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This work investigates the tracking consensus problem of multiagent systems over directed networks, where the control gains follow certain volatile patterns. Some event-based consensus protocols are formulated so as to reduce the redundant execution of control. By using an extended differential inequality with a time-dependent coefficient, criteria for tracking consensus under time- and state-dependent triggering conditions are constructed, respectively. It is proved that the time average of the control gain, together with the agent dynamics, network topology, and triggering conditions, governs the consensus despite the fluctuation of control gain. The derived theorem can be utilized to ensure consensus with intermittent strategies aiming to lessen the burden in communications, including aperiodic on-off control with periodic perturbation and pulse-modulated on-off control. Unlike existing works, the requirement of a positive lower bound of control ratios is removed and, thus, a wide range of control gain patterns is possible, signifying higher flexibility in intermittent policy design. Finally, numerical examples are provided to further illustrate the theoretical results.

In this paper, the synchronization problem for networked nonlinear agents with time-varying control gain is studied under a synchronous periodic data sampling framework. To achieve synchronization, both the state-dependent and time-dependent event-triggered protocols are proposed. The effectiveness of these protocols is justified by Lyapunov stability theorem based on rigorous mathematical proof, facilitated by a delayed differential inequality with time-dependent parameters. Instead of specifying a lower bound for the control gain, as others usually suggested, our criteria rely on its time-average and thus allow higher flexibility in controller design. Numerical simulations are also presented to confirm the reaching of synchronization and demonstrate the wide applicability of the proposed protocols.

In this paper, the second-order leader-following consensus of coupled nonlinear agents with intermittent control is investigated. A subset of followers is pinned while it is assumed that the underl...

A hierarchical quantum secret sharing scheme is proposed, for which participants are divided into multiple layers. In this scheme, the number of participants and the shared secrets can be different for layers. The shared secret of a layer can only be recovered by the cooperation of all the participants at that layer. Moreover, each participant is able to obtain the shared secrets at lower layers, but not those at higher layers. The design is based on a special high-dimensional entangled state, in which the particles have different dimensions and can be set as subtle values to satisfy the hierarchical requirement. The correctness and security of the proposed scheme are analyzed. As compared to existing quantum secret sharing schemes, it possesses distinct features which are demanded by some specified scenarios.

In recent years, the popularity of electric vehicles (EVs) has been rapidly expanding, thanks to the government’s supportive policies. However, managing EV’s en-route re-charge activities under different operation scenarios is still a critical issue, when the EV’s limited driving range and long re-charge time are concerned. In this paper, an EV flow distribution problem is formulated for the guidance of EV’s re-charge activities. The problem manipulates EV flows directly with the consideration of EV’s queuing and re-charge delay at charging stations, which makes it greatly different from the classic problems. To solve the problem effectively, a dedicated flow distribution algorithm (FDA) is devised. Furthermore, based on the centrality properties in the context of complex network science, the interdependence of EV flow distribution and charging resource allocation is investigated. Simulation results show that a proportional allocation of chargers to nodes with high weighted betweenness leads to the most efficient flow distribution. In addition, robustness is introduced to measure the flow distribution solution’s endurance under EV drivers’ ignorance of guidance. The comparison among centrality-based allocations and an optimization-based allocation reveals that efficiency and robustness are two conflicting properties in flow distribution, dependent on the allocation of charging resources.

This paper investigates the synchronization problem of nonlinear multi-agent systems with time-varying control in the presence of transmission delay over a communication network. To facilitate the study, a novel delayed differential inequality with time-varying coefficients is first established. Then, the synchronization problem is recast into the stability problem of a delayed differential system with certain time-dependent parameter. A sufficient criterion is further formulated to guarantee the synchronization. The mathematical proof reveals that the time average of the control strength is crucial for reaching synchronization. Together with the agent dynamics and the topology, this average also governs the largest admissible delay. Moreover, the criterion is applied to synchronization problems with general on-off coupling under data sampling and delayed communications, respectively. Some useful corollaries are consequently deduced. Finally, numerical simulations are presented to illustrate the validity of our theoretical results.

For the benefit of global environmental preservation, electric vehicles (EVs) have been gradually accepted by people in the past few years. However, the technical problem of limited drivable range and long charging duration is still a major hurdle for the popularization of EVs, especially for commercial usage. In this paper, a dynamic electric vehicle routing problem (D-EVRP) model is designed for planning the itinerary for goods delivery by the utilization of EVs in logistics industry. To reflect the real situation, the D-EVRP considers a time-dependent stochastic traffic condition and captures the discharging/charging pattern of an EV using an analytical battery model. Its aim is to minimize the overall service duration, subject to a variety of the state-of-art constraints common in EV routing problems. Furthermore, to address the D-EVRP, a hybrid rollout algorithm (HRA), which incorporates a dedicated pre-planning strategy and a rollout algorithm, is also proposed. The effectiveness of the HRA and benefits of incorporating the analytical battery model are justified by extensive simulations using the real-world D-EVRP instances.

This brief addresses the consensus problem of a group of agents coupled via nonlinear locally passive functions over a time-varying network. A consensus protocol is designed which is solely dependent on an agent’s own instantaneous state and the states broadcasted from its neighbors. A time-dependent triggering condition is defined to govern the broadcasting of one’s state to all its neighbors. Information exchange only occurs when the triggering condition is met, as a result, communication overhead can be greatly reduced. It is mathematically proved that consensus is reachable and Zeno behavior is excluded if the union of the underlying graphs over any time interval of certain length admits a directed spanning tree. The proposal is applicable for various kinds of networks, such as continuously time-varying network, switching network, blinking network, and its effectiveness is confirmed with numerical examples.

