{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T01:02:44Z","timestamp":1780794164366,"version":"3.54.1"},"reference-count":0,"publisher":"River Publishers","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JWE"],"abstract":"<jats:p>Large-scale interactive online education platforms present significant challenges to traditional elastic scaling strategies based on static thresholds due to their dynamic and unpredictable load characteristics. This article designs and implements a cloud native high-availability network infrastructure centered around an intelligent elastic scaling model that integrates time series prediction and reinforcement learning. This architecture deeply integrates microservices and service mesh technology, predicting short-term resource requirements through historical load and contextual information (such as course schedules), and driving Kubernetes clusters to perform pre-scaling. The research is validated through simulation analysis and real prototype system experiments. The results show that in the simulation environment, the model improves resource prediction accuracy by 25% compared to traditional Horizontal Pod Autoscaler (HPA) strategies, and reduces service level agreement (SLA) violation rates by more than 60% during sudden traffic. In practical systems, the average response delay during peak periods is reduced by 40%, resource utilization increases by 35%, and system availability reaches 99.99%, significantly improving service quality and resource utilization efficiency.<\/jats:p>","DOI":"10.13052\/jwe1540-9589.2542","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:35:49Z","timestamp":1779669349000},"source":"Crossref","is-referenced-by-count":0,"title":["Design and Implementation of a High-availability Network Infrastructure for Large-scale Interactive E-learning"],"prefix":"10.13052","author":[{"given":"Xiaoyong","family":"Su","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"5195","published-online":{"date-parts":[[2026,5,24]]},"container-title":["Journal of Web Engineering"],"original-title":[],"link":[{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JWE\/article\/download\/31209\/23870","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JWE\/article\/download\/31209\/23871","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JWE\/article\/download\/31209\/23870","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,7]],"date-time":"2026-06-07T00:36:46Z","timestamp":1780792606000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JWE\/article\/view\/31209"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,24]]},"references-count":0,"URL":"https:\/\/doi.org\/10.13052\/jwe1540-9589.2542","relation":{},"ISSN":["1544-5976","1540-9589"],"issn-type":[{"value":"1544-5976","type":"electronic"},{"value":"1540-9589","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5,24]]}}}