{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T05:55:45Z","timestamp":1773813345463,"version":"3.50.1"},"reference-count":33,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"crossref","award":["2017YFB1401300"],"award-info":[{"award-number":["2017YFB1401300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"crossref","award":["2017YFB1401302"],"award-info":[{"award-number":["2017YFB1401302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Research and Development Program of Jiangsu Province","award":["BE2017166"],"award-info":[{"award-number":["BE2017166"]}]},{"name":"Natural Science Foundation Outstanding Youth Fund of Jiangsu Province","award":["BK20170100"],"award-info":[{"award-number":["BK20170100"]}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["19KJB520046"],"award-info":[{"award-number":["19KJB520046"]}]},{"name":"Project of Nanjing University of Posts and Telecommunications, Six Talent Peaks project in Jiangsu Province","award":["JY-012"],"award-info":[{"award-number":["JY-012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Info. Tech. Dec. Mak."],"published-print":{"date-parts":[[2020,1]]},"abstract":"<jats:p> To improve the quality of service and network performance for the Flash P2P video-on-demand, the prediction Flash P2P network traffic flow is beneficial for the control of the network video traffic. In this paper, a novel prediction algorithm to forecast the traffic rate of Flash P2P video is proposed. This algorithm is based on the combination of the ensemble local mean decomposition (ELMD) and the generalized autoregressive conditional heteroscedasticity (GARCH). The ELMD is used to decompose the original long-related flow into the summation of the short-related flow. Then, the GRACH is utilized to predict the short-related flow. The developed algorithm is tested in a university\u2019s campus network. The predicted results show that our proposed method can further achieve higher accuracy than those obtained by existing algorithms, such as GARCH and Local Mean Decomposition and Generalized AutoRegressive Conditional Heteroskedasticity (LMD-GARCH) while keeping lower computational complexity. <\/jats:p>","DOI":"10.1142\/s0219622019500469","type":"journal-article","created":{"date-parts":[[2019,12,10]],"date-time":"2019-12-10T03:54:38Z","timestamp":1575950078000},"page":"127-141","source":"Crossref","is-referenced-by-count":6,"title":["A Novel Flash P2P Network Traffic Prediction Algorithm based on ELMD and Garch"],"prefix":"10.1142","volume":"19","author":[{"given":"Yimu","family":"Ji","sequence":"first","affiliation":[{"name":"School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210023, China"},{"name":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, Jiangsu 210023, China"},{"name":"Institute of 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