Multi agent based simulation: beyond social simulation
MABS 2000 Proceedings of the second international workshop on Multi-agent based simulation
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users' Guide
Proceedings of the First International Workshop on Multi-Agent Systems and Agent-Based Simulation
SENS: A Sensor, Environment and Network Simulator
ANSS '04 Proceedings of the 37th annual symposium on Simulation
Experimental evaluation of wireless simulation assumptions
MSWiM '04 Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
J-Sim: A Simulation Environment for Wireless Sensor Networks
ANSS '05 Proceedings of the 38th annual Symposium on Simulation
Integrating agent based modeling into a discrete event simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Characterization of an unintentional Wi-Fi interference device-the residential microwave oven
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Using the OMNeT++ discrete event simulation system in education
IEEE Transactions on Education
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The constantly growing number of wireless devices and applications makes efficient spectrum utilization critical. Cognitive radio technology offers a solution by employing opportunistic and adaptive selection of transmission parameters and communication strategies. Due to the lack of general simulation tools available for analyzing cognitive radio networks, we propose an agent-based framework for cognitive radio studies. Unlike existing simulation tools, our design facilitates modeling of the physical environment along with the behavior of a network of cognitive radios. The inclusion of real-life spectrum occupancy data collected by the IIT Spectrum Observatory brings the modeled environment very close to reality. Additionally, because of its agent-based nature, our framework enables to study emergent and behavioral aspects of large and heterogeneous cognitive radio networks, an important factor that is being constantly neglected. Preliminary results show that presented solution is promising, but requires more development.