Packet Domain Research Articles

Failure recovery in the MANTRA architecture with an IPoWDM SONiC node and 400ZR/ZR+ pluggables

The utilization of IP over wavelength division multiplexing (IPoWDM) boxes in optical networks introduces coordination issues at the control plane level between the optical and packet domains. Indeed, IPoWDM boxes are technically packet devices, but the configuration of coherent optical pluggables requires knowledge of optical network state information (e.g., wavelength availability). MANTRA (metaverse ready architectures for open transport) aims to define a new SDN control architecture for managing IPoWDM, enhancing coordination between the packet and optical controllers. Within MANTRA, two distinct architectures were presented: Dual and Single. However, only the roles related to controller management are defined, while clear procedures are not specified for dealing with resource provisioning and failure recovery. This leads to the need for the definition and implementation of tailored procedures. Besides the characterization of the coherent optical pluggables performance, this paper presents and compares three procedures based on MANTRA to coordinate and control IPoWDM nodes in a multi-layer network performing failure recovery. The considered solutions have been designed and experimentally validated with a focus on the achievable traffic recovery performance considering IPoWDM configuration and communication within the SDN control architecture. An experimental testbed, comprising a sliced IPoWDM node running an extended version of the open-source SONiC network operating system, has been deployed to validate these solutions, with a comprehensive analysis of the time required to recover a real traffic flow that spans both the packet and optical domains.

Infiltration of Traditional Music Elements in Piano Teaching Models Combining Wavelet Packet Domain Auditory Perception

Abstract In Chinese piano teaching practice, the importance of auditory perception of music has been neglected, so that in piano performance and teaching, many people play music that lacks personality and emotional experience. This paper proposes an auditory perception model based on wavelet packet domain based on the acoustic properties of the human ear. The model analyzes the acoustical perception characteristics of piano audio signals through wavelet transform, and introduces adaptive wavelet packet decomposition into the calculation of the auditory perception model to simplify the calculation of the model, so that the obtained auditory masking threshold is closer to the actual value. Finally, the acoustic perception model is practically applied to piano teaching to verify its effectiveness. And the traditional Chinese music elements of Gong, Zheng and Shang were infiltrated in piano teaching. The results showed that the model detected the 3rd harmonic g1 with root tone C, whose frequency peak was most prominent at 397.25 Hz, and the sound pressure value reached 39.50 dB, indicating that the auditory perception ability directly affects the musical expression and creativity. This study cultivates students’ musical auditory perception ability, which significantly improves piano playing ability.

Enabling hierarchical control of coherent pluggable transceivers in SONiC packet–optical nodes

Traditional metro networks are composed of packet switching nodes (i.e., routers) interconnected by optical transport links. In this scenario, the packet and optical domains are clearly separated, using dedicated controllers. Standalone muxponders/transponders will be replaced in optical metro and transport networks by the utilization of hybrid packet–optical nodes equipped with coherent pluggable transceivers. Thus, the traditional packet control plane is unable to manage and fully support the specific optical parameters required to configure such pluggable modules. Moreover, the coordination between the optical and packet layers within this hybrid node has not been standardized yet and requires careful design to enable effective management of connectivity services. This paper proposes two software-defined networking (SDN)-based hierarchical solutions to coordinate and control coherent pluggable transceivers in a multi-layer network exploiting hybrid packet–optical nodes. The two solutions have been designed and validated focusing on the pluggable module configuration and the communication within the SDN hierarchical architecture. An experimental testbed including two packet–optical nodes, running an extended version of the open-source Software for Open Networking in the Cloud (SONiC) operating system, is deployed to show the effectiveness of the two solutions, with a deep analysis of the time required to set up end-to-end connections spanning the packet and optical domains.

A visually secure image encryption scheme using adaptive-thresholding sparsification compression sensing model and newly-designed memristive chaotic map

Aiming at the deficiencies of existing image compression-encryption algorithms, such as unstable reconstruction performance and weak crypticity, a novel visually secure image encryption scheme based on the adaptive-thresholding sparsification compression sensing model and the newly designed memristive chaotic map is proposed in this paper. First, the plain image is sparsely represented in the wavelet packet domain. Then, the coefficient matrix is scrambled and compressed using parallel compressive sensing with assistance from the newly developed adaptive-thresholding sparsification model. Next, the compressed image is re-encrypted by the FAN transform and diffusion to generate a noise-like secret image. Finally, the reversible matrix encoding-based embedding method is employed to create a meaningful cipher image. To improve the execution efficiency of the encryption algorithm without affecting the security performance, a low-dimensional discrete memristive chaotic map is designed and applied in the compression, encryption and embedding stages. Additionally, the Lp matrix norm is utilized to establish an adaptive threshold model to effectively enhance the compression performance. Simulation results and analyses are presented to demonstrate the effectiveness, the compressibility, and the secrecy of the proposed scheme.

