On Evaluating Loss Performance Deviation: A Simple Tool and Its Practical Implications

Abstract

The focus of this paper is on developing and evaluating a practical methodology for determining if and when different types of traffic can be safely multiplexed within the same service class. The use of class rather than individual service guarantees offers many advantages in terms of scalability, but raises the concern that not all users within a class see the same performance. Understanding when and why a user will experience performance that differs significantly from that of other users in its class is, therefore, of importance. Our approach relies on an analytical model developed under a number of simplifying assumptions, which we test using several real traffic traces corresponding to different types of users. This testing is carried out primarily by means of simulation, to allow a comprehensive coverage of different configurations. Our findings establish that although the simplistic model does not accurately predict the absolute performance that individual users experience, it is quite successful and robust when it comes to identifying situations that can give rise to substantial performance deviations within a service class. As a result, it provides a simple and practical tool for rapidly characterizing real traffic profiles that can be safely multiplexed.

This work was supported in part through NSF grant ITR00-85930.