. 671\u2013673 (2019)."},{"key":"59_CR19","doi-asserted-by":"crossref","unstructured":"Wang, Y., Jiang, D., Huo, L., et al.: A new traffic prediction algorithm to software defined networking. Mob. Netw. Appl. (2019)","DOI":"10.1007\/s11036-019-01423-3"},{"issue":"5","key":"59_CR20","first-page":"1","volume":"13","author":"D Jiang","year":"2018","unstructured":"Jiang, D., Huo, L., Li, Y.: Fine-granularity inference and estimations to network traffic for SDN. Plos One 13(5), 1\u201323 (2018)","journal-title":"Plos One"},{"issue":"1","key":"59_CR21","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1109\/TNET.2019.2957008","volume":"28","author":"X Wang","year":"2020","unstructured":"Wang, X., et al.: The joint optimization of online traffic matrix measurement and traffic engineering for software-defined networks. IEEE\/ACM Trans. Netw. 28(1), 234\u2013247 (2020)","journal-title":"IEEE\/ACM Trans. Netw."},{"issue":"3","key":"59_CR22","doi-asserted-by":"publisher","first-page":"1332","DOI":"10.1109\/TITS.2019.2939290","volume":"21","author":"Y Gu","year":"2020","unstructured":"Gu, Y., Lu, W., Xu, X., Qin, L., Shao, Z., Zhang, H.: An improved bayesian combination model for short-term traffic prediction with deep learning. IEEE Trans. Intell. Transp. Syst. 21(3), 1332\u20131342 (2020)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"59_CR23","doi-asserted-by":"crossref","unstructured":"Huo, L., Jiang, D., Qi, S., et al.: An AI-based adaptive cognitive modeling and measurement method of network traffic for EIS. Mob. Netw. Appl. (2019)","DOI":"10.1007\/s11036-019-01419-z"},{"key":"59_CR24","doi-asserted-by":"crossref","unstructured":"Aung, S.T., Thein, T.: Internet traffic categories demand prediction to support dynamic QoS. In: 2020 5th International Conference on Computer and Communication Systems (ICCCS), Shanghai, China, pp. 650\u2013654 (2020)","DOI":"10.1109\/ICCCS49078.2020.9118431"},{"issue":"6","key":"59_CR25","doi-asserted-by":"publisher","first-page":"5412","DOI":"10.1109\/JIOT.2020.2978160","volume":"7","author":"MB Attia","year":"2020","unstructured":"Attia, M.B., Nguyen, K.K., Cheriet, M.: Dynamic QoS-aware scheduling for concurrent traffic in smart home. IEEE Internet Things J. 7(6), 5412\u20135425 (2020)","journal-title":"IEEE Internet Things J."},{"key":"59_CR26","doi-asserted-by":"crossref","unstructured":"Lemeshko, O., Yeremenko, O., Yevdokymenko, M., Hailan, A.M.: Tensor based load balancing under self-similar traffic properties with guaranteed QoS. In: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, pp. 293\u2013297 (2020)","DOI":"10.1109\/TCSET49122.2020.235442"},{"key":"59_CR27","doi-asserted-by":"crossref","unstructured":"Ren, S., Tang, G.: A reactive traffic flow estimation in software defined networks. In: 2020 5th International Conference on Computer and Communication Systems (ICCCS), Shanghai, China, pp. 585\u2013588 (2020)","DOI":"10.1109\/ICCCS49078.2020.9118430"},{"issue":"3","key":"59_CR28","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1109\/TNSM.2019.2924942","volume":"16","author":"T Mangla","year":"2019","unstructured":"Mangla, T., Halepovic, E., Ammar, M., Zegura, E.: Using session modeling to estimate HTTP-based video QoE metrics from encrypted network traffic. IEEE Trans. Netw. Serv. Manage. 16(3), 1086\u20131099 (2019)","journal-title":"IEEE Trans. Netw. Serv. Manage."},{"key":"59_CR29","doi-asserted-by":"crossref","unstructured":"Tian, F., Yu, Y., Li, D., Cui, J., Dong, Y.: QoE optimization for traffic offloading from LTE to WiFi. In: 2019 IEEE 8th Global Conference on Consumer Electronics (GCCE), Osaka, Japan, pp. 115\u2013116 (2019)","DOI":"10.1109\/GCCE46687.2019.9015615"},{"key":"59_CR30","doi-asserted-by":"crossref","unstructured":"Tang, S., Li, C., Qin, X., Wei, G.: Traffic classification for mobile video streaming using dynamic warping network. In: 2019 28th Wireless and Optical Communications Conference (WOCC), Beijing, China, pp. 1\u20135 (2019)","DOI":"10.1109\/WOCC.2019.8770669"},{"key":"59_CR31","doi-asserted-by":"publisher","unstructured":"Bao, R., Chen, L., Cui, P.: User behavior and user experience analysis for social network services. Wirel. Netw. (2020). https:\/\/doi.org\/10.1007\/s11276-019-02233-x","DOI":"10.1007\/s11276-019-02233-x"},{"key":"59_CR32","doi-asserted-by":"crossref","unstructured":"Oszmianski, J., Safjan, K., Dottling, M., Bohdanowicz, A.: Impact of traffic modeling and scheduling on delay and spectral efficiency of the WINNER system. In: VTC Spring 2008 - IEEE Vehicular Technology Conference, Singapore, pp. 2661\u20132665 (2008)","DOI":"10.1109\/VETECS.2008.583"},{"issue":"5","key":"59_CR33","doi-asserted-by":"publisher","first-page":"4098","DOI":"10.1109\/TVT.2018.2789498","volume":"67","author":"G Zhao","year":"2018","unstructured":"Zhao, G., Chen, S., Zhao, L., Hanzo, L.: Energy-spectral-efficiency analysis and optimization of heterogeneous cellular networks: a large-scale user-behavior perspective. IEEE Trans. Veh. Technol. 67(5), 4098\u20134112 (2018)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"6","key":"59_CR34","doi-asserted-by":"publisher","first-page":"3251","DOI":"10.1109\/TWC.2019.2912596","volume":"18","author":"G Zhao","year":"2019","unstructured":"Zhao, G., Chen, S., Qi, L., Zhao, L., Hanzo, L.: Mobile-traffic-aware offloading for energy- and spectral-efficient large-scale D2D-enabled cellular networks. IEEE Trans. Wirel. Commun. 18(6), 3251\u20133264 (2019)","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"59_CR35","doi-asserted-by":"crossref","unstructured":"Stahlbuhk, T., Shrader, B., Modiano, E.: Learning aloglrithms for mining queue length regret. In: 2018 IEEE International Symposium on Information (2018)","DOI":"10.1109\/ISIT.2018.8437817"},{"issue":"1","key":"59_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000024","volume":"5","author":"S Bubeck","year":"2012","unstructured":"Bubeck, S., Cesa-Bianchi, N.: Regret analysis of stochastic and nonstochastic multi-armed bandit problems. Found. Trends Mach. Learn. 5(1), 1\u2013122 (2012)","journal-title":"Found. Trends Mach. Learn."},{"issue":"2\u20133","key":"59_CR37","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1023\/A:1013689704352","volume":"47","author":"P Auer","year":"2002","unstructured":"Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2\u20133), 235\u2013256 (2002)","journal-title":"Mach. Learn."},{"key":"59_CR38","unstructured":"Krishnasamy, S., et al.: Regret of queueing bandits. In: Proceedings of Neural Information Processing Systems, pp. 1669\u20131677 (2016)"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Simulation Tools and Techniques"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-72792-5_59","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,25]],"date-time":"2022-12-25T13:50:47Z","timestamp":1671976247000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-72792-5_59"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030727918","9783030727925"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-72792-5_59","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"27 April 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SIMUtools","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Simulation Tools and Techniques","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guiyang","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":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"simutools2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/simutools.eai-conferences.org\/2020\/","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":"Confy +","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"354","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":"125","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":"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 (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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to COVID 19 pandemic the conference was held virtually.","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)"}}]}}