It is a critical issue for achieving dynamic average consensus (DAC) in the presence of privacy eavesdroppers and false data injection (FDI) attacks, and this scenario is applicable to intelligent transportation systems. A dynamic event-triggered privacy preserving DAC (DET-PPDAC) control scheme is proposed. Firstly, in a privacy-sensitive scene, different time-varying terms are added to communication states by hiding real information from eavesdroppers. An observer and a compensator are designed to construct a control scheme for compensating for the impact of FDI attacks over a channel between a control signal and an actuator. Adaptive auxiliary variables are introduced for compensating for residual errors owing to asymmetric encryption/decryption functions. Dynamic event-triggered conditions are constructed to reduce the number of data as well as the risk of leakage by eavesdroppers, and continuous monitor from neighbors is removed. Our DET-PPDAC control scheme can also be applied to a directed graph. Stability analysis shows that the control scheme finally achieves DAC with bounded errors and Zeno-free behaviors while satisfying the requirement of privacy preservation. Simulation examples with formation of vehicles are given to demonstrate the effectiveness of the proposed control scheme.

In this paper, a home Internet-of-Things system is analyzed by dividing it into four layers, i.e., the node layer, gateway layer, service layer, and open layer. The gateway layer, which supports a variety of wireless technologies and is the core of home wireless networks access unit, together with the node layer constitutes the home wireless network. A gateway prototype following the proposed architecture has been implemented. A testbed of an interference-aware wireless network which includes the gateway prototype has also been created for testing its user interaction performances. The experimental results show that both Wi-Fi and Bluetooth have an impact on the ZigBee communication. Considering the complex scene of home and building, ZigBee multihop communications are set to reduce the packet loss probability. In addition, an event-level-based transmission control strategy is proposed, in which the packet loss probability of wireless network is reduced by controlling the transmission priority of different levels of monitoring events, and optimizing the ZigBee wireless network channel occupancy.

Many environmental monitoring applications that are based on the Internet of Things (IoT) require robust and available systems. These systems must be able to tolerate the hardware or software failure of nodes and communication failure between nodes. However, node failure is inevitable due to environmental and human factors, and battery depletion in particular is a major contributor to node failure. The existing failure detection algorithms seldom consider the problem of node battery consumption. In order to rectify this, we propose a low-power failure detector (LP-FD) that can provide an acceptable failure detection service and can save on the battery consumption of nodes. From simulation experiments, results show that the LP-FD can provide better detection speed, accuracy, overhead and battery consumption than other failure detection algorithms.