Ubiquitous environment simulation

A Simulator for Smartspace Application with 3D Virtual Space

we propose a simulator which provides a virtual testbed for reliable and inexpensive development of application software for Smartspace. The proposed simulator allows application programmers to set up virtual devices in a 3D virtual space, simulate communication between the devices, and observe their behavior. Moreover, the simulator can reproduce transitions of physical quantities such as room temperature as a consequence of device actions, display the situation of the virtual space in real-time from an arbitrary viewpoint, and move virtual inhabitants in the space. Some existing simulators can simulate behavior and communication of devices, but no existing simulator can reproduce richer context such as transitions of physical quantities and user movements. Reproducing richer context by our simulator will make it easier to develop smartspace applications. We constructed virtual Smarthome consisting of 8 rooms and application software which controls information appliances according to context change, and conducted experimental validation of usefulness of the simulator. As a result, we confirmed that our simulator has enough performance to simulate Smarthome with practical size and is useful to detect bugs of application software.

Published Paper

  • Nishikawa, H., Yamamoto, S., Tamai, M., Nishigaki, K., Kitani, T., Shibata, N., Yasumoto, K., and Ito, M.: A Simulator for Smartspace Application with 3D Virtual Space, IPSJ Journal, Vol.49,No.2,pp. 774-785 (2008-02)
  • Nishikawa, H., Yamamoto, S., Tamai, M., Nishigaki, K., Kitani, T., Shibata, N., Yasumoto, K., and Ito, M.: UbiREAL: Realistic Smartspace Simulator for Systematic Testing, Proc. of the 8th Int’l Conf. on Ubiquitous Computing (UbiComp2006), LNCS4206, pp. 459-476 (Sep. 2006).

Enhancing Collaboration Support Function into Smartspace Simulator

masayoshi-yo_poster
We propose a framework for the smartspace simulator which runs simulation of smartspace applications synchronously on multiple terminals while displaying different parts of the target smartspace with different layouts
on the screens of those terminals. It takes a great labor and expense to confirm the correctness of the behavior and find bugs during the smartspace development since devices are automatically controlled depending on contexts of users and environment. Furthermore, in order to develop a largescale smartspace composed of many sensors and home appliances, it will be difficult to understand entire behavior of smartspace and find bugs due to complex dependencies between the devices. Existing smartspace simulators are supposed to run simulation on a single terminal, thus it has no functions for facilitating more than two developers to collaborate in confirming correct behavior and finding bugs through simulation. In order to solve the above mentioned problem, we integrate a function which enables synchronous simulation of the smartspace on multiple terminals and a function which allows multiple developers to collaborate in confirming correct behavior and finding bugs by displaying different parts of the smartspace with different layouts on those terminals.

Published Paper

  • Yoshida, M., Tamai, M., Shibata, N., Yasumoto, K.: Enhancing Collaboration Support Function into Smartspace Simulator, Proc. of IPSJ DICOMO 2012 Symposium.

Cost-Efficient Deployment for Full-Coverage and Connectivity in Indoor 3D WSNs

In WSNs, coverage of the target field and wireless connectivity among sensor nodes are important criteria in terms of the performance required for WSN. In indoor environments, the target field is in general 3D space, thus WSNs deployed for such environments are called 3D WSNs. The sensor node deployment problem for 3D coverage and connectivity is NP-hard even without obstacles in the target field. Furthermore, no study has systematically examined the optimal 3D WSN deployment considering both obstacles and deployment cost. In this paper, we propose a new heuristic algorithm for computing a near optimal sensor node deployment that minimizes the cost for achieving the full coverage and node connectivity of a 3D target space with obstacles. First, we represent the monitoring area as well as the sensor node deployable area in the target 3D space, by a set of grid points. Our algorithm puts sensor nodes one by one on a grid point of the deployable area in the descendant order of the cost-performance value (i.e., how many monitoring space points are covered by the deployable area point per unit deployment cost) of the deployable area points. Then, the algorithm adds extra nodes to cover the shadow area of each node’s sensing region cut off by the obstacles. Moreover, to ensure the connectivity among all WSN nodes, the algorithm adds extra nodes and/or moves each unconnected sensor node one by one towards the closest connected sensor node in order to reduce the number of extra nodes. We implemented our proposed method in the UbiREAL simulator and evaluated the performance through simulations. As a result, we have confirmed that our proposed method can provide reliable and cost-efficient solutions for WSN deployment in indoor environments.

Published Paper

  • Marc T. Kouakou, Shinya Yamamoto, Keiichi Yasumoto, Minoru Ito: Deployment planning tool for indoor 3D-WSNs, Adjunct Proceedings of UbiComp 2010, Demo, pp. 369-370 (Sep. 2010).
  • Kouakou, N. M. T., Yamamoto, S., Yasumoto, K., Ito, M.: Cost-Efficient Deployment for Full-Coverage and Connectivity in Indoor 3D WSNs, IPSJ DICOMO 2010 Symposium,pp. 1975 – 1982,(2010-07).
  • Marc T. Kouakou, Shinya Yamamoto, Keiichi Yasumoto, Minoru Ito: Cost-Efficient Sensor Placement for Full Coverage of 3D Indoor Space with Moving Obstacles, IPSJ SIG Tech. Rep., Vol.2010-MBL-57 No.5, pp.1-8 (Mar. 2011).

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