In cluster-based wireless sensor networks, cluster heads (CHs) gather and fuse data packets from sensor nodes; then, they forward fused packets to the sink node (SN). This helps wireless sensor networks balance energy effectively and efficiently to prolong their lifetime. However, cluster-based WSNs are vulnerable to selective forwarding attacks. Compromised CHs would become malicious and launch selective forwarding attacks in which they drop part of or all the packets from other nodes. In this paper, a data clustering algorithm (DCA) for detecting a selective forwarding attack (DCA-SF) is proposed. It can capture and isolate malicious CHs that have launched selective forwarding attacks by clustering their cumulative forwarding rates (CFRs). The DCA-SF algorithm has been strengthened by changing the DCA parameters (Eps, Minpts) adaptively. The simulation results show that the DCA-SF has a low missed detection rate of 1.04% and a false detection rate of 0.42% respectively with low energy consumption.Keywords: data clustering algorithm; selective forwarding attack; cumulative forwarding rate; cluster-based WSN IntroductionA wireless sensor network (WSN) is a self-organizing network formed by a mass of small and cheap sensor nodes, which have low energy, poor computing ability, and small storage. The cluster-based WSN has been widely applied in large-scale data gathering WSNs [1,2]. In the dense cluster-based WSN, as shown in Figure 1, member nodes (MNs) send data packets to their cluster heads (CHs). Then, CHs forward these packets to the next-hop CHs until they reach the sink node (SN). In this way, each CH does not have to exchange data with the SN directly. On the one hand, the direct communication between the CH and SN may fail due to the long-distance or poor channels. On the other hand, in some conditions, the energy cost of multi-hop communication is less than that of direct long-distance communication. All the nodes in the network take turns to act as CHs, so the energy consumption can get balanced. The network lifetime also becomes longer.

Because of the inherent safety feature, the modular high temperature gas-cooled reactor (MHTGR) has been seen as one of the best candidates for the next generation of nuclear power plants. Power-regulation is a key technique to provide safe, stable and efficient plant operation for the multi-reactor-module power plants. Based on the successful design and operation of Chinese test high temperature gas-cooled reactor HTR-10, the high temperature gas cooled reactor pebble-bed module (HTR-PM) project is proposed. Since the HTR-PM is composed of two interconnected nuclear steam supply system (NSSS), the operation strategy of the multi-reactor-modular HTR-PM is different from that of those one-reactor-modular high temperature reactors such as HTR-10. In order to design and verify the operation strategy for HTR-PM, it is necessary to establish a real-time simulation platform. The design and development of this platform is presented in this paper.

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Because of its strong inherent safety features and high outlet temperature, the modular high temperature gas-cooled nuclear reactor (MHTGR) is already seen as the central part of the next generation of nuclear plants. Such power plants are being considered for industrial applications with a wide range of power levels, and thus power-level control is an important technique for their efficient and stable operation. Stimulated by the high regulation performance provided by nonlinear controllers, a novel dynamic output-feedback nonlinear power-level regulator is developed in this paper based on the technique of iterative damping assignment (IDA). This control strategy can provide the L 2 disturbance attenuation performance under modeling uncertainty or exterior disturbance, and can also guarantee the globally asymptotic closed-loop stability without uncertainty and disturbance. This newly built control strategy is then applied to the power-level regulation of the HTR-PM plant, and numerical simulation results show both the feasibility and high performance of this newly-built control strategy. Furthermore, the relationship between the values of the parameters and the performance of this controller is not only illustrated numerically but also analyzed theoretically.

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