Forwarding in Energy-Constrained Wireless Information Centric Networks.

Information Centric Networks (ICNs) have been considered one of the most promising candidates to overcome the disadvantages of host-centric architectures when applied to IoT networks, having the potential to address the challenges of a smart city. One of the foundations of a smart city is its sensory capacity, which is obtained through devices associated with the IoT concept. The more sensors spread out, the greater the ability to sense the city. However, such a scale demands high energy requirements and an effective improvement in the energy management is unavoidable. To improve the energy management, we are proposing an efficient forwarding scheme in energy-constrained wireless ICNs. To achieve this goal, we consider the type of devices, their internal energy and the network context, among other parameters. The proposed forwarding strategy extends and adapts concepts of ICNs, by means of packet domain analysis, neighbourhood evaluation and node sleeping and waking strategies. The proposed solution takes advantage of the neighbourhood to be aware of the moments to listen and forward packets in order to consistently address mobility, improving the quality of content delivery. The evaluation is performed by simulation with real datasets of urban mobility, one from the lagoon of “Ria de Aveiro” and the other from a vehicular network in the city of Porto. The results show that the proposed forwarding scheme resulted in significant improvements in network content availability, in the overall energy saving and, consequently, in the network lifetime.

Prediction of remaining useful life of rolling bearing based on fractal dimension and convolutional neural network

In order to predict the remaining useful life (RUL) of rolling bearings in complex environmental conditions, a bearing RUL prediction method based on fractal dimension and one-dimensional convolutional neural network (1D-CNN) is proposed. This method uses fractal dimension to characterize the degeneration process of the rolling bearing and combines the features of time domain, frequency domain, wavelet packet domain, and entropy domain. Fractal dimension provides an analytical method for characterizing the complexity of vibration signals. The features extracted from different feature domains can complement each other’s advantages, reveal the degradation state of the bearing more comprehensively and achieve better performance. Then, the percentage of the remaining life of the bearing is used as the degradation tracking index of the rolling bearing. Based on the idea of stratified sampling, the training samples and test samples are constructed, and then a 6-layer CNN is constructed to train the model. Finally, three commonly used data sets of full-life bearings are used to verify the model, namely, IEEE prognostics and health management 2012 Data Challenge, IMS dataset, and XJTU-SY dataset. The experimental results show that, on the three experimental datasets, compared to the long short-term memory network (LSTM) and the extreme learning machine (ELM) methods, the prediction effect of the RUL of the bearing based on the fractal dimension and 1D-CNN proposed in our paper is better. Its mean absolute error and root mean square error (RMSE) and mean absolute percentage error (MAPE) have been reduced, and the correlation index ( R2), adjusted_ R2, and relative accuracy (RA) have been improved, which can predict the RUL of the bearing more accurately.

Intensive packet domain mining engine (IPDME)

