Enabling richer statistical MANET simulations through cluster computing

Abstract

The wide-scale adoption of modern smart phones and other multi-radio mobile devices, has begun to provide pragmatic deployment environments for non-cellular mobile ad hoc network (MANET) services (i.e., for disaster recovery scenarios, peered mobile games, social networking applications, etc.). User perceptions of the quality of such MANET services will be driven, in part, by standard network-level quality of service (QoS) metrics such as delay, jitter, throughput, etc. Much of the existing MANET literature has explored these issues, as well as MANET routing protocol design, through single computer Monte Carlo simulations (e.g., via ns-2, ns-3, OMNeT++, or OpNet). Results are then reported as the averages of these Monte Carlo runs. As is well known from probability and statistics, such averaging is only meaningful when applied across statistically ergodic data (i.e., data drawn from the same underlying distribution). But, assessing the validity of this underlying ergodic assumption requires transitioning to more rigorous cluster-based MANET simulation frameworks. This work highlights the theoretical rationale for such ergodicity testing, the developments of a cluster-based framework, the STARs framework, to support such testing, and the results and insights obtained by using this framework to evaluate the popular DYMO and OLSR MANET routing protocols. This work also discusses why the insights ergodic testing provides are of interest to potential real-world MANET deployments.