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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.

In wireless sensor networks, sensors are extremely vulnerable to false positive and false negative attacks due to their stringent energy and computational constraints. Several en-route filtering schemes mainly focus on saving energy through early detection of false data within a short distance against these attacks; however, they cannot immediately block the false data injected by compromised nodes. A security scheme uses context-aware architecture for a probabilistic voting–based filtering scheme to detect the compromised nodes and block the injection of false data, unlike security protocols. Although these schemes effectively obstruct the false data forwarding, they cannot make any detour around the compromised node to avoid it during data forwarding. In this article, we propose a discrete event simulation–based energy efficient path determination scheme that takes a detour around the compromised node against the attacks. Our proposed scheme extracts candidate paths considering the network status and selects a path with the highest energy efficiency from among the candidates using discrete event simulation. Simulation results indicate that the proposed scheme provides energy savings of up to 12% while maintaining the security strength against the two attacks compared to the existing schemes.

Wireless sensor networks (WSNs) consist of a large number of sensor nodes that monitor the environment and a few base stations that collect the sensor readings. Individual sensor nodes are subject to compromised security because they may be deployed in hostile environments and each sensor node communicates wirelessly. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a wormhole by directly linking two compromised nodes or using out-of-band channels. If these two kinds of attacks occur simultaneously in a network, existing methods cannot defend against them adequately. We thus propose a secure routing method for detecting false report injections and wormhole attacks in wireless sensor networks. The proposed method uses ACK messages for detecting wormholes and is based on a statistical en-route filtering (SEF) scheme for detecting false reports. Simulation results show that the proposed method reduces energy consumption by up to 20% and provide greater network security.