This paper proposes multi-input physical layer network coding (multi-input PLNC) for high speed wireless communication in two-dimensional wireless multihop networks. In the proposed PLNC, all the terminals send their packets simultaneously for the neighboring relays to maximize the network throughput in the first slot, and all the relays also do the same to the neighboring terminals in the second slot. Those simultaneous signal transmissions cause multiple signals to be received at the relays and the terminals. Signal reception in the multi-input PLNC uses multichannel filtering to mitigate the difficulties caused by the multiple signal reception, which enables the two-input PLNC to be applied. In addition, a non-linear precoding is proposed to reduce the computational complexity of the signal detection at the relays and the terminals. The proposed multi-input PLNC makes all the terminals exchange their packets with the neighboring terminals in only two time slots. The performance of the proposed multi-input PLNC is confirmed by computer simulation. The proposed multi-input physical layer network coding achieves much higher network throughput than conventional techniques in a two-dimensional multihop wireless network with 7 terminals. The proposed multi-input physical layer network coding attains superior transmission performance in wireless hexagonal multihop networks, as long as more than 6 antennas are placed on the terminals and the relays.

Currently, NDN-based VANETs protocols have several problems with packet overhead of rebroadcasting, control packet, and the accuracy of next-hop selection due to the dynamic topology. To deal with these problems in this paper, we propose a robust and lightweight forwarding protocol in Vehicular ad-hoc Named Data Networking. The concept of our forwarding protocol is adopting a packet-free approach. A vehicle collects its neighbor's visual identification by a pair of cameras (front and rear) to assign a unique visual ID for each node. Based on these IDs, we construct a hop-by-hop FIB-based forwarding strategy effectively. Furthermore, the Face duplication [1] in the wireless environment causes an all-broadcast problem. We add the visual information to Face to distinguish the incoming and outgoing Face to prevent broadcast-storm and make FIB and PIT work more accurate and efficiently. The performance evaluation results focusing on the communication overhead show that our proposal has better results in overall network traffic costs and Interest satisfaction ratio than previous works.

Sememes are the smallest semantic units of human languages, the composition of which can represent the meaning of words. Sememes have been successfully applied to many downstream applications in natural language processing (NLP) field. Annotation of a word's sememes depends on language experts, which is both time-consuming and labor-consuming, limiting the large-scale application of sememe. Researchers have proposed some sememe prediction methods to automatically predict sememes for words. However, existing sememe prediction methods focus on information of the word itself, ignoring the expert-annotated knowledge bases which indicate the relations between words and should value in sememe predication. Therefore, we aim at incorporating the expert-annotated knowledge bases into sememe prediction process. To achieve that, we propose a CilinE-guided sememe prediction model which employs an existing word knowledge base CilinE to remodel the sememe prediction from relational perspective. Experiments on HowNet, a widely used Chinese sememe knowledge base, have shown that CilinE has an obvious positive effect on sememe prediction. Furthermore, our proposed method can be integrated into existing methods and significantly improves the prediction performance. We will release the data and code to the public.

When a disaster hits a network, network service disruptions can occur even if the network facilities have survived and battery and power generators are provided. This is because in the event of a disaster, the power supply will not be restarted within the lifetime of the battery or oil transportation will not be restarted before running out of oil and power will be running out. Therefore, taking a power grid into account is important. This paper proposes a polynomial-time algorithm to identify the critical location C*D of a communications network Nc when a disaster hits. Electrical power grid Np supplies power to the nodes of Nc, and a link in Nc is disconnected when a node or a link in Nc or Np fails. Here, the disaster area is modeled as co-centric disks and the failure probability is higher in the inner disk than the outer one. The location of the center of the disaster with the greatest expected number of disconnected links in Nc is taken as the critical location C*D.

