A framework for the simulation experimentation process
Proceedings of the 29th conference on Winter simulation
A comparison of mechanisms for improving TCP performance over wireless links
IEEE/ACM Transactions on Networking (TON)
A novel distributed call admission control for wireless mobile multimedia networks
WOWMOM '00 Proceedings of the 3rd ACM international workshop on Wireless mobile multimedia
Real-time prioritized call admission control in a base station scheduler
WOWMOM '00 Proceedings of the 3rd ACM international workshop on Wireless mobile multimedia
Performance evaluation of mobile wireless networks: a new perspective
MSWIM '01 Proceedings of the 4th ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Enabling Large-Scale Simulation: Selective Abstraction Approach to the Study of Multicast Protocol
MASCOTS '98 Proceedings of the 6th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
Quality of service guarantees in mobile computing
Computer Communications
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Simulation is a widely used technique in understanding and analyzing the properties and behavior of wireless networks. Simulation models abound in the wireless domain. Most of these models suffer from an abundance of parameters. Different models might use different parameters. Moreover, even for common parameters, there are no universally accepted standard values. This makes the task of analyzing simulation results a complicated one.We propose a framework to address this problem. One component of our framework is based on the reduction of the vast parameter space to a smaller, more compact one that encompasses only a few essential parameters. These parameters try to aggregate other parameters and hide the specifics of the underlying system, thereby easing the task of evaluating simulation results.The other component is based on a novel concept called steady state utilization which tries to capture the inherent capacity of a network. Using steady state utilization as the maximum potential capacity (without loss) of a network, we show how it can be used in the task of comparing results from different simulation models.