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Statistical characterization for per-hop qos.
| Content Provider | CiteSeerX |
|---|---|
| Author | Bose, Abhijit Gendy, Mohamed El Shin, Kang G. Wang, Haining |
| Abstract | The Differentiated Services (DiffServ) architecture is designed to provide scalable network-level Quality of Service (QoS) via service differentiation at intermediate nodes of a network (called Per-Hop Behaviors (PHBs)). Per-hop QoS is measured in terms of throughput, delay, jitter, and loss rate experienced by traffic crossing a PHB. In this paper, we use a statistical approach that is based on experiments on a real network testbed to characterize the per-hop QoS of a given PHB. Specifically, we employ a full factorial statistical design of experiments to study the effects of different PHB configurations and input traffic scenarios on perhop QoS. We use Analysis of Variance (ANOVA) to identify the input and PHB configuration parameters that have the most significant influence on per-hop QoS. Then, multiple regression analysis is applied to construct models for the per-hop QoS with respect to these parameters. The overall approach is shown to be effective and capable of characterizing any given PHB, within the ranges of the experiments, and for construction of functional relationships for the PHB output parameters. We are also able to identify the operational differences between different realizations of a given PHB. The approach in this paper forms a "fundamental" step towards achieving predictable end-to-end QoS when applying statistical QoS control at intermediate nodes. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Predictable End-to-end Qos Full Factorial Statistical Design Phb Output Parameter Overall Approach Input Traffic Scenario Functional Relationship Multiple Regression Analysis Statistical Qos Control Phb Configuration Parameter Differentiated Service Statistical Approach Different Realization Intermediate Node Perhop Qos Different Phb Configuration Per-hop Qos Per-hop Behavior Service Differentiation Significant Influence Statistical Characterization Loss Rate Operational Difference Fundamental Step Towards Scalable Network-level Quality Real Network |
| Content Type | Text |
| Resource Type | Article |
