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Over recent years, traditional manufacturing factories have been accelerating their transformation and upgrade toward smart factories, which are an important concept within Industry 4.0. As a key communication technology in the industrial internet architecture, time-sensitive networks (TSNs) can break through communication barriers between subsystems within smart factories and form a common network for various network flows. Traditional routing algorithms are not applicable for this novel type of network, as they cause unnecessary congestion and latency. Therefore, this study examined the classification of TSN flows in smart factories, converted the routing problem into two graphical problems, and proposed two heuristic optimization algorithms, namely GATTRP and AACO, to find the optimal solution. The experiments showed that the algorithms proposed in this paper could provide a more reasonable routing arrangement for various TSN flows with different time sensitivities. The algorithms could effectively reduce the overall delay by up to 74% and 41%, respectively, with promising operating performances. [ABSTRACT FROM AUTHOR]

The Internet of Underwater Things (IoUT) gradually becomes the future direction of ocean. Many devices, which are called the sources, are deployed in the sea to fulfill scientific, civilian, and military needs. If the locations of these sources are leaked, it will cause a serious economic and military crisis. Thus, in this context, the source location privacy protection becomes critical. In this paper, we focus on the source location privacy protection of underwater acoustic sensor networks (UASNs), where a multi-channel interference based source location privacy protection scheme (MCISLP) is proposed. The MCISLP mainly contains four steps. First, to enhance the sense of autonomous underwater vehicles (AUV) for nodes, a noise reduction method is proposed. Then, based on the previous step, an AUV movement prediction method for nodes is presented to ensure the success of packet transmission. After that, for the information exchange among nodes, given the interference of multiple underwater channels, this interference is then utilized to protect the source location privacy. Further, to reduce the channel interference on the source packet, the time slot control is added to weaken the influence. Last, the ant colony algorithm is adopted for the data collection of AUV. The simulation results show that the MCISLP can increase the network safety time by up to 57 $\%$ (compared with data collection algorithms), and balance the energy consumption of nodes (for about 20 $\%$ energy saving), with a minor compromise of energy consumption of AUV and delay. [ABSTRACT FROM AUTHOR]

In this paper, we take an in-depth study on the data collection scheduling issue in underwater acoustic sensor networks (UASNs). To address this issue, we propose the use of software-defined networking (SDN) technique, based on which the paradigm of software-defined underwater acoustic sensor networks (SD-UASNs) is proposed. With SD-UASNs, we propose an efficient data collection scheme on account of node clustering. We take the data scale into account, propose a fast node clustering approach based on an improved Birch algorithm including node pre-clustering and node re-clustering. In particular, for the node pre-clustering procedure, we improve the cluster feature tree of the Birch algorithm and limit the nodes in each cluster to be within an optimal distance. Based on the proposed pre-clustering approach, we propose a greedy data collection scheme that can heuristically seek optimal solutions when the compressed sampling is taken into account. Evaluation results demonstrate that our scheme performs better in network efficiency than some popular schemes. [ABSTRACT FROM AUTHOR]

