江苏大学主页平台管理系统王昌达--中文主页--论文成果

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王昌达

性别：男
学历：博士研究生毕业
学位：博士
在职信息：在本单位任职
所在单位：克兰菲尔德研究生院
入职时间： 1994-07-01

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论文成果

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[1] 王昌达.AMSO-INT: Reinforcement Learning-Driven Dynamic Adaptive In-Band Telemetry.PROCEEDINGS OF THE 2025 2ND WORKSHOP ON NETWORKS FOR AI COMPUTING, SIGCOMM 2025
[2] 王昌达.Service Function Chain Migration: A Survey.Computers
[3] 王昌达.Joint Optimization for Fairness-Revenue Adjustable Network Slices Embedding.ACM International Conference Proceeding Series
[4] 王昌达.Link failure recovery through nested cycles.ACM International Conference Proceeding Series
[5] 王昌达.基于网络熵变率的节点重要性排序方法.计算机与数字工程
[6] 王昌达.A Deep Learning Approach to Online Social Network Account Compromisation.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
[7] 王昌达.基于广义网络温度的链路备份方法研究.软件导刊
[8] 王昌达.服务功能链部署的能耗与负载均衡联合优化.计算机应用研究
[9] 王昌达.The core nodes identification method through adjustable network topology information.PROCEEDINGS OF THE 7TH ASIA-PACIFIC WORKSHOP ON NETWORKING, APNET 2023
[10] 王昌达.二维隐蔽时间信道构建的研究.计算机与数字工程
[11] 王昌达.Fuzzy Local Information and Bhattacharya-Based C-Means Clustering and Optimized Deep Learning in Spa.ELECTRONICS
[12] 王昌达.Compact Provenance Scheme Through Packet Path Index Differences in WSNs.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
[13] 王昌达.Network Anomaly Early Warning through Generalized Network Temperature and Deep Learning.JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
[14] 王昌达.Searchable Encryption for Integrating Cloud and Sensor Networks with Secure Updates.AD HOC & SENSOR WIRELESS NETWORKS
[15] 王昌达.基于压缩感知的网络流关联方法.计算机应用研究
[16] 王昌达.Stepwise Refinement Provenance Scheme for Wireless Sensor Networks.IEEE Internet of Things Journal
[17] 王昌达.Generating indoor Wi-Fi fingerprint map based on crowdsourcing.WIRELESS NETWORKS
[18] 王昌达.Network Temperature: A Novel Statistical Index for Networks Measurement and Management.ACM TRANSACTIONS ON INTERNET TECHNOLOGY
[19] 王昌达.SDN中基于MS-KNN算法的LFA检测方法.计算机应用研究
[20] 王昌达.A Node Importance Ranking Method Based on the Rate of Network Entropy Changes.Proceedings - 2021 17th International Conference on Mobility, Sensing and Networking, MSN 2021

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