SB-10-2 Analysis of Relationship between TCP Flow Behavior and Utilization of Bottleneck Link
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概要
- 論文の詳細を見る
- 社団法人電子情報通信学会の論文
- 2001-08-29
著者
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ISHIBASHI Keisuke
NTT Information Sharing Platform Laboratories, NTT Corporation
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Kawahara Ryoichi
Ntt Information Sharing Platform Laboralories Ntt'corporation
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Ishibashi Keisuke
Ntt Information Sharing Platform Laboralories Ntt'corporation
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Ishibashi Keisuke
Ntt Information Sharing Laboratories Ntt Corporation
関連論文
- Structures of Human Relations and User-Dynamics Revealed by Traffic Data(Human Communication I)
- Detection of TCP Performance Degradation Using Link Utilization Statistics(Network)
- Method of Bandwidth Dimensioning and Management for Aggregated TCP Flows with Heterogeneous Access Links(Internet)
- A Method of Bandwidth Dimensioning and Management Using Flow Statistics(Network Management/Operation)
- A Method of IP Traffic Management Using the Relationship between TCP Flow Behavior and Link Utilization(Network Management/Operation)
- Packet Sampling TCP Flow Rate Estimation and Performance Degradation Detection Method
- Finding Cardinality Heavy-Hitters in Massive Traffic Data and Its Application to Anomaly Detection
- Capacity Dimensioning of VPN Access Links for Elastic Traffic in the Hose Model(Network)
- Capacity Dimensioning of VPN Access Links for Elastic Traffic in the Hose Model
- Proposal and Evaluation of Method to Estimate Packet Loss-Rate Using Correlation of Packet Delay and Loss(New Technologies in the Internet and their Applications)
- SB-10-2 Analysis of Relationship between TCP Flow Behavior and Utilization of Bottleneck Link
- SB-10-3 Is the Hurst Parameter Sufficient for Evaluating the Performance of Bursty Network Traffic?
- Method of Implementing GFR Service in Large-Scale Networks Using ABR Control Mechanism and Its Performance Analysis
- VoIP Quality Measurement System Using Flow Mediation for Large-Scale IP Networks
- Traffic Monitoring System Based on Correlation between BGP Messages and Traffic Data
- Effects of Sampling and Spatio/Temporal Granularity in Traffic Monitoring on Anomaly Detectability