PurposeThe service denial threats are regularly regarded as tools for effortlessly triggering online-based services offline. Moreover, the present occurrences reveal that these threats are being constantly employed for masking other vulnerable threats like disseminating malware, information losses, wire scams and mining bitcoins (Sujithra et al., 2018; Boujnouni and Jedra, 2018). In some cases, service denials have been employed to cyberheist financial firms which sums around $100,000. Documentation from Neustar accounts that is about 70 percent of the financial sector are aware of the threat, and therefore, incidents result in few losses, more than 35 percent of service denial attempts are identified as malware soon after the threat is sent out (Divyavani and Dileep Kumar Reddy, 2018). Intensive packet analysis (IPA) explores the packet headers from Layers 2 to 4 along with the application information layer from Layers 5 to 7 for locating and evading vulnerable network-related threats. The networked systems could be simply contained by low potent service denial operations in case the supplies of the systems are minimized by the safety modules. The paper aims to discuss these issues.Design/methodology/approachThe initial feature will be resolved using the IPDME by locating the standard precise header delimiters such as carriage return line feed equally locating the header names. For the designed IPDME, the time difficulties in locating the initial position of the header field within a packet with static time expenses of four cycles. For buffering packets, the framework functions at the speed of cables. Soon after locating the header position, the value of the field is mined linearly from the position. Mining all the field values consequentially resolves the forthcoming restrictions which could be increased by estimating various information bytes per cycle and omitting non-required information packets. In this way, the exploration space is minimized from the packet length to the length of the header. Because of the minimized mining time, the buffered packets could be operated at an increasing time.FindingsBased on the assessments of IPDME against broadly employed SIP application layer function tools it discloses hardware offloading of IPDME it could minimize the loads on the essential system supplies of about 25 percent. The IPDME reveals that the acceleration of 22X– 75X as evaluated against PJSIP parser and SNORT SIP pre-processor. One IPDME portrays an acceleration of 4X–6X during 12 occurrences of SNORT parsers executing on 12 processors. The IPDME accomplishes 3X superior to 200 parallel occurrences of GPU speeded up processors. Additionally, the IPDME has very minimal latencies with 12X–1,010X minimal than GPUs. IPDME accomplishes minimal energy trails of nearly 0.75 W using two engines and for 15 engines it is 3.6 W, which is 22.5X–100X less as evaluated to the graphic-based GPU speeding up.Originality/valueIPDME assures that the system pools are not fatigued on Layer 7 mining by transmitting straightforwardly based on network intrusions without branching into the operating systems. IPDME averts the latencies because of the memory accesses by sidestepping the operating system which essentially permits the scheme to function at wired speed. Based on the safety perception, IPDME ultimately enhances the performance of the safety systems employing them. The increased bandwidth of the IPDME assures that the IPA’s could function at their utmost bandwidth. The service time for the threat independent traffic is enhanced because of minimization over the comprehensive latencies over the path among the network intrusions and the related applications.

An integrated acoustic echo and noise cancellation system using cross-band adaptive filters and wavelet thresholding of multitaper spectrum

An efficient integrated system for acoustic echo and noise cancellation in hands free devices is proposed in this paper. Adaptive filters are usually employed in such systems for the acoustic echo cancellation. In order to reduce the computational complexity, sub band adaptive filters are commonly used since the order of filter required will be less but at the cost of distortion due to aliasing effect. In this work, cross-band adaptive filters are developed in wavelet domain/wavelet packet domain in tune with psychoacoustic model, to reduce the above distortion and thereby effectively estimate the echo and cancel it. The system uses wavelet thresholding technique for smoothening the log multitaper spectrum which eliminates the annoying musical noise in the processed output. To achieve efficient echo and noise cancellation, a novel switching mechanism to switch between wavelet filter bank and perceptual wavelet packet filter bank with most matching wavelet basis, from a dictionary of wavelet bases, depending on the type of noise present in each frame of the noisy speech is designed and developed in this work. The performance of the proposed integrated system is evaluated in terms of Acoustic Interference Cancellation (AIC) and Noise Attenuation (NA) under different Signal to Noise Ratio (SNR) conditions. The system exhibits very good performance even at very low SNRs close to −10 dB when compared with other such competitive systems.

Fast matching pursuit for wideband spectrum sensing in cognitive radio networks

Wideband spectrum sensing is one of the most challenging components of cognitive radio networks. It should be performed as fast and accurately as possible. Traditional wideband spectrum sensing techniques suffer from the requirement of analog-to-digital converters with very high sampling rates. Compressed sensing has been recently considered as a technique that may enable wideband spectrum sensing at a much lower sampling rate than that dictated by the Nyquist theorem. However, the complexity and speed of existing compressed sensing reconstruction techniques remained a barrier for such an application. In this paper, we introduce fast matching pursuit (FMP), a fast and accurate greedy recovery algorithm for compressed sensing. We show that the spectral data are sparse in the Haar wavelet and wavelet packet domains. We apply FMP to wideband spectrum sensing for cognitive radio networks. Our proposed algorithm is capable of reconstructing spectrum signals from samples at a rate of about 25% of the Nyquist rate, significantly faster than other related algorithms, at more than 99% probability of detection and less than 1% probability of false alarm.

