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A multi-modal simulation system for wireless sensor networks: a comparison study considering stationary and mobile sink and event

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Abstract

The wireless sensor networks (WSNs) are a sensing, computing and communication infrastructure that are able to observe and respond to phenomena in the natural environment and in our physical and cyber infrastructure. In order to simulate WSNs, we implemented a simulation system. We implement our system as a multi-model system considering different topologies, radio models, routing protocols and number of nodes. In this work, we consider the goodput, depletion and delay metrics to evaluate the performance of WSNs for AODV and DSR routing protocols considering TwoRayGround and Shadowing radio models, lattice and random topologies, and different number of nodes. We investigate the performance of WSNs for stationary and mobile sink, and stationary and mobile event. The simulation results have shown that for both stationary and mobile sinks, the goodput decreases with the increase of number of sensor nodes. In the case of mobile sink, the goodput is stable and better than in case of stationary sink, especially when the number of nodes is increased. In case of mobile sink, the consumed energy is better than stationary sink (about half of stationary sink). In case of mobile sink, the consumed energy of lattice topology is better than random topology for large number of nodes. In the case of mobile event, the goodput of AODV is better than DSR and it is stable. For large number of nodes, the goodput of DSR is low and unstable. In the case of mobile event, the depletion of Shadowing is lower than TwoRayGround. For low transmission rate, the delay of Shadowing is lower than TwoRayGround. However, for large transmission rate, the delay of Shadowing is higher than TwoRayGround.

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Correspondence to Shinji Sakamoto.

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Matsuo, K., Elmazi, D., Liu, Y. et al. A multi-modal simulation system for wireless sensor networks: a comparison study considering stationary and mobile sink and event. J Ambient Intell Human Comput 6, 519–529 (2015). https://doi.org/10.1007/s12652-015-0277-8

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  • DOI: https://doi.org/10.1007/s12652-015-0277-8

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