In this paper, we propose a novel radial line planar phased array in which helical antenna elements are individually rotated by their respective connected micromotors to realize dynamic beam-scanning. To our knowledge, this is the first radial line planar array (RLPA) that has antenna elements electromechanically rotated by their individual micromotors. To facilitate its fabrication, helix and its probe are directly metallized on a plastic shaft using molded interconnect device technology, and a motor shaft is press-fitted into the plastic shaft. We also present a new design methodology for RLPA, which combines the equivalent circuit theory and electromagnetic simulations of the unit cell element. The proposed procedure is practical to design an RLPA of antenna elements with arbitrary probe shape without large-scale full-wave analysis of the whole structure of the RLPA. We design, fabricate, and evaluate a 7-circle array with 168 helical antenna elements fabricated using molded interconnect device technology. The prototype antenna exhibits dynamic and accurate beam-scanning performance. Furthermore, the prototype antenna exhibits a low reflection coefficient (less than -17dB) and high antenna efficiency (above 77%), which validates the proposed design methodology.

Defect prediction approaches have been greatly contributing to software quality assurance activities such as code review or unit testing. Just-in-time defect prediction approaches are developed to predict whether a commit is a defect-inducing commit or not. Prior research has shown that commit-level prediction is not enough in terms of effort, and a defective commit may contain both defective and non-defective files. As the defect prediction community is promoting fine-grained granularity prediction approaches, we propose our novel class-level prediction, which is finer-grained than the file-level prediction, based on the files of the commits in this research. We designed our model for Python projects and tested it with ten open-source Python projects. We performed our experiment with two settings: setting with product metrics only and setting with product metrics plus commit information. Our investigation was conducted with three different classifiers and two validation strategies. We found that our model developed by random forest classifier performs the best, and commit information contributes significantly to the product metrics in 10-fold cross-validation. We also created a commit-based file-level prediction for the Python files which do not have the classes. The file-level model also showed a similar condition as the class-level model. However, the results showed a massive deviation in time-series validation for both levels and the challenge of predicting Python classes and files in a realistic scenario.

To improve the performance of underwater acoustic communications, this letter proposes a polar coding scheme with adaptive channel equalization, which can reduce the amount of feedback information. Furthermore, a hybrid automatic repeat request (HARQ) mechanism is provided to mitigate the impact of estimation errors. Simulation results show that the proposed scheme outperforms the turbo equalization in bit error rate. Computational complexity analysis is also provided for comparison.

This paper proposes a design of high-speed interconnection between optical modules and electrical modules via bonding-wires and coplanar waveguide transmission lines on printed circuit boards for 400 Gbps 4-channel optical communication systems. In order to broaden the interconnection bandwidth, interdigitated capacitors were integrated with GSG pads on chip for the first time. Simulation results indicate the reflection coefficient is below -10 dB from DC to 53 GHz and the insertion loss is below 1 dB from DC to 45 GHz. Both indicators show that the proposed interconnection structure can effectively satisfy the communication bandwidth requirements of 100-Gbps or even higher data-rate PAM4 signals.

This letter proposes a novel intelligent dynamic channel assignment (DCA) scheme with small-cells to improve the system performance for uplink machine-type communications (MTC) based on OFDMA-FDD. Outdoor MTC devices (OMDs) have serious interference from indoor MTC devices (IMDs) served by small-cell access points (SAPs) with frequency reuse. Thus, in the proposed DCA scheme, the macro base station (MBS) first measures the received signal strength from both OMDs and IMDs after setting the transmission power. Then, the MBS dynamically assigns subchannels to each SAP with consideration of strong interference from IMDs to the MBS. Through simulation results, it is shown that the proposed DCA scheme outperforms other schemes in terms of the capacity of OMDs and IMDs.

Recently, Linux Container has been the de-facto standard for a cloud system, enabling cloud providers to create a virtual environment in a much more scaled manner. However, configuring container networks remains immature and requires automatic verification for efficient cloud management. We propose Verikube, which utilizes a novel graph structure representing policies to reduce memory consumption and accelerate verification. Moreover, unlike existing works, Verikube is compatible with the complex semantics of Cilium Policy which a cloud adopts from its advantage of performance. Our evaluation results show that Verikube performs at least seven times better for memory efficiency, at least 1.5 times faster for data structure management, and 20K times better for verification.