In recent years, underwater acoustic sensor networks (UASNs) have been widely investigated for ocean environmental monitoring, offshore exploration, and marine military. The core function of UASNs is to collect data for related operations. A number of factors make the monitoring challenging; ocean thermoclines may affect the communication of the underwater nodes and gliders, reducing their communication range at varying depth; moreover, the node movement caused by Ekman drifting effect can significantly interfere with the data transmissions. Thus, these factors are regarded essential towards characterizing the ocean environment. To address these challenges, a sleep-scheduling-based hierarchical data collection algorithm (SSHDCA) for underwater gliders is designed. The UASN is split into multiple virtual cubes, where the nodes in different virtual cubes sleep and work alternately to save energy. Then, the SSHDCA divides the network into a dynamic layer and a static layer. In the dynamic layer, a virtual-cube-based multi-hop method is leveraged to transmit data packets to the central area. In the static layer, an improved density-based clustering technique is applied to assign each node to an appropriate cluster, while the underwater gliders collect data from the cluster heads. Further, to reduce energy consumption, the SSHDCA compresses key and non-key data, reducing the size of the packets. Simulation results have shown that the proposed algorithm is effective in reducing the path length of the gliders and the average energy consumption of the nodes, while increasing the remaining operational life of the whole network. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, enormous amounts of vehicular services have been emerging and challenge both the architectures and protocols of the Internet of Vehicles. The high-speed mobility features of nodes in the vehicular networks changes the network topology frequently, resulting in low routing efficiency, and higher packet loss. In this article, we utilize software-defined networking (SDN) technology to decouple the network control plane from the data forwarding plane, and divide the vehicular networks into three functional layers: data, control, application layers. Based on the proposed network architecture, we propose an adaptive traffic engineering (TE) mechanism to guarantee the V2V continuous traffic in vehicular networks with high-speed mobile vehicles or dynamic network topology. In particular, the proposed TE is based on a proposed active network measurement mechanism under the assistance of the centralized management ability of the SDN technique. The proposed active network measurement approach is a greedy approach where the next hop determination for the measurement packet takes multiple link reliability factors (e.g., the delay, the length, the packet error rate, the neighbors, etc.) into account. Then, we utilize the artificial bee colony (ABC) algorithm to optimize the TE mechanism that can be deployed and executed in the SDN controller. By the proposed TE mechanism, multiple candidate end-to-end paths can be concurrently measured, and the optimal data forwarding path can be adaptively switched. Simulation results demonstrate that our approach performs better than some recent research outcomes, especially in the aspect of performing reliable data forwarding (almost 5% better than the compared objects). [ABSTRACT FROM AUTHOR]

SDVN is a promising architecture to extend the computation resources which break through the limitations of current vehicular networks. It is possible to learn new networking schemes by observing the surrounding environment in SDVN. However, within SDVN, the construction and application of such schemes still lack proper consideration in data collection, prediction, verification, and validation before applying these schemes in the real network, which is due to the limited knowledge of the physical environment. Intelligent Digital Twin (IDT) was initially designed for realizing intelligent manufacturing by virtualizing and learning the data of the physical space in cyberspace. Hence, bringing IDT to networking can provide additional valuable functionalities to meet the above considerations by constructing a virtual intelligent network space, aiming to realize the iterative update of the networking schemes in an adaptive way. In this article, we introduce a new network architecture, IDT-SDVN, by maximizing the advantages of SDVNs. We present the challenges and open issues of IDT-SDVNs. A case study is presented to demonstrate the effectiveness of SDVNs. The experimental results show that significant improvement of performance is achieved for vehicular networking with the proposed IDT-SDVNs. [ABSTRACT FROM AUTHOR]

With the emergence of new underwater ICTs, UWNs based on AUV have become the mainstream technology for underwater search tasks. These advanced underwater searching technologies are leading to smart perceptual ocean technologies. However, to support precise multi-AUVs cooperative underwater search and provide intelligent data collection and data transfer among the AUVs, one of the challenging issues is to design a scalable network architecture capable of fine-grained control and smart underwater data routing. In this article, we employ the paradigm of SDN technology and propose an SDN-based underwater cooperative searching framework for AUV-based UWNs. In particular, we propose a software-defined beaconing framework integrating two categories of defined beacons to synchronize network information and execute network operations. Based on the software-defined beaconing framework, we introduce the USBL positioning system and propose a hierarchical localization framework to localize/track each AUV in the network. Then, we utilize the potential field theory to model the multi-AUV cooperative operation, leading to a cooperative control framework. Finally, to guarantee the potential data transfer among the AUVs, we also propose a software-defined hybrid data transfer scheduling framework. Simulation results demonstrate that our proposed scheme performs more efficiently than some existing schemes especially the distributed control policy. [ABSTRACT FROM AUTHOR]

