Packet Size Research Articles

Efficient data sensing and monitoring model for areca nut precision farming with wireless sensor network

<span>Arecanut plays a prominent role in economic life in India; it produces ‘betel nut’ which is primarily used for the masticatory purpose. Nutrient’s cycle and environmental factors impact the forming, these impacts can be minimized through sensing technology i.e., wireless sensor network incorporated with internet of things (IoT). Designing of sensing technologies is considered as primary steps in achieving the arecanut production through precision agriculture; This research focuses on designing and developing an efficient monitoring mechanism named efficient data sensing and monitoring (EDSM), the proposed model will minimize the energy, reduce the false alarm rate, and enhance the detection accuracy. EDSM comprises four-step optimal sensing mechanism; first, formulate the energy consumption, further in this step the sensor device information and all the preliminary details are analyzed. Second step, data are sensed optimally, third step includes monitored and alert is generated the fourth step includes the optimization of packet size. EDSM is evaluated considering the different parameters like energy consumption and alert generation for temperature. Performance comparison is carried out with the existing model considering parameters like fault detection, false alarm detection, event detection, and event false alarm rate. Comparative analysis shows proposed methodology simply outperforms the existing model with significant improvisation.</span>

Color Doppler shear wave elastography using commercial ultrasound machine with compensated transducer scanning delay.

Tissue elasticity can be measured and mapped using color Doppler elastography. In a previous study, a binary pattern of shear waves was observed using a color flow imaging (CFI) system with matched pulse Doppler packet size as well as shear wave frequency and displacement condition. In the present study, we demonstrate the possibility of mapping shear wave velocity and resolving phantom elasticity using any commercial ultrasound machine without fulfilling that condition. We derive a relation between Doppler autocorrelator integration time and the estimated flow velocity. The underlying principles behind the shear wave shadows captured by a typical modern ultrasound machine are investigated. The ultrasound machine measurement preset is calibrated to remove the effect of transducer array scanning delay in modifying the appearing wavenumber and thus correct the measurement error. The method was used to successfully measure the elasticity of a biological tissue-mimicking phantom and distinguish a stiff phantom from a soft phantom. Using this method, the elasticity of a biological tissue-mimicking phantom can be recovered with less strict constraint. As a result, it provides more flexibility to be implemented in common ultrasound machines. This method may be practically used to help identify tissue stiffness-related disease.

Effects of Mo and Nb on Microstructure and Charpy Impact Properties of CGHAZ in HSLA Steels

In this study, the effects of Mo and Nb on the microstructure and Charpy impact properties of coarse-grain heat affected zone (CGHAZ) in high-strength low-alloy (HSLA) steels were investigated. The high-Mo steel had a lower volume fraction of acicular ferrite (AF) and higher volume fraction of granular bainite (GB) than those of the low Mo steel. The high-Mo CGHAZ specimen had a lower volume fraction of AF and higher volume fraction of GB compared to the low-Mo CGHAZ specimen. This is because, an increase in Mo lowers the bainite transformation temperature, induces the formation of GB and bainitic ferrite (BF), and reduces the diffusion velocity of carbon, thereby inhibiting the formation of ferrite. The Nb-added steel had a volume fraction similar to that of AF but smaller packet sizes of GB compared to the non-Nb steel. Compared to the non-Nb CGHAZ specimens, the Nb-added CGHAZ specimen had a lower volume fraction of AF, a higher volume fraction of GB, smaller packet sizes of GB and BF, and a smