The design of an output data collection framework for NS-3

Abstract

An important design decision in the construction of a simulator is how to enable users to access the data generated in each run of a simulation experiment. As the simulator executes, the samples of performance metrics that are generated beg to be exposed either in their raw state or after having undergone mathematical processing. Also of concern is the particular format this data assumes when externalized to mass storage, since it determines the ease of processing by other applications or interpretation by the user. In this paper, we present a framework for the ns-3 network simulator for capturing data from inside an experiment, subjecting it to mathematical transformations, and ultimately marshaling it into various output formats. The application of this functionality is illustrated and analyzed via a study of common use cases. Although the implementation of our approach is specific to ns-3, this design presents lessons transferrable to other platforms.

Automating ns-3 experimentation in multi-host scenarios

“…The parametrizable models simplify the description of simulations, making ns-3 more accessible to non-experienced users. SAFE also provides automated data processing, data storage, and data visualization functionalities that are complemented by the ns-3 data collection framework (DCF) [11]. The DCF framework extends ns-3 with primitives to instrument simulations, and to collect, process, and aggregate simulated data across hosts.…”