Wireless sensor networks are widely deployed and implicitly characterized by stringent energy and computation constraints. Sensor nodes are vulnerable to false positive and false negative attacks that inject false data through compromised nodes. Such attacks cause false alarms with energy drain and information loss. Although several en-route filtering schemes have been designed to detect the attacks, they focus on saving energy through early filtering or continuous delivery of data in accordance with verification records; they cannot exclude compromised nodes. In this paper, we propose a scheme that effectively identifies the compromised nodes and copes with new attacks using a context-aware architecture. In addition, the proposed scheme improves the security strength and energy efficiency of the network. Simulation results validate that the proposed scheme provides energy savings of up to 45 percent and allows fewer attack successes than the existing scheme.

Large-scale wireless sensor networks are characterized by stringent energy and computation restrictions. It is exceedingly difficult to change a sensor network’s environment configurations, such as the number of sensor nodes, after deployment of the nodes. Although several simulators are able to variously construct simulation models for sensor networks before their deployment, the configurations should be modified with extra human effort as the simulators cannot freely generate diverse models. In this paper, we propose a novel framework, called a system entity structure and model base for large-scale wireless sensor networks (WSN-SES/MB), which is based on discrete event system specification formalism. Our proposed framework synthesizes the structure and models for sensor networks through our modeling construction process. The proposed framework achieves time and cost savings in constructing discrete event simulation-based models. In addition, the framework increases the diversity of simulation models by the process’s pruning algorithm. The simulation results validate that the proposed framework provides up to 8% time savings and up to 23% cost savings as compared to the manual extra effort.

Computer vehicle simulators are used to model real-world situations to overcome time and cost limitations. The vehicle simulators provide virtual scenarios for real-world driving. Although the existing simulators precisely observe movement on the basis of good-quality graphics, they focus on a few driving vehicles instead of accident simulation. In addition, it is difficult to represent vehicle collisions. We propose a vehicle crash simulator with simulation and animation components. The proposed simulator synthesizes and simulates models of vehicles and environments. The simulator animates corresponding to the simulation through the execution results. The simulation results validate that the proposed simulator provides collision and non-collision results according to the speed of two vehicles at an intersection.