Multi-hop V2V communication is a fundamental way to realize data transmission in Vehicular Ad-hoc Networks (VANET). It has excellent potential in intelligent transportation systems and automatic vehicle driving, and positively affects the safety, reliability, and comfort of vehicles. With advantages in speed and trajectory, distribution along the route, size, etc., the urban buses have become prospective relay nodes for urban VANETs. However, it is a considerable challenge to construct stable and reliable (meeting the requirements of bandwidth, delay, and bit error rate) multi-hop routing because of the complexity of the urban road and bus line network in the communication area, as well as many unevenly distributed buses on the road, etc. Given this above, this paper proposes a new hierarchical routing algorithm based on V2V geographic topology segmentation. Urban hierarchical routing is divided into two layers. The first layer of routing is called coarse routing, which is composed of areas; the second layer of routing is called internal routing (bus routing within the area). Q-learning is used to formulate the sequence of buses that transmit information within each area. Details are as follows: Firstly, based on a city map containing road network information, the entire city is divided into small grids by physical streets. Secondly, based on an analysis of the characteristics of the adjacent grid bus lines, the grids with the same routing attributes are integrated into the same area, reducing the algorithm's computational complexity during route discovery. Then, for the calculated area set, a coarse route composed of the selected area is established by filtering out a group of areas satisfying from the source node to the destination node. Finally, the bus sequence between anchor intersections is selected within the chosen area, and a complete multi-hop route from the source node to the destination node is finally constructed. Sufficient simulations show that the proposed routing algorithm has more stable performance in terms of packet transmission rate, average end-to-end delay, routing duration, and other indicators than similar algorithms.

The prosperous Internet communication technologies have led to e-commerce in mobile computing and made Web of Things become popular. Electronic payment is the most important part of e-commerce, so many electronic payment schemes have been proposed. However, most of proposed schemes cannot give change. Based on proxy blind signatures, an e-cash payment system is proposed in this paper to solve this problem. This system can not only provide change divisibility through Web of Things, but also provide anonymity, verifiability, unforgeability and double-spending owner track.

Convolutional neural network (CNN) based vehicle re-identificatioin (ReID) inevitably has many disadvantages, such as information loss caused by downsampling operation. Therefore we propose a vision transformer (Vit) based vehicle ReID method to solve this problem. To improve the feature representation of vision transformer and make full use of additional vehicle information, the following methods are presented. (I) We propose a Quadratic Split Architecture (QSA) to learn both global and local features. More precisely, we split an image into many patches as “global part” and further split them into smaller sub-patches as “local part”. Features of both global and local part will be aggregated to enhance the representation ability. (II) The Auxiliary Information Embedding (AIE) is proposed to improve the robustness of the model by plugging a learnable camera/viewpoint embedding into Vit. Experimental results on several benchmarks indicate that our method is superior to many advanced vehicle ReID methods.

Multi-core fiber (MCF) is one of the most promising candidates for achieving ultra-wideband optical transmission in the near future. To build a network using MCF, a high-performance and reliable MCF connector is indispensable. We have developed an SC-type optical connector for MCF and confirmed its excellent optical performance, mechanical durability, and environmental reliability. To put the communication system using MCF into practical use, it is necessary to establish a procedure for measuring the initial connection characteristics. Fan-in / fan-out (FIFO) devices are indispensable for measuring the connection characteristics of MCF connectors. To measure the return loss of the MCF connector, it is necessary to remove the influence of reflection at the FIFO itself and at the connection points with the FIFO. In this paper, we compare four types of return loss measurement procedures (three usual method and a new method we proposed) and find that most stable measurement method involves using our new method, the OCWR method without FIFO. The OCWR method without FIFO is considered to be the most advantageous when used for outgoing inspection of connectors. The reason is that it eliminates the measurement uncertainty caused by the FIFO and enables speedy measurement.

This study presents a selective data-compression interconnection network to boost its performance. Data compression virtually increases the effective network bandwidth. One drawback of data compression is a long latency to perform (de-)compression operation at a compute node. In terms of the communication latency, we explore the trade-off between the compression latency overhead and the reduced injection latency by shortening the packet length by compression algorithms. As a result, we present to selectively apply a compression technique to a packet. We perform a compression operation to long packets and it is also taken when network congestion is detected at a source compute node. Through a cycle-accurate network simulation, the selective compression method using the above compression algorithms improves by up to 39% the network throughput with a moderate increase in the communication latency of short packets.