Image denoising method based on local neighbourhood and modified mean in wavelet packet domain

Due to the imperfection of image acquisition systems and transmission channels, noise degrades the quality of almost every acquired image. There are number of denoising techniques which are in existence over the last few years, originated from various disciplines. Wavelet transform has speedily become one of the image processing tool for variety of applications. Unlike standard wavelet-based method, in the present paper, we have proposed new technique using local neighbourhood and modified mean in wavelet packet domain. On comparing this method with other methods we have obtained better quality of the estimated signal at the cost of more computational time.

Identification of Structural Stiffness Parameters via Wavelet Packet from Seismic Response

Vibration-based damage assessment approaches are conventionally and widely adopted to monitor the structural health of a building during the bases excitation process. This study explores the possibility of using structural stiffness parameters to locate the storeys of building that are damaged in an earthquake event. A damaged storeys usually exhibits stiffness parameters variations during a strong enough earthquake, and the corresponding stiffness of storey often change in the earthquake. The wavelet packet transform is applied to the measured acceleration responses of a structure to reconstruct the autoregressive with exogenous input (ARX) model in wavelet packet domain. The modal parameters of the structure are estimated directly through the identified coefficient matrixes of the ARX model. Next, the stiffness parameters of the structure that could be reconstructed form the identified natural frequencies and mode shapes would be used to detect the damage locating of a building. The accuracy of this procedure is numerically confirmed, the effects of the wavelet parameters and noise on the ability to accurately estimate the dynamic properties are also investigated.

PULSAR SIGNAL DENOISING METHOD BASED ON LAPLACE DISTRIBUTION IN NO-SUBSAMPLING WAVELET PACKET DOMAIN

ABSTRACT In order to improve the denoising effect of the pulsar signal, a new denoising method is proposed in the no-subsampling wavelet packet domain based on the local Laplace prior model. First, we count the true noise-free pulsar signal’s wavelet packet coefficient distribution characteristics and construct the true signal wavelet packet coefficients’ Laplace probability density function model. Then, we estimate the denosied wavelet packet coefficients by using the noisy pulsar wavelet coefficients based on maximum a posteriori criteria. Finally, we obtain the denoisied pulsar signal through no-subsampling wavelet packet reconstruction of the estimated coefficients. The experimental results show that the proposed method performs better when calculating the pulsar time of arrival than the translation-invariant wavelet denoising method.

An interlaced secure algorithm for RGB image encryption in wavelet packet domain

We propose a secure interlaced algorithm for RGB image encryption associated with Arithmetic Random Matrix Affine Cipher (ARMAC) in wavelet packet domain. In this approach, the arrangement of ARMAC parameters along with correct de-interlacing is mandatory for correct decryption. Computer simulation with standard example and result (security analysis) is given to analyze the capability and robustness of the proposed approach and comparison with existing methods are drawn. We have designed a highly secure algorithm wherein an RGB image can be encrypted with varied computational cost depending on the user, enabling real-time image encryption. Moreover, the proposed approach can be used in transmission of images over unsecured network.

NMR Log Data De-noising Method Based on a Variable Order Wavelet Packet Domain Adaptive Filtering

To improve the de-noising effects of low signal to noise ratio (SNR) nuclear magnetic resonance (NMR) log data, improve the calculating precision of the porosity parameters of the reservoirs, this paper attempts to apply the wavelet packet domain adaptive filtering algorithm to de-noise the NMR log data. First of all, the algorithm is interpreted in detail. And then, the de-noise off phenomenon is analyzed in the de-noising process of simulant and NMR echo data using the wavelet (packet) domain adaptive filtering algorithm. The factors affecting the occasion of the phenomenon are studied systematically, and a variable order processing scheme is proposed to eliminate the influence of the existence of the de-noise off phenomenon on the inversed T2 spectra. As a result, the effectiveness of the algorithm is verified by the application in the numerical simulation and NMR log data, respectively. The results indicated that, comparing with wavelet domain adaptive filtering algorithm, wavelet packet domain adaptive filtering algorithm is more suitable for low SNR-NMR echo data de-noising.

