The development of wireless technology like Internet Protocol version 6 over Low power Wireless Personal Area Networks, which defines IP communication for resource-constrained networks enables communication on the lower layers, while the diverging and incompatible application layer protocols lead to barriers in the way of information transferring between heterogeneous networks. Fortunately, extensible messaging and presence protocol (XMPP) is a preferential protocol to solve the problem of interoperability between heterogeneous networks. Hence, it is attractive to extend XMPP to the Internet of Things (IoT). However, XMPP protocol is initially designed for the Internet where the equipment is rich in resources, considering the characteristics of the IoT, the XMPP protocol needs to be optimized to meet the requirements of IoT, e.g. , downsized protocol, publish/subscribe service and sleeping mechanism. In this paper, by staying true to the IoT visions, we propose a lightweight XMPP publish/subscribe scheme for resource-constrained IoT devices to perform data exchange either periodically or upon any value change. According to the subscriber’s needs, the publisher can adjust the data information published to the server. Inherit the merits of XEP-0060, the server maintains and manages the publish/subscribe relationships with multiple subscribers, as well as distributes the received data sent by publisher to all subscribers, yielding less complexity of publication and energy efficiency. In addition, the proposed scheme strongly supports publish/subscribe architecture of the sleeping clients that actually prolongs the lifetime of battery-powered devices. Thus, based on the standardized XMPP protocol, we present a down-sized and trimmed XMPP to implement this scheme. Through the experimental results, we demonstrate our work on optimizing and improving XMPP publish/subscribe scheme for resource-constrained IoT devices and show the simplicity and efficiency of this scheme.

Although many vector-borne agents are potential zoonoses and cause substantial morbidity and mortality in dogs worldwide, there are limited data on these organisms in dogs of China. Quantitative PCRs for vector-borne agents were performed to investigate their prevalences in convenience whole blood samples obtained from 1114 dogs from 21 veterinary clinics and a commercial dog breeding facility in ten provinces of China. In addition, the PCRs were performed on 146 Rhipicephalus sanguineus senso lato and 37 Linognathus setosus collected from dogs in the commercial dog breeding facility. DNAs of Babesia gibsoni and B. vogeli (1.2 %), Ehrlichia canis (1.3 %), Hepatozoon canis (1.8 %) and Theileria orientalis (0.1 %) or a closely related organism were detected in the bloods of the dogs studied, and Babesia vogeli (3.4 %) and Ehrlichia canis (4.1 %) in R. sanguineus senso lato. The qPCRs for Anaplasma spp., Dirofilaria immitis and Leishmania spp. were negative for all blood samples, ticks and lice. At least one vector-borne agent was found in dogs from 5 of the 10 provinces investigated in this study. Overall, 4.4 % (49/1117) of the dogs studied were positive for at least one vector-borne agent with the prevalence being highest in the commercial breeding colony (24/97; 24.7 %). Our study confirms that B. vogeli, B. gibsoni, H. canis, and E. canis occur in China. Also, we present evidence that T. orientalis or a closely related organism can infect dogs.

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.

Real-time data delivery is significant for the Industrial Internet of Things (IIoT). Age of information (AoI), a popular real-time metric, is usually used to measure the data freshness of the IIoT systems. If the data most recently received by the destination at time $t$ was generated at time $t_{1}$ , then the AoI is $t-t_{1}$ . In this article, we consider a multisensor multiserver IIoT system and develop scheduling algorithms to minimize the average AoI. The challenge lies in the strong coupling between link scheduling, server selection, and service preemption. To address this issue, we propose a guided exploration-based deep $Q$ -Network (GE-DQN) algorithm utilizing a fixed advantage policy, which has a faster learning speed compared to classical deep $Q$ -network. Moreover, we use a shared decision module followed by several network branches to transform the structure of GE-DQN and propose a guided exploration-based branching dueling $Q$ -network (GE-BDQN) algorithm. Since the branch structure of GE-BDQN can decompose the high-dimensional action, GE-BDQN can reduce the approximate exponential growth of the number of output neurons with the increase of the number of sensors to linear growth compared to GE-DQN, ensuring the applicability of the algorithm under large-scale systems. From the simulation results, it can be found that the proposed two algorithms can achieve better average AoI compared to the advanced algorithms, and the GE-BDQN algorithm can achieve up to 36% performance gain.

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.