Time Packet Research Articles

Non-invasive analysis of macro-crack on the characteristics of ultrasonic guided wave

The effects of macro-crack in plates on the characteristic of ultrasonic guided wave were studied. Using the Finite Element Model and numerical calculation method, the finite element mesh models of various macro-crack in aluminum plate were established. The single S0 or A0 mode Lamb wave was excited in plate by the wave structure loading method. The propagation time and amplitude of wave packet in the received signal were analyzed to study the phenomenon of mode transformation and the relationship between macro-crack size and signal amplitude. The simulation results show that there is mode conversion when the single mode Lamb wave interacts with an asymmetric macro-crack, and no mode conversion with a symmetric macro-crack. The energy of reflected wave increases with the increase of the depth and width of macro-crack, and the energy of transmitted wave decreases correspondingly. The size and inclined angle of macro-crack can be quantitatively estimated by the fitting function from the energies of reflected and transmitted waves. The variation of crack depth, width and angle is approximately linear with the amplitudes of reflected and transmitted wave packets. A fitting function is constructed by using the amplitude ratio of reflected wave packet or transmitted wave packet to total wave packet, which can be used to estimate the macro-crack depth, width and angle. This conclusion is helpful to the detection of macro-crack in the actual production and service of plate structures.

Magnonic Klein and acausal tunneling enabled by breaking the anti parity-time symmetry in antiferromagnets

Klein tunneling associated with particle-antiparticle pair productions across a potential barrier is a key prediction of quantum-field theory for relativistic particles. Yet, a direct experimental realization is hampered by the particles large rest mass resulting in high potential barrier. Here, for non-Hermitian antiferromagnets, at the verge of the anti-parity-time symmetry transition, chiral magnons are demonstrated to offer a bosonic platform to access Klein tunneling at meV energies in experimentally feasible settings. Our analytical and numerical simulations evidence that magnetic damping renders a low energy mechanism for the breakdown of the magnonic vacuum and for creating particle-antiparticle pairs in strong magnetic fields. Adopting Feynman’s picture for antiparticles, the tunneling time of an incident magnon wave packet across a supercritical barrier is found to be negative. The uncovered aspects point to the potential of chiral magnons for addressing fundamental physics in a conceptually simple setup with the potential for use in chirality-dependent magnonic computing.

Blockchain-assisted Secure Routing Protocol for Cluster-based Mobile-ad Hoc Networks

MANETs aredecentralized network that involves mobile nodes. As the overall network is mobile and has no centralization, network management, routing, and security become very challenging. Though many works have been presented, still there is a lack in organizing the network due to unauthorized access, centralized security schemes, and the dynamic nature of the nodes. This paper proposed a novel Blockchain-assisted Secure Routing (Block-Sec) protocol for MANETs. All mobile nodes are authenticated by Distributed One-Time Passcode (DOT) based authorization scheme. All authorized nodes are segregated into multiple clusters based on Weight based Dynamic Clustering (WDC) algorithm in which multiple metrics are considered in clustering and re-clustering processes. After cluster formation, each cluster is elected with optimal Cluster Head (CH) by Strawberry Optimization (SBO) algorithm with a new objective function. After cluster formation, the optimal route is selected by Fast Neural Net-assisted Fuzzy (FNNF) algorithm by combining multiple variables. Data transmission is secured by Efficient Elliptic Curve (E2C2) algorithm. With the combined algorithms, the proposed approach obtainedimproved efficiency in packet delivery ratio (PDR), throughput, time analysis, and security level.

Performance and Scalability Analysis of SDN-Based Large-Scale Wi-Fi Networks

The Software-Defined Networking (SDN) paradigm is one that is utilized frequently in data centers. Software-Defined Wireless Networking, often known as SDWN, refers to an environment in which concepts from SDN are implemented in wireless networks. The SDWN is struggling with challenges of scalability and performance as a result of the growing number of wireless networks in its coverage area. It is thought that SDN techniques, such as Mininet-Wi-Fi and Ryu Controller for wireless networks, can overcome the problems with scalability and performance. Existing Wi-Fi systems do not provide SDN execution to end clients, which is one reason why the capability of Wi-Fi is restricted on SDN architecture. Within the scope of this study, we analyzed Wi-Fi networks operating on SDN using the Transmission Control Protocol (TCP) and User Datagram Protocol (UDP). By utilizing a testbed consisting of Ryu Controller and Mininet-Wi-Fi, we were able to test Wi-Fi over SDN and evaluate its performance in addition to its scalability. When evaluating the performance of a network, we take into account a number of different metrics, such as bandwidth, round-trip time, and jitter. In order to assess the level of performance, the SDN-based Wi-Fi controller Ryu is linked to an increasing number of access points (1, 2, 3, and 4) as well as stations (10, 30, 50, and 100). The experimental findings obtained using Mininet-Wi-Fi indicate the scalability and dependability of the network performance provided by the SDN Wi-Fi network controller Ryu in an SDN environment. In addition, the round-trip time for TCP packets grows proportionally with the number of hops involved. A single access point is capable of simultaneously supporting up to fifty people at once.

Delay-Aware and Link-Quality-Aware Geographical Routing Protocol for UANET via Dueling Deep Q-Network.

In an unmanned aerial vehicles ad hoc network (UANET), UAVs communicate with each other to accomplish intricate tasks collaboratively and cooperatively. However, the high mobility of UAVs, the variable link quality, and heavy traffic loads can lead to difficulties in finding an optimal communication path. We proposed a delay-aware and link-quality-aware geographical routing protocol for a UANET via the dueling deep Q-network (DLGR-2DQ) to address these problems. Firstly, the link quality was not only related to the physical layer metric, the signal-to-noise ratio, which was influenced by path loss and Doppler shifts, but also the expected transmission count of the data link layer. In addition, we also considered the total waiting time of packets in the candidate forwarding node in order to decrease the end-to-end delay. Then, we modeled the packet-forwarding process as a Markov decision process. We crafted an appropriate reward function that utilized the penalty value for each additional hop, total waiting time, and link quality to accelerate the learning of the dueling DQN algorithm. Finally, the simulation results illustrated that our proposed routing protocol outperformed others in terms of the packet delivery ratio and the average end-to-end delay.

Sonic black hole duct

The sonic black hole is a type of acoustic black hole that attenuates sound propagation via the acoustic black hole effect. This phenomenon is when an incident acoustic wave propagates through a power-law tapering geometry causing the wavelength to compress, the wave speed to decrease, and the time for the wave packet to reach the exit to extend infinitely. As a result, the wave never reaches the exit, so it cannot be reflected or transmitted. However, this outcome relies on the taper approaching exactly zero, which is impossible to manufacture. Therefore, the taper must be truncated leading to imperfect sound absorption. One method to increase the sound absorption is by applying perforations to the rings. This study explores the effect that varying the perforations on the sonic black hole’s rings has on the absorption coefficient from 1 to 5 kHz.

Electrical Manipulation of Quantum Coherence in a Two-Level Molecular System.

We report the manipulation of ultrafast quantum coherence of a two-level single hydrogen molecular system by employing static electric field from the sample bias in a femtosecond terahertz scanning tunneling microscope. A H_{2} molecule adsorbed on the polar Cu_{2}N surface develops an electric dipole and exhibits a giant Stark effect. An avoided crossing of the quantum state energy levels is derived from the resonant frequency of the single H_{2} two levels in a double-well potential. The dephasing time of the initial wave packet can also be changed by applying the electric field. The electrical manipulation for different tunneling gaps in three dimensions allows quantification of the surface electrostatic fields at the atomic scale. Our work demonstrated the potential application of molecules as controllable two-level molecular systems.

An Efficient Distributed MAC Protocol for Underwater Acoustic Sensor Networks

Many marine scientific and industrial applications in underwater acoustic sensor networks (UASNs) are characterized by dynamic-high load and dense deployment. In such UASNs, the channel reservation mechanism is devised to deal with channel utilization degradation. Unfortunately, channel reservation would lead to an increase in end-to-end delay and a decrease in throughput due to long propagation delay in UASNs. To reduce end-to-end delay and improve throughput, we proposed an efficient distributed medium access control (ED-MAC) protocol for UASNs. ED-MAC reduces the impact of long propagation delays on channel reservation by removing the channel reservation confirmation process and improving channel reservation efficiency. First, the optimized time slot length for the next time frame is obtained based on the data packet number estimate and secondary transmission data packet number, which could reduce idle waiting time. Then, the channel reservation confirmation process is removed by distributed channel reservation mechanism, and efficient channel reservation is achieved through channel reservation packet collision-free transmission and channel multiplexing. Meanwhile, channel reservation is performed before packet generation. Thus, the data packet waiting delay is reduced. Finally, a distributed data packet time slot schedule scheme is proposed to achieve collision avoidance between different data packets, as well as data packets and channel reservation packets. The performance analysis and simulation results show that our proposed ED-MAC could efficiently reduce end-to-end delay and improve throughput in dynamic-high-load and dense UASNs. Simulation results show that ED-MAC can achieve a maximum 98.7% reduction in average end-to-end delay and a maximum 61.1% improvement in throughput.