Industrial networks need to provide reliable communication services, usually in a redundant transmission (RT) manner. In the past few years, several device-redundancy-based, layer 2 solutions have been proposed. However, with the evolution of industrial networks to the Industrial Internet, these methods can no longer work properly in the non-redundancy, layer 3 environments. In this paper, an SDN-based reliable communication framework is proposed for the Industrial Internet. It can provide reliable communication guarantees for mission-critical applications while servicing non-critical applications in a best-effort transmission manner. Specifically, it first implements an RT-based reliable communication method using the Industrial Internet's link-redundancy feature. Next, it presents a redundant synchronization mechanism to prevent end systems from receiving duplicate data. Finally, to maximize the number of critical flows in it (an NP-hard problem), two ILP-based routing & scheduling algorithms are also put forward. These two algorithms are optimal (Scheduling with Unconstrained Routing, SUR) and suboptimal (Scheduling with Minimum length Routing, SMR). Numerous simulations are conducted to evaluate its effectiveness. The results show that it can provide reliable, duplicate-free services to end systems. Its reliable communication method performs better than the conventional best-effort transmission method in terms of packet delivery success ratio in layer 3 networks. In addition, its scheduling algorithm, SMR, performs well on the experimental topologies (with average quality of 93% when compared to SUR), and the time overhead is acceptable.

Named Data Networking (NDN) uses name to indicate content mechanism to divide content, and uses content names for routing and addressing. However, the traditional network devices that support the TCP/IP protocol stack and location-centric communication mechanisms cannot support functions such as in-network storage and multicast distribution of NDN effectively. The performance of NDN routers designed for specific functional platforms is limited, and it is difficult to deploy on a large scale, so the NDN network can only be implemented by software. With the development of data plane languages such as Programmable Protocol-Independent Packet Processors (P4), the practical deployment of NDN becomes achievable. To ensure efficient data distribution in the network, this paper proposes a protocol-independent multicast method according to each binary bit. The P4 language is used to define a bit vector in the data packet intrinsic metadata field, which is used to mark the requested port. When the requested content is returned, the routing node will check which port has requested the content according to the bit vector recorded in the register, and multicast the Data packet. The experimental results show that bitwise multicast technology can eliminate the number of flow tables distributed compared with the dynamic multicast group technology, and reduce the content response delay by 57% compared to unicast transmission technology.

This paper presents a novel frequency-controlled beam steering scheme for a phased-array antenna system (PAS). The proposed scheme employs phase-controlled carrier signals to form the PAS beam. Two local oscillators (LOs) and delay lines are used to generate the carrier signals. The carrier of one LO is divided into branches, and then the divided carriers passing through the corresponding delay lines have the desired phase relationship, which depends on the oscillation frequency of the LO. To confirm the feasibility of the scheme, four-branch PAS transmitters are configured and tested in a 10-GHz frequency band. The results verify that the formed beam is successfully steered in a wide range, i.e., the 3-dB beamwidth of approximately 100 degrees, using LO frequency control.

This paper shows structural optimal design of optical waveguide components utilizing an efficient 3D frequency-domain and 2D time-domain beam propagation method (BPM) with an alternating direction implicit (ADI) scheme. Usual optimal design procedure is based on iteration of numerical simulation, and total computational cost of the optimal design mainly depends on the efficiency of numerical analysis method. Since the system matrices are tridiagonal in the ADI-based BPM, efficient analysis and optimal design are available. Shape and topology optimal design shown in this paper is based on optimization of density distribution and sensitivity analysis to the density parameters. Computational methods of the sensitivity are shown in the case of using the 3D semi-vectorial and 2D time-domain BPM based on ADI scheme. The validity of this design approach is shown by design of optical waveguide components: mode converters, and a polarization beam splitter.

In various studies of attacks on autonomous vehicles (AVs), a phantom attack in which advanced driver assistance system (ADAS) misclassifies a fake object created by an adversary as a real object has been proposed. In this paper, we propose F-GhostBusters, which is an improved version of GhostBusters that detects phantom attacks. The proposed model uses a new feature, i.e, frequency of images. Experimental results show that F-GhostBusters not only improves the detection performance of GhostBusters but also can complement the accuracy against adversarial examples.