In underwater acoustic sensor networks (UASNs), the sensors are deployed at different areas of the ocean, which perform information collection and delay-sensitive routing to the data center for further processing or industrial computing. However, in UASNs, the network states have spatiotemporal characteristics due to tides or autonomous underwater vehicles. To steadily route the traffic especially when the spatiotemporal characteristics of the UASNs are considered, a network architecture with intelligent traffic engineering or routing policies is indispensable. In this paper, we employ software-defined networking (SDN) technology and propose an SDN-enabled distributed architecture for UASNs. Based on the proposed architecture, we propose a scheme DSR-SDN for delay-sensitive spatiotemporal routing in SDN-enabled UASNs. The DSR-SDN includes three phases: First, topology awareness; second, spatiotemporal characteristics estimation; and third, routing computation. Particularly, with SDN features, DSR-SDN provides topology awareness based on a proposed software-defined beaconing scheme. Based on the detected topology, the spatiotemporal characteristics of the network states are estimated based on a proposed SDN-based hierarchical node localizing approach SDN-HL. Lead by the SDN controllers, SDN-HL makes use of the proposed “minimum weighted gap” formulation and Adam algorithm to optimize the localization and builds the indirect links to increase the localization rate. To route the traffic through the network with spatiotemporal characteristics, we adopt the time-expanded network approach, based on which a spatiotemporal route decision can be made before the routing starts. The simulation results demonstrate that the proposed scheme, i.e., DSR-SDN, can conduct accurate spatiotemporal characteristic estimation for the network states and provide delay-sensitive spatiotemporal routing for the sensed data. [ABSTRACT FROM AUTHOR]

To provide satisfactory Quality of Service (QoS) on the move, efficient mobility management is indispensable to provide mobile users with seamless and ubiquitous wireless connectivity. However, both the conventional centralized mobility architecture and the upcoming distributed mobility management face fundamental challenges such as sub-optimal routing, scalability, and so on. The emerging software-defined networking (SDN) architecture can efficiently manage network operations, and accordingly provides a new direction to address the challenges in mobility management. In this paper, we propose an SDN-based Mobility Management (SDN-MM) scheme to support seamless Intro/Inter domain handover with route optimization. SDN-MM decouples mobility management and packet forwarding functions by installing route optimizing and mobility control logics in an SDN controller, but exempting it from traffic redirecting. In SDN-MM, a comprehensive set of signaling operations are designed in order to provide transparent and efficient mobility support for ongoing sessions in each handover scenario, which prevents packet loss and tunneling overhead, and accordingly provide improved QoS to mobile users. For data communications, an SDN controller in SDN-MM pre-calculates the optimal end-to-end route before a handover, and decides whether to migrate traffic to the route by balancing the performance gain and the signaling overhead, which greatly improves bandwidth resource utilization. Finally, we develop a novel analytical model to evaluate the performance of SDN-MM, including signaling overhead, handover latency, and packet delivery cost. The simulation results have been provided to demonstrate that the proposed SDN-MM can greatly improve handover performance and maintain high resource utilization efficiency as well. [ABSTRACT FROM AUTHOR]

In this paper, an autonomous underwater vehicle (AUV) location prediction (ALP)-based data collection scheme (ALP) has been proposed to overcome high and unbalanced energy consumption for underwater wireless sensor networks. In our scheme, an AUV travels around the network, follows a predefined trajectory, and collects data from the sensor nodes. The nodes near the trajectory send their data to the AUV directly, while the others send data to their neighbors that are closer to the trajectory. To overcome the “hot region” problem, which means the nodes near the trajectory of the AUV consume energy faster and die early, a trajectory adjustment mechanism is applied. A mathematical model is proposed to adjust the trajectory periodically. To guarantee an efficient communication between the nodes and the AUV, a reliable time mechanism is proposed. In this mechanism, only the nodes with a sufficient amount of time are capable to communicate and send their data to the AUV directly. The analyses and simulation results validate that our proposed ALP prolongs the network lifetime and has a higher packet delivery ratio than the existing protocols. [ABSTRACT FROM AUTHOR]

With the recent developments of wireless sensor networks (WSNs), computing and communication have experienced huge advancement. Meanwhile, security has not received the same attention to go along with such developments. In this paper, we focus on the source location privacy problem in WSNs, a hot research topic in security, and propose a probabilistic source location privacy (PSLP) protection scheme for WSNs. A more powerful adversary, which can use hidden Markov model to estimate the state of the source, is considered in this study. To cope with this type of adversary, phantom nodes and fake sources, which are responsible to mimic the behavior of the source, are utilized to diversify the routing path. Then, the weight of each node is calculated as a criterion to select the next-hop candidate. In addition, two transmission modes are designed to transmit real packets. The simulation results demonstrate that the proposed PSLP scheme improves the safety time without compromising the energy consumption. [ABSTRACT FROM AUTHOR]

