The autonomous scheduling at unsignalized intersections faces a great challenge for ensuring collision-free passing and improving traffic efficiency under the complex intersection environment and heavy traffic density. In this article, we first design an autonomous management model for unsignalized intersections which uses the intersection control center to manage the passage of vehicles instead of traffic light. To avoid vehicles collision, the intersection is divided into multiple collision subzones, and each collision subzone needs to satisfy that the occupancy time of different vehicles is not overlapped. Second, a conflict graph tree search (CGTS) algorithm is developed to attain the optimal passing priority, which has the highest traffic efficiency. The CGTS algorithm reduces the computational complexity by compressing the solution space and reducing repeated calculations. Then, a heuristic threshold-based motion control strategy is proposed, which supports vehicles to reach the intersection at the assigned time by controlling their acceleration. Finally, we perform simulation experiments to show that the effectiveness of our algorithm outperforms comparison algorithms at various traffic densities.

Wireless audio transmission has always been the focus of Bluetooth application scenarios. Future audio use cases, such as multistreaming to assist stereo imaging experiences, broadcast audio sharing, hearing aid support, etc., have higher requirements for Quality of Service (QoS). Bluetooth low-energy (BLE) Audio is considered to be a replacement for the Bluetooth classic audio standard in the next generation of audio applications. In low-energy (LE) Audio, the audio data is carried by connected isochronous streams (CISs), which is a logical transport that enables the transmission of isochronous data. However, until now, the performance of CIS-based LE Audio has not been fully analyzed. In this article, we propose a mathematical model to evaluate the performance of CIS, such as packet loss rate (PLR), throughput, backlog, delay, and average power consumption. In addition, the feasibility of multihop transmission based on CIS is explored, and the model is extended to analyze the end-to-end PLR and throughput. Finally, the accuracy of the proposed model is verified by simulation results, and the relationship between CIS parameters and performance is analyzed, providing guidance for parameter selection in LE Audio applications.

Device discovery or neighbor discovery, which enables devices to detect other devices in the vicinity, plays an important role in many IoT applications as it is a prerequisite for wireless communication and interaction with each other. In this article, we study collaborative neighbor discovery, where multiple sensors connected to a gateway collaborate to discover another mobile device. Such a scenario can be found in many applications, such as automotive keyless access system, smart home monitoring, asset tracking, and safety monitoring. We first build an analytical model called Co-Circle for collaborative neighbor discovery. Based on Co-Circle, we derive the lower bound of the expected discovery latency. Then, we show how the lower bound of the expected discovery latency varies with the energy budget (or duty cycle). Finally, we propose an optimal collaboration scheme that can achieve the lower bound of the expected discovery latency. Experimental results verify the performance of the proposed collaboration scheme.

Bluetooth Low Energy (BLE) has become one of the enabling wireless technologies to facilitate the Internet of Things. Neighbor discovery is critical in BLE communications. BLE uses multiple (three) channels in neighbor discovery. It is challenging to achieve low-latency and low-energy-consumption BLE neighbor discovery due to the lack of analytical models for multichannel neighbor discovery. In this paper, we study BLE multichannel neighbor discovery for two advertising modes specified by BLE: periodic deterministic advertising (PDA) and pseudo-random delay advertising (RDA). We build two generic models, BLE 3-Circle model and BLE 1-Circle model, for characterizing BLE multichannel neighbor discovery. For PDA mode, we present a necessary and sufficient condition for BLE multichannel neighbor discovery, and provide a guideline for parameter setting. With the guideline, we derive the expected discovery latency in closed form, and demonstrate that the expected discovery latency is very close to a theoretical lower bound. For RDA mode, we build an analytical model based on Markov chain to accurately compute the expected discovery latency. Simulation and experimental results show accuracy of our analytical works. Interestingly, our parameter setting guideline works well for both PDA and RDA modes.

