Abstract
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.
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References
McHaney, R.: Computer simulation: a practical perspective. Academic Press Professional, Inc., San Diego (1991)
Eriksson, J.: Detailed simulation of heterogeneous wireless sensor networks. PhD thesis, Uppsala University, Department of Information Technology (May 2009)
Kropff, M., Reinl, C., Listmann, K., Petersen, K., Radkhah, K., Shaikh, F.K., Herzog, A., Strobel, A., Jacobi, D., von Stryk, O.: MM-ulator: Towards a common evaluation platform for mixed mode environments. In: Carpin, S., Noda, I., Pagello, E., Reggiani, M., von Stryk, O. (eds.) SIMPAR 2008. LNCS (LNAI), vol. 5325, pp. 41–52. Springer, Heidelberg (2008)
Zahedi, S., Srivastava, M.B., Bisdikian, C.: A computational framework for quality of information analysis for detection-oriented sensor networks. In: Military Communications Conference, MILCOM 2008., pp. 1–7. IEEE, Los Alamitos (2008)
Gelenbe, E., Hey, L.: Quality of information: An empirical approach. In: 5th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2008, pp. 730–735 (September 2008)
Zahedi, S., Bisdikian, C.: A framework for QoI-inspired analysis for sensor network deployment planning. In: WICON 2007: Proceedings of the 3rd International Conference on Wireless Internet, pp. 1–8. ICST, Brussels (2007)
Thornley, D.J., Young, R.I., Richardson, P.J.: From mission specification to quality of information measures-closing the loop in military sensor networks. In: ACITA 2008 (2008)
Bisdikian, C., Damarla, R., Pham, T., Thomas, V.: Quality of information in sensor networks. In: ITA 2007 (2007)
Levis, P., Lee, N., Welsh, M., Culler, D.: TOSSIM: Accurate and scalable simulation of entire TinyOS applications. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp. 126–137. ACM, New York (2003)
The Network Simulator NS-2, http://www.isi.edu/nsnam/ns/
Varga, A., Hornig, R.: An overview of the OMNeT++ simulation environment. In: Simutools 2008: Proceedings of the 1st International Conference on Simulation Tools and Techniques for Communications, Networks and Systems & Workshops, pp. 1–10. ICST, Brussels (2008)
Friedmann, M., Petersen, K., von Stryk, O.: Adequate motion simulation and collision detection for soccer playing humanoid robots. Robotics and Autonomous Systems 57, 786–795 (2009)
Lewis, M., Wang, J., Hughes, S.: USARSim: Simulation for the Study of Human-Robot Interaction. Journal of Cognitive Engineering and Decision Making 2007, 98–120 (2007)
Gerkey, B.P., Vaughan, R.T., Howard, A.: The Player/Stage Project: Tools for Multi-Robot and Distributed Sensor Systems. In: Proceedings of the 11th International Conference on Advanced Robotics, pp. 317–323 (2003)
Koenig, N., Howard, A.: Design and use paradigms for gazebo, an open-source multi-robot simulator. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2149–2154 (2004)
Michel, O.: Cyberbotics ltd. webots tm: Professional mobile robot simulation. Int. Journal of Advanced Robotic Systems 1, 39–42 (2004)
Friedmann, M.: Simulation of Autonomous Robot Teams With Adaptable Levels of Abstraction. PhD thesis, Technische Universität Darmstadt (November 30, 2009)
Curren, D.: A survey of simulation in sensor networks. Technical report, University of Binghamton
Mekni, M., Moulin, B.: A survey on sensor webs simulation tools. In: Second International Conference on Sensor Technologies and Applications, SENSORCOMM 2008, pp. 574–579 (25-31, 2008)
Mogre, P.S., Hollick, M., d’Heureuse, N., Heckel, H.W., Krop, T., Steinmetz, R.: A Graph-based Simple Mobility Model. In: 4th Workshop zu Mobilen Ad Hoc Netzen, KiVS 2007 (2007)
Österlind, F., Dunkels, A., Eriksson, J., Finne, N., Voigt, T.: Demo abstract: Cross-level simulation in cooja. In: Proceedings of the First IEEE International Workshop on Practical Issues in Building Sensor Network Applications (2006)
Eriksson, J., Österlind, F., Finne, N., Tsiftes, N., Dunkels, A., Voigt, T., Sauter, R., Marrón, P.J.: Cooja/mspsim: interoperability testing for wireless sensor networks. In: Simutools 2009: Proceedings of the 2nd International Conference on Simulation Tools and Techniques, pp. 1–7. ICST, Brussels (2009)
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Sachidananda, V. et al. (2010). Simulation and Evaluation of Mixed-Mode Environments: Towards Higher Quality of Simulations. In: Ando, N., Balakirsky, S., Hemker, T., Reggiani, M., von Stryk, O. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2010. Lecture Notes in Computer Science(), vol 6472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17319-6_15
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DOI: https://doi.org/10.1007/978-3-642-17319-6_15
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