While enjoying the convenience brought by the Internet of Things (IoT), people also encounter many problems with wireless sensor networks (WSNs), the foundation of IoT. Security problems are especially of concern. In this article, we focus on location privacy, which is a major security issue in WSNs, and propose a k-means cluster-based location privacy (KCLP) protection scheme for IoT. To protect the source location, fake source nodes are used to simulate the function of the real sources. Then, to protect the sink location privacy, fake sink nodes and a specific transmission pattern are utilized. In order to improve safety time, a k-means cluster is applied to create clusters and fake packets that must pass through the area. Compared to contrasting algorithms, the KCLP scheme can increase the safety time and reduce delay at minor expense in energy consumption. [ABSTRACT FROM AUTHOR]

With the boost of IoT, WSNs have been a well-liked know-how. However, due to WSNs' open and unmonitored nature, security vulnerabilities pose a significant problem. In this article, aiming at SLP, a major security problem, we propose the CASLP protection scheme in WSNs for IoT. To increase the scope of the transmitting path, the source starts the random walk in a given direction. Then, to maintain CASLP convergence, nodes only select their next relay nodes in a specific range. Last, to further improve SLP, we concatenate arcs from several rings around the sink to form a new closed loop. Compared to a ringbased routing scheme, CASLP can reduce delays and energy consumption at the minor expense of safety time in WSNs. [ABSTRACT FROM AUTHOR]

The emerging real-time and computation-intensive services driven by the Internet of Things, augmented reality, automatic driving, and so on, have tight quality of service and quality of experience requirements, which can hardly be supported by conventional cloud computing. Fog computing, which migrates the features of cloud computing to the network edge, guarantees low latency for location-aware services. However, due to the locality feature of fog computing, maintaining service continuity when mobile users travel across different access networks has become a challenging issue. In this article, we propose a novel software-defined-networking-based fog computing architecture by decoupling mobility control and data forwarding. Under the proposed architecture, we design efficient signaling operations to provide seamless and transparent mobility support to mobile users, and present an efficient route optimization algorithm by considering the performance gain in data communications and system overhead in mobile fog computing. Numerical results from extensive simulations have demonstrated that the proposed scheme can not only guarantee service continuity, but also greatly improve handover performance and achieve high data communication efficiency in mobile fog computing. [ABSTRACT FROM PUBLISHER]

Industrial wireless sensor networks (IWSNs) are an expansion of the Internet of Things paradigm that fully exploits the collective intelligence of smart nodes in industrial processes. The data acquisition of IWSNs in harsh industrial environments is susceptible to transmission failures and time delay while being strict in the performance of reliability and timeliness. This article proposes an SNR-assured anti-jamming clustering routing (SA-AJCR) protocol to address the problem of data transmission in an environment of high ambient noise and complex electromagnetic interference. To ease the influence of the industrial field on wireless communication, the irregular radio range of each node is modeled through field testing, and then its communication range is artificially constrained to ensure that each signal is received under a satisfying SNR. Through mapping out an approximation of jammed areas at the cluster level, SA-AJCR enables IWSNs to be tolerant of node or link failure caused by jamming. Routing paths can be adjusted to greedily bypass the mapped jammed regions in the network without interrupting the data transmission or overriding the CSMA limitation. The simulation results demonstrate that the proposed protocol is effectively able to provide high packet delivery ratio in hostile electromagnetic environments with the existence of jammers. [ABSTRACT FROM AUTHOR]

Nowadays, mini-drones, officially called unmanned aerial vehicles, are widely used in many military and civilian fields. Compared to traditional ad hoc networks, the mobile ad hoc networks established by UAVs are more efficient in completing complex tasks in harsh environments. However, due to the unique characteristics of UAVs (e.g., high mobility and sparse deployment), existing protocols or algorithms cannot be directly used for UAVs. In this article, we focus on the routes designed for UAVs, and aim to present a somewhat complete survey of the routing protocols. Moreover, the performance of existing routing protocols is compared in detail, which naturally leads to a great number of open research problems that are outlined afterward. [ABSTRACT FROM PUBLISHER]