Unmanned aerial vehicles (UAVs) have been widely used to collect data from ground nodes (GNs) in various applications because of their flexibility and mobility. Some emergency situations pose strict requirements for UAV’s mission completion time. The current research focuses on the design and optimization of UAV’s flight trajectory to shorten the mission completion time. But the data collection process also greatly affects the mission completion time, especially when the uplink throughput is large. This article emphasizes the data collection process and proposes a V-shaped collection trajectory for the first time to shorten UAV’s collection time and then jointly optimizes the flight and collection trajectory to minimize the mission completion time. We formulate the mission completion time under energy constraints to an optimization problem and decompose it into three subproblems: 1) mission allocation of UAVs; 2) collection time minimization; and 3) joint optimization of collection and flight trajectory. 1) We establish the mission allocation model by setting the scaling factors for the flight and collection mission, and then solve it by utilizing the min–max multiple traveling salesman problem (MTSP) algorithm; 2) for the data collection process, we propose a V-shaped trajectory to minimize the data collection time and prove its validity; and 3) since the flight and collection trajectory of the adjacent GNs are deeply coupled, we model the joint optimization of the flight and the collection time as a mixed-integer nonlinear programming problem, and solve it by the joint optimization algorithm for flight trajectory and collection trajectory (JOFC). The simulation results show that our proposal outperforms the compared schemes.

Existing packet-based synchronization approaches take extensive energy for industrial wireless sensor networks (IWSNs) due to substantial timing message exchanges. Combined with acknowledgement (ACK), this paper proposes an energy-efficient synchronization protocol without exchanging timestamps. Also, a mapping rule of ACK response time is presented for the joint estimation of skew and fixed delay without requiring a following response in each cycle, so that estimation can be implemented in parallel to data transmission. Then the timestamp-free synchronization technique is extended to the receiver-only synchronization (ROS) scenario to further reduce communication overhead. Assuming Gaussian variable delays, the maximum likelihood estimators and corresponding lower bounds for slave node and silent node are developed, as well as a low-complexity estimator for silent node. In addition, considering the dynamics of clock, a timestamp-free clock skew tracking algorithm using Kalman filtering is developed. Simulation results validate the efficiency of the proposed estimators.

Time synchronization is indispensable for convenient network management, device monitoring, security and other fundamental operations in industrial wireless sensor networks (IWSNs). Over the past few decades, a wide variety of highly accurate clock synchronization protocols have been investigated by employing powerful statistical signal processing techniques. However, most two-way exchange estimation schemes do not readjust the node's local clock upon every resynchronization before the clock parameters are estimated. And it may not be appropriate in IWSNs where time synchronization is consistently required. Based on the two-way message exchange mechanism, this paper investigates the clock synchronization schemes of active node and overhearing node with immediate clock readjustment. The maximum-likelihood estimators (MLEs) of the clock skew and the corresponding Cramer-Rao lower bounds (CRLBs) are derived assuming Gaussian delays. Simulation and experimental results validate the performance of the proposed estimators.

Clock synchronization is crucial for applications in wireless sensor networks, such as event scheduling and data fusion. In practical wireless networks, environmental changes cause the oscillator to be imperfect. Thus, it is necessary to track the nonlinear varying clock dynamically. In this paper, we propose a timestamp-free clock skew (frequency difference) and offset (time difference) joint tracking algorithm based on extended Kalman filter (EKF), which can be embedded into the general network data flow to achieve long-term synchronization without additional communication overhead. To further improve energy efficiency of clock synchronization, this paper develops an EKF clock skew tracking algorithm for silent nodes in receiver-only synchronization. For the situation that silent node overhears synchronization information from multiple active nodes, we present multi-information timestamp-free synchronization and multi-observation clock skew fusion scheme for silent nodes. Simulation results show the effectiveness of the proposed tracking algorithms.

In UAV-enabled wireless power transfer (WPT) systems, the UAV is usually planned to fly and charge the ground nodes (GNs), so as to prolong the lifetime of wireless sensor networks. But in fact, the long charging distance between the UAV and the GNs makes the GNs receive less energy. In order to maximize the received energy of GNs, this paper focuses on the charging process and proposes a V-shaped WPT scheme, where the UAV descends to the optimal hover position and charges the GNs, so as to transfer more energy to the GNs. Moreover, considering that the GNs far from the hover position receive little energy in the V-shaped WPT scheme, we further develop an Inverted Trapezoidal WPT scheme to improve the fairness of the energy received by the GNs, in which the UAV continuously charges the GNs whether it is hovering or flying horizontally after lowering its altitude. Because the UAV’s flight and maneuvering are strictly constrained by its loading energy, we establish the UAV’s propulsion power consumption model in different flight attitudes and formulate the optimization problems of the GNs’ received energy in two schemes, and then develop two algorithms to solve them. The simulation results show that the performance metrics of UAV’s energy consumption, the efficiency and fairness of GNs’ received energy are better than the compared schemes.

Clock synchronization is a significant basis for many operations in wireless sensor networks. The distributed consensus-based clock synchronization has gained popularity for its robustness and scalability. However, most consensus-based clock synchronization protocols either ignore communication delay, or consider bounded delay without distribution model. In this paper, based on the consensus theory, the clock synchronization problem with truncated exponential delay is investigated. We use the maximum likelihood method to estimate relative drift between nodes. A recursive method is presented to cope with the maximum likelihood estimation, which largely reduces the computational complexity and the storage overhead. Then, the estimated relative drift is adopted in the two main parts of consensus clock synchronization: drift compensation and offset compensation. We give the rigorous theoretical proof of the convergence of the network-wide synchronization. Simulations further verify the theoretical analysis and show that the synchronization performance of the proposed algorithm is better than existing similar schemes under truncated exponential delays.