In the edge computing Internet of Things network, we minimize the offloading overhead (caused by the bandwidth cost for data transmission and computation resource consumption for task remote processing) while providing the end-to-end (E2E) delay provisioning. Under the scenario, a tandem queue consisting of a transmission queue and a computing process queue is formed by the tasks offloaded to the edge server via wireless link and then processed through the computing resource. Due to the tandem queue, the offloading decision and computing resource allocation are coupled over the tandem queue. To make the problem tractable, we decouple the above two operations and propose a two-stage offloading filtering and computing resource allocation policy. After decouple, we then investigate the delay bound violation probability of the tandem queue by leveraging large deviation analysis. Further, we reveal that under the same E2E delay provisioning, the offloading overhead under the proposed decoupled policy can approach to the non-decoupled optimum by selecting an appropriate value of control parameter. Simulation results verify the theoretical analysis and show the efficiency of the proposed policy.

Internet of Things (IoT) networks are usually distributed in nature. Due to the possible mobility of IoT devices, it is common and critical for each IoT device to keep discovering who is in its neighborhood, referred to as neighbor discovery. Due to the limited battery capacity of IoT devices, it is challenging to design a neighbor discovery protocol (NDP) that can achieve both low duty cycle and low discovery latency. In this article, we build a model called Circle to characterize the process of neighbor discovery in IoT networks. Then, we give a necessary and sufficient condition for neighbor discovery and theoretically prove its correctness. This is the first time in the research community that a necessary and sufficient condition is given for neighbor discovery. According to the necessary and sufficient condition, we analytically derive a lower bound of the worst case discovery latency and demonstrate when the lower bound can be achieved. The analytical model is generic as it can be used to analyze existing NDPs. Based on the Circle model and the analysis, we propose an NDP, which is also called Circle. We compare Circle with the state-of-the-art NDPs in a real testbed, and experimental results show that Circle is superior to the existing state-of-the-art NDPs.

ABSTRACT For a wireless ad hoc network to achieve fault‐tolerance, it is desired that the network is bi‐connected. This means that each pair of nodes in the network have at least two node‐disjoint paths between them, and thus, failure at any single node does not partition the network. In other words, in a bi‐connected network, there is nocut‐node(defined as a node such that the removal of it partitions the network). To make a connected but not bi‐connected network become bi‐connected, actions should be taken such that all cut‐nodes become non‐cut‐nodes. In this research, we propose to deal with cut‐nodes from a new perspective. Specifically, we first introduce a new concept ofremovable node, defined as a non‐cut‐node such that the removal of it does not generate any new cut‐node in the network. Then, we propose to move a removable node to a new location around a cut‐node. In this way, the cut‐node becomes a non‐cut‐node, that is, the failure of it does not partition the network anymore. Algorithms are provided (i) to identify removable nodes; (ii) to match cut‐nodes with a feasible set of removable nodes, in which all nodes can be simultaneously removed from the network without generating any new cut‐node in the network; and (iii) to derive the final location of a removable node such that its movement distance is the shortest and the associated cut‐node becomes a non‐cut‐node. The proposed algorithms do not guarantee the final bi‐connectivity but have the merits of a large success rate (almost 100% in the simulation), a small number of moved nodes, and a short total movement distance. In addition, the proposed algorithms are shown to be effective even when there are a large portion of fixed nodes in the network. Copyright © 2011 John Wiley & Sons, Ltd.

The topology of a wireless sensor network has a significant effect on the network performance. Although topology control algorithms can optimize the network topology, the resultant topology is usually changeable. In this paper, we focus on how to maintain the network connectivity while reducing the maintenance overhead as some nodes fail. A distributed topology maintenance algorithm based on the shortest path tree is proposed. In this algorithm, nodes in immediate surroundings of a faulty node are first triggered to respond, and if they couldn’t ensure that the network is connected, the other related nodes are further triggered. Simulation results show that the proposed scheme can efficiently maintain the network connectivity with significant reduction in the overhead for topology maintenance.