Optical service chaining for network function virtualization

This article presents an efficient optical service chaining architecture for network function virtualization in data centers. Service chaining (i.e., steering traffic through a sequence of network functions) is one emerging application of software-defined networking. However, existing schemes steer traffic solely in the packet domain, which is well suited for fine-grained (e.g., peruser level) flows carrying a relatively small volume of traffic. This article discusses how packet-based schemes do not yield sufficient efficiency for large/aggregated flows steered through high-capacity core network functions. It introduces an optical steering domain into the operator's data centers for NFV service chaining at a coarse-grained traffic level using wavelength switching. Performance evaluation shows that the optical steering domain can achieve significant power savings compared to using packet technologies as flow rates and the number of vNFs per service chain grow.

A Target Guided Subband Filter for Acoustic Event Detection in Noisy Environments Using Wavelet Packets

This paper deals with acoustic event detection (AED), such as screams, gunshots, and explosions, in noisy environments. The main aim is to improve the detection performance under adverse conditions with a very low signal-to-noise ratio (SNR). A novel filtering method combined with an energy detector is presented. The wavelet packet transform (WPT) is first used for time-frequency representation of the acoustic signals. The proposed filter in the wavelet packet domain then uses a priori knowledge of the target event and an estimate of noise features to selectively suppress the background noise. It is in fact a content-aware band-pass filter which can automatically pass the frequency bands that are more significant in the target than in the noise. Theoretical analysis shows that the proposed filtering method is capable of enhancing the target content while suppressing the background noise for signals with a low SNR. A condition to increase the probability of correct detection is also obtained. Experiments have been carried out on a large dataset of acoustic events that are contaminated by different types of environmental noise and white noise with varying SNRs. Results show that the proposed method is more robust and better adapted to noise than ordinary energy detectors, and it can work even with an SNR as low as -15 dB. A practical system for real time processing and multi-target detection is also proposed in this work.

Field-Trial Demonstration of Cost Efficient Sub-wavelength Service Through Integrated Packet/Circuit Hybrid Network [Invited

Carriers are under constant pressure to meet the ever-increasing bandwidth demand while reducing cost per bit, enhancing network throughput, and offering a large variety of services. Hybrid packet and circuit network technologies are being widely investigated and considered as a solution for offering both the high network throughput of the packet domain and wavelength services, i.e., a low fixed latency and zero packet loss. To enable carriers to serve a higher number of customers requiring wavelength services, optical transport network (OTN)-based sub-wavelength switching is adopted to support finer granularity with similar performance to full wavelength services. However, OTN is not able to perform statistical multiplexing and achieve the throughput efficiency of packet networks. In this work an integrated hybrid optical network field-trial is described to demonstrate the ability to both aggregate and transport sub-wavelength circuits, and offer high throughput efficiency by statistically multiplexing traffic on transport wavelengths. Results show the transport of sub-wavelength services with packet-delay variation limited to only 15 ns and 82.4% wavelength utilization using statistical multiplexing.

Research on Improving Strategies of PoC Session Setup Delay Based on TD-SCDMA Network

PoC is a half-duplex PTT service using VoIP technology based on cellular network packet domain carrying. However PoC uses the standard Session Initiation Protocol (SIP) to setup session. The standard SIP signaling is too long, which brings more setup delay and does not hold true the wireless communication network, so it must be cut. This paper researchs the method to reduce PoC session setup delay from SIP session cut. We achieve the testing results in the actual commercial network. The results shows that this method can effectivly shorten the PoC session setup delay.

Voice Service Solutions in Evolved Packet System

EPS network is the future direction of mobile network, and voice service is still important in the EPS network. In the conventional 2G/3G mobile communication, voice service is provided by circuit switching in the CS domain. As the LTE core network provides the access to high-speed and lower latency wireless packet data on the air interface 3GPP retains the PS domain rather than the CS domain in designing the core network. And voice service which is included in the packet domain is available through VOIP. To ensure high-quality voice services, 3GPP proposes two solutions: CSFB and SRVCC. Each option has its own applied conditions, advantages and disadvantages. This article first introduces EPC network framework and the functions of its core functional entities. Then the network framework and voice processing of the two programs (CSFB and SRVCC) are compared. At last, a conclusion of advantages and disadvantages of the two programs is given, and it will lay the basis for different options.

SAR Image Denoising Based on Wavelet Packet and Median Filter

In this study a novel image processing approach is proposed to improve the denoising in SAR images based on wavelet packet and median filter, Median filter is adopted to remove noise in the wavelet packet domain. At first, the process of the novel is introduced in detail .At last, by adding some simulated noise in the SAR image, the performance of the proposed approach is shown and compared with other filter algorithms in terms of PSNR