Computer simulation: a practical perspective
Computer simulation: a practical perspective
TOSSIM: accurate and scalable simulation of entire TinyOS applications
Proceedings of the 1st international conference on Embedded networked sensor systems
An overview of the OMNeT++ simulation environment
Proceedings of the 1st international conference on Simulation tools and techniques for communications, networks and systems & workshops
A Survey on Sensor Webs Simulation Tools
SENSORCOMM '08 Proceedings of the 2008 Second International Conference on Sensor Technologies and Applications
A framework for QoI-inspired analysis for sensor network deployment planning
WICON '07 Proceedings of the 3rd international conference on Wireless internet
MM-ulator: Towards a Common Evaluation Platform for Mixed Mode Environments
SIMPAR '08 Proceedings of the 1st International Conference on Simulation, Modeling, and Programming for Autonomous Robots
COOJA/MSPSim: interoperability testing for wireless sensor networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Adequate motion simulation and collision detection for soccer playing humanoid robots
Robotics and Autonomous Systems
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For rescue and surveillance scenarios, the Mixed-Mode Environments (MMEs) for data acquisition, processing, and dissemination have been proposed. Evaluation of the algorithms and protocols developed for such environments before deployment is vital. However, there is a lack of realistic testbeds for MMEs due to reasons such as high costs for their setup and maintenance. Hence, simulation platforms are usually the tool of choice when testing algorithms and protocols for MMEs. However, existing simulators are not able to fully support detailed evaluation of complex scenarios in MMEs. This is usually due to lack of highly accurate models for the simulated entities and environments. This affects the results which are obtained by using such simulators. In this paper, we highlight the need to consider the Quality of Simulations (QoSim), in particular aspects such as accuracy, validity, certainty, and acceptability. The focus of this paper is to understand the gap between real-world experiments and simulations for MMEs. The paper presents key QoSim concepts and characteristics for MMEs simulations, describing the aspects of contents of simulation, processing of simulation, and simulation outputs. Eventually, a road map for improving existing simulation environments is proposed.