In this brief, a multi-carrier differential chaos shift keying system capable of mitigating channel noise is proposed. In this system, subcarriers are allocated to the reference and data signals in an optimal way, while noise reduction is achieved through reference diversity. To verify its performance, the bit error rate of the proposed system over multipath Rayleigh fading channels is derived, together with a detailed discussion about the determination of the optimal number of reference-carrying subcarriers. Extensive simulations are carried out for performance evaluation, which are further compared to other state-of-the-art systems. Results confirm the superior bit error rate performance of the proposed system, which has only small loss in energy and spectral efficiencies.

In this work, the consensus problem of networked agents under denial-of-service (DoS) attacks is studied. Due to DoS attacks, communication channels would be intermittently congested, which inevitably affects the state update in the consensus process and leads to the failure of a consensus protocol. Such a situation has been recast into a consensus problem with on-off control, as suggested by other studies. However, it is commonly assumed that the underlying graph is undirected and the DoS attack follows certain periodic patterns. Obviously, these assumptions cannot truly reflect some real cases. Therefore, aperiodic attacks and directed topology are considered here. Our theoretical results reveal that consensus is achievable, provided that the average of the DoS attack duration over a certain length of time interval is upper bounded. Compared with other existing results, this new consensus criterion demonstrates better generality and tractability. Finally, simulations are presented to further demonstrate the effectiveness of the theoretical results.

Network optimization problems are usually NP-hard and evolutionary algorithms (EAs) are good at these problems. However, direct implementation of EA, ignoring the network properties or problem features, is common which usually results in a low-efficient algorithm. In this paper, a framework of feature-embedded evolutionary algorithm is outlined and the idea is demonstrated by embedding the nodal centralities in a genetic algorithm (GA) for solving the node selection problem in pinning control. Simulation results confirm that the new design outperforms existing deterministic schemes in terms of solution quality, and significant improvements are also noticed as compared to classical GA. The results also shed light on high efficient feature-embedded EAs in solving other challenging optimization problems.

A quantum key distribution protocol with single-particle and Bell state is proposed, in which one player Alice sends the states from some special single-particles and Bell states, the other player Bob measures these states in the single-particle basis or Bell basis, and then establish their secret key. Through combining the single-particle and Bell state novelly, the error rate of eavesdropping in our protocol can be increased up to $$ \frac{3}{8} $$ . Compared to BB84, our protocol can get higher secure key rate in practice.

This brief investigates the master–slave synchronization problem of delayed neural networks with general time-varying control. Assuming a linear feedback controller with time-varying control gain, the synchronization problem is recast into the stability problem of a delayed system with a time-varying coefficient. The main theorem is established in terms of the time average of the control gain by using the Lyapunov–Razumikhin theorem. Moreover, the proposed framework encompasses some general intermittent control schemes, such as the switched control gain with external disturbance and intermittent control with pulse-modulated gain function, while some useful corollaries are consequently deduced. Interestingly, our theorem also provides a solution for regaining stability under control failure. The validity of the theorem and corollaries is further demonstrated with numerical examples.

Quantum group signature is an important branch of quantum signature. Most of the existing quantum group signature schemes require that all the signatories must be present to generate a valid signature, and this property may limit their application in practice. In this paper, we will propose a quantum (t, n) threshold group signature scheme. In our scheme, n signatories compose a group, and any t out of these n signatories can generate a valid signature on behalf of the group. The t signatories use the quantum-controlled-not operations to expand the quantum message into t-particle entangled states, and then use the entanglement swapping to transmit the quantum message to the receiver. The receiver performs the single-particle measurements and unitary operations to recover the initial quantum message, and then verifies the signature with the help of the arbitrator. Compared to the existing quantum group signature schemes, our (t, n) threshold scheme will be more flexible in practice.

The traditional quantum secret sharing does not succeed in the presence of rational participants. A rational participant’s motivation is to maximize his utility, and will try to get the secret alone. Therefore, in the reconstruction, no rational participant will send his share to others. To tackle with this problem, we propose a rational quantum secret sharing scheme in this paper. We adopt the game theory to analyze the behavior of rational participants and design a protocol to prevent them from deviating from the protocol. As proved, the rational participants can gain their maximal utilities when they perform the protocol faithfully, and the Nash equilibrium of the protocol is achieved. Compared to the traditional quantum secret sharing schemes, our scheme is fairer and more robust in practice.

Information broadcast (IB) is a critical process in complex network, usually accomplished by flooding mechanism. Although flooding is simple and no prior topological information is required, it consumes a lot of transmission overhead. Another extreme is the tree-based broadcast (TB), for which information is disseminated via a spanning tree. It achieves the minimal transmission overhead but the maintenance of spanning tree for every node is an obvious obstacle for implementation. Motivated by the success of scale-free network models for real-world networks, in this paper, we investigate the issues in IB by considering an alternative solution in-between these two extremes. A novel relay-based broadcast (RB) mechanism is proposed by employing a subset of nodes as relays. Information is firstly forwarded to one of these relays and then re-disseminated to others through the spanning tree whose root is the relay. This mechanism provides a trade-off solution between flooding and TB. On one hand, it saves up a lot of transmission overhead as compared to flooding; on the other hand, it costs much less resource for maintenance than TB as only a few spanning trees are needed. Based on two major criteria, namely the transmission overhead and the convergence time, the effectiveness of RB is confirmed. The impacts of relay assignment and network structures on performance are also studied in this work.

Many realistic scenarios have been considered in the studies of naming games, for example, misunderstandings [1], limited memory sizes [2], and group discussions [3, 4]. Recently, a scenario with multiple languages is considered in [5, 6], useful for community detection. In such a scenario, agents speak different languages, and the population would reach a metastable state when different-language agents reach consensus in their own group, when the underlying network is a community-based one [5, 6, 7].