Title
Sapphire: Statistical Characterization and Model-Based Adaptation of Networked Applications
Abstract
Many modern networked applications require specific levels of service quality from the underlying network. Moreover, next-generation networked applications are expected to adapt to changes in the underlying network, services, and user interactions. While some applications have built-in adaptivity, the adaptation itself requires specification of a system model. This paper presents Sapphire, an experimental approach for systematic model generation for application adaptation within a target network. It employs a nearly-automated, statistical design of experiments to characterize the relationships of both application and network-level parameters. First, it applies the Analysis of Variance (ANOVA) method to identify the most significant parameters and their interactions that affect performance. Next, it generates a model of application performance with respect to these parameters within the ranges of measurements. The key benefit of the framework is the integration of several well-established concepts of statistical modeling and distributed systems in the form of simple APIs so that existing applications can take advantage of it. We demonstrate the usefulness and flexibility of Sapphire by generating a performance model of an audio streaming application. We show that many existing multimedia and QoS-sensitive applications can exploit a statistical modeling approach such as Sapphire to incorporate application adaptivity. The approach can also be used for feedback control of distributed applications, tuning network and application parameters to achieve service levels in a target network.
Year
DOI
Venue
2006
10.1109/TPDS.2006.177
IEEE Trans. Parallel Distrib. Syst.
Keywords
Field
DocType
underlying network,application adaptivity,application performance,tuning network,application adaptation,modern networked application,statistical characterization,application parameter,target network,model-based adaptation,networked applications,next-generation networked application,qos-sensitive application,level of service,measurements,statistical model,service level,analysis of variance,distributed application,system modeling,statistical analysis,feedback control,distributed system,next generation network,design of experiment
Service level,Level of service,Computer science,Real-time computing,Exploit,Performance model,Statistical model,Statistical design,System model,Distributed computing,Statistical analysis
Journal
Volume
Issue
ISSN
17
12
1045-9219
Citations 
PageRank 
References 
1
0.36
23
Authors
3
Name
Order
Citations
PageRank
Abhijit Bose121920.83
Mohamed El Gendy2704.51
Kang G. Shin3140551487.46