On the Age of Status Updates in Unreliable Multi-Source M/G/1 Queueing Systems

The timeliness of status message delivery in communications networks is subjective to time-varying wireless channel transmissions. In this letter, we investigate the age of information (AoI) of each source in a multi-source M/G/1 queueing update system with active server failures. In particular, we adopt the method of supplementary variables to derive a closed-form expression for the average AoI in terms of system parameters, where the server repair time follows a general distribution and the service time of packets generated by independent sources is a general random variable. Numerical results are provided to validate the effectiveness of the proposed packet serving policy under different parametric settings.

Characterizing Privacy Leakage in Encrypted DNS Traffic

Increased demand for DNS privacy has driven the creation of several encrypted DNS protocols, such as DNS over HTTPS (DoH), DNS over TLS (DoT), and DNS over QUIC (DoQ). Recently, DoT and DoH have been deployed by some vendors like Google and Cloudflare. This paper addresses privacy leakage in these three encrypted DNS protocols (especially DoQ) with different DNS recursive resolvers (Google, NextDNS, and Bind) and DNS proxy (AdGuard). More particularly, we investigate encrypted DNS traffic to determine whether the adversary can infer the category of websites users visit for this purpose. Through analyzing packet traces of three encrypted DNS protocols, we show that the classification performance of the websites (i.e., user's privacy leakage) is very high in terms of identifying 42 categories of the websites both in public (Google and NextDNS) and local (Bind) resolvers. By comparing the case with cache and without cache at the local resolver, we confirm that the caching effect is negligible as regards identification. We also show that discriminative features are mainly related to the inter-arrival time of packets for DNS resolving. Indeed, we confirm that the F1 score decreases largely by removing these features. We further investigate two possible countermeasures that could affect the inter-arrival time analysis in the local resolver: AdBlocker and DNS prefetch. However, there is no significant improvement in results with these countermeasures. These findings highlight that information leakage is still possible even in encrypted DNS traffic regardless of underlying protocols (i.e., HTTPS, TLS, QUIC).

Fault Diagnosis Based on Optimized Wavelet Packet Transform and Time Domain Convolution Network

Fault Diagnosis Based on Optimized Wavelet Packet Transform and Time Domain Convolution Network

ASSESSMENT OF QUALITY OF SERVICE CHARACTERISTICS OF SIMILAR TRAFFIC IN GSM STANDARD MOBILE TELECOMMUNICATION NETWORKS

P/M/1, which models the service processes of self-similar GPRS packet traffic in GSM standard mobile telecommunication networks, including Pareto and limited Pareto distributions, and fBM/D/1/∝ type single-channel mass service system, which takes into account the self-similarity of this traffic, has been viewed. Development of telecommunication networks. has gone through many different stages of development to the current modern networks, which eventually resulted in a large number of different types of mobile telecommunication networks. One of such networks is GSM (Global system for mobile communication) standard mobile telecommunication networks. In these networks, the directions of rapid development of modern service services are observed recently, one of these directions is the GPRS (General packet radio service) superstructure service, which is considered the superstructure of the GSM mobile network and carries out the transmission of data in packets. Analytical models of these systems are developed based on them Analytical methods have been proposed for evaluating relevant quality of service characteristics such as the relative average waiting time of packets in these systems, average queue length, buffer volume, and packet dwell time in the system. As well as the nature of the dependence of the shape parameter of the Pareto distribution on the Herst parameter was determined based on the experiment.

Encrypted Traffic Classification Based on a Convolutional Neural Network

To resolve the issues of low accuracy, weak universality, and easy invasion of privacy in traditional encryption traffic classification methods, an encryption traffic classification method based on a convolutional neural network is offered. Firstly, according to the packet size and time message of the net traffic, the original traffic is transformed into a two-dimensional picture to avoid relying on the packet payload to violate privacy, and then the model is embedded. The Inception module performs feature fusion to improve the classification accuracy. Finally, the average pooling layer and the convolution layer are used to replace the fully connected layer, increasing the calculation speed and avoiding overfitting. Experimental results show that the algorithm achieves an accuracy of more than 95% for application traffic classification tasks.

Packet loss compensation over wireless networked using an optimized FOPI-FOPD controller for nonlinear system

Wireless networked control systems (WNCS) consist of an actuator, sensor, and controller communicating over wireless networks in place of traditional point-to-point wired connection. Due to their main advantages, a decrease in maintenance costs, more flexibility, and safety could be achieved. As a result, it attracted a great deal of interest, but packet losses and time delays in the wireless network through transmitting and receiving the data are considered very challenging issues, which impair the output accuracy of the WNCS and can affect the entire system stability. In this study, integer-order proportional integral-proportional derivative (PI-PD) and fractional-order PI-PD (FOPI-FOPD) controllers are proposed to reduce the effect of expected packet loss in a WNCS to improve system performance. At high packet loss percent, the PI controller is introduced to act as a compensator in the feed-forward loop to keep the system stable. MATLAB/Simulink and Truetime simulator are used to simulate the WNCS. The rotary inverted pendulum (RIP) is utilized as the object of the controllers. Grey wolf optimization (GWO) algorithm is used to find the optimal controllers and compensator parameters. The simulation results showed that the FOPI-FOPD is superior to PI-PD in the packet loss compensation.

Detection of Middlebox-Based Attacks in Healthcare Internet of Things Using Multiple Machine Learning Models.

The huge number of network traffic data, the abundance of available network features, and the diversity of cyber-attack patterns mean that intrusion detection remains difficult even though many earlier efforts have succeeded in building the Internet of Healthcare Things (IoHT). The implementation of an effective algorithm to filter out most of the probable outliers of Round Trip Time (RTT) of packets recorded in the Internet environment is urgently required. Congestion and interference in networks can arise when numerous biosensors in an IoHT system all attempt to communicate at once. Internet of Health Things networks are susceptible to both intra- and internetwork interference. In this research, the Server-Side Includes (SSI) attack is a key issue because it allows for network compromise as part of Internal Attacks. Despite recent advancements, SSI detection remains difficult due to the vast amounts of network traffic data, the abundance of network features, and the diversity of cyber-attack patterns (DDoS, DoS, Satan, spoofing, etc.). With the help of sensors, physiological data may be collected and sent to distant servers, where they can be analyzed in real time by doctors to help them catch diseases in their earliest stages. This is made possible by the Internet of medical things (IoMT). Wireless data transfer, however, leaves it vulnerable to hackers, especially if the data being transferred are particularly private or sensitive. Security measures designed for devices with more storage space and processing power will not work on those with less. However, machine learning for intrusion detection can give a tailored security response to the needs of IoMT systems. For SSI detection, current methods are either inefficient because of the large number of packets that need to be caught and analyzed or unsuccessful because of outlier values in the RTTs obtained from the captured TCP packets. To the same end, "downstream detection" refers to the process of calculating the total length of all connections made after a certain point. As a means of improving the SSI detection algorithm's throughput in a network environment, packet RTT outliers will be eliminated. Flow records are used as inputs by flow-based NIDS to determine whether or not a given flow is malicious. In order to detect middlebox-based attacks from two Medical Health IoT datasets, this paper proposes a unique architecture of explainable neural networks (XNN). The model's accuracy in classifying attacks in dataset 1 of the IoHT is 99.7%t, besides achieving 99.4% accuracy in categorising attacks on IoHT dataset 2.

An Adaptive Network Design for Advanced Metering Infrastructure in a Smart Grid.

A smart grid is a next-generation intelligent power grid that can maximize energy efficiency by monitoring power information in real time and by controlling the flow of power by introducing IT communication technology to the existing power grid. In order to apply a wireless communication network to a smart grid, it is necessary to be able to efficiently process large amounts of power-related data while enabling a high level of reliability and quality of service (QoS) support. In addition, international standards-based design is essential considering compatibility and scalability. The IEEE 802.15.4 standard is considered to be the most powerful communication method for processing data through the smart grid AMI. To reduce the energy consumption, as the duty cycle of the superframe increases, the probability of the congestion increases. However, this binary exponential algorithm in IEEE 802.15.4 standard does not account for the application of traffic characteristics that essentially negatively affect the smart grid network performances in terms of packet delivery ratio and time delay. Therefore, in this paper, we propose a new transmission scheme to reduce performance degradation by excessive collisions in the content access period (CAP), when data transmission is performed in IEEE 802.15.4 applied to smart grids. In addition, we investigated the main research topics required when applying wireless networking technology to smart grids and suggested improvement measures. Simulation results showed that the proposed scheme increased the data delivery rate and reduced the latency, and it was confirmed that reliability was improved.

Scattering of energetic electrons through nonlinear cyclotron resonance with coherent whistler-mode hiss emissions

Recent observations have revealed that plasmaspheric hiss consists of many discrete waves called “hiss elements.” However, the interaction of energetic electrons (10 keV to several MeV) with the plasmaspheric hiss has only been simulated by the quasilinear (QL) diffusion theory, which does not take the fine wave structure into account. The QL theory cannot address nonlinear particle motions determined by the inhomogeneity factor, which influences the scattering of electrons in pitch angle and energy. This study aims to identify differences between the nonlinear wave–particle interaction and QL theory for plasmaspheric hiss emissions. We conduct test particle simulations to demonstrate the nonlinear interactions between hiss waves and electrons. The nonlinear theory is used to model hiss elements consisting of discrete frequencies and continuous phases. Unlike the other theories, the frequency and amplitude variations in time of the hiss packet are taken into account. Frequencies of the packets are determined to satisfy the separability criterion; when the criterion is met, resonance overlapping is absent, and the electrons can generate each wave element independently. The realistic simulation model of hiss waves reproduces the scattering of electrons by both first- and second-order resonances. We also evaluate the efficiency of electron scattering by calculating nonlinear diffusion coefficients. The diffusion coefficient of equatorial pitch angle is of the same order of magnitude as those calculated by the QL diffusion theory, while we find the effective acceleration of resonant electrons by successive nonlinear trapping, which is not evaluated by the QL theory.

Convergence of a Packet Routing Model to Flows over Time

Mathematical approaches for modeling dynamic traffic can be roughly divided into two categories: discrete packet routing models and continuous flow over time models. Despite very vital research activities on models in both categories, their connection was poorly understood so far. We build this connection by specifying a (competitive) packet routing model, which is discrete in terms of flow and time, and proving its convergence to the intensively studied model of flows over time with deterministic queuing. More precisely, we prove that the limit of the convergence process when decreasing the packet size and time step length in the packet routing model constitutes a flow over time with multiple commodities. In addition, we show that the convergence result implies the existence of approximate equilibria in the competitive version of the packet routing model. This is of significant interest as exact pure Nash equilibria cannot be guaranteed in the multicommodity setting. Funding: This work was funded by the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany’s Excellence Strategy—The Berlin Mathematics Research Center MATH+ [Grant EXC-2046/1, project ID: 390685689] and the Research Training Group [Grant 2236 UnRAVeL].

HeteroTiC: A robust network flow watermarking based on heterogeneous time channels

Tracking back stealthy attackers is still a great challenge in face of complicated Internet environments and increased attacker capabilities. As a possible solution, network flow watermarking has been developed to embed attack labels actively in data flows, trying to identify the attack source accurately in time. However, due to the influences of uncertain network noises, the robustness of watermarking cannot be ensured efficiently in case of non-cooperative network scenarios currently. Meanwhile, it is difficult to enhance robustness and covertness simultaneously when suffering from severe network noises. Thus, a robust network flow watermarking based on Heterogeneous Time Channels (HeteroTiC) is proposed, for which packet order, packet timing and packet size constitute heterogeneous time channels to carry watermarks. The beginning positions are located by packet order to support accurate synchronization, the long watermark sequences are carried by inter-packet delays to improve capabilities against packet dropping and time jitter, the mapping relationships for the watermark sequences on heterogeneous time channels are mixed by packet size of the flow itself to enhance covertness. With multiple layers design of watermarking, HeteroTiC is designed to accomplish fast detection and accurate extraction on watermarks. By experiments, the average detection accuracy reaches 100% and the average extraction accuracy is validated with 94.2%. Furthermore, the same mapping pattern on multiple flows only accounts for 8.11%, which validates the covertness against multiple flow similarities. The extraction accuracy exceeds 9.76%∼18.1% in comparison with classical watermarking methods, which validates the robustness under network noises in Internet.

ICRP: Internet-Friendly Cryptographic Relay-Detection Protocol

Traffic hijacking over the Internet has become a frequent incident over the last two decades. From minor inconveniences for casual users to massive leaks of governmental data, these events cover an unprecedently large spectrum. Many hijackings are presumed to be caused by unfortunate routing mistakes, but a well-organized attacker could set up a long-term stealthy relay, accessing critical traffic metadata, despite suitable encryption schemes. While many studies focus on the mitigation of known attacks, we choose to design a complete detection method regardless of the attacker’s strategy. We propose a two-party cryptographic protocol for detecting traffic hijacking over the Internet. Our proposal relies on a distance-bounding mechanism that performs interactive authentication with a “Challenge–Response” exchange, and measures the round-trip time of packets to decide whether an attack is ongoing. Our construction is supported by worldwide experiments on communication time between multiple nodes, allowing us to both demonstrate its applicability and evaluate its performance. Over the course of this paper, we demonstrate our protocol to be efficient—itrequires only two cryptographic operations per execution inducing negligible workload for users and very few loss of throughput, scalable—no software updates are required for intermediate network nodes, routing protocol independent—this means that any future update of the route selection process will not induce changes on our scheme, and network friendly—the added volume of transiting data is only about 1.5%.