Design-time simulation of a large-scale, distributed object system

Abstract

We present a case study in using simulation at design time to predict the performance and scalability properties of a large-scale distributed object system. The system, called Consul, is a network management system designed to support hundreds of operators managing millions of network devices. It is essential that a system such as Consul be designed with performance and scalability in mind, but due to Consul's complexity and scale, it is hard to reason about performance and scalability using ad hoc techniques. We built a simulation of Consul's design to guide the design process by enabling performance and scalability analysis of various design alternatives. A major challenge in doing design-time simulation is that many parameters for the simulation are based on estimates rather than measurements. We developed analysis methods that derive conclusions that are valid in the presence of estimation errors. In this article, we describe our scalability analysis method for design simulations of distributed object systems. The main idea is to use relative and comparative reasoning to analyze design alternatives and compare transaction behaviors. We demonstrate the analysis approach by describing its application to Consul.

A Simulation Environment for Job Scheduling on Distributed Systems

“…Simulation models have been widely used to study computer systems and network properties [5,81. Damson [6] uses a simulation to predict the performance and scalability properties of a large scale distributed object system. Another example is HASE [I] that is used to simulate computer architectures at multiple levels of abstraction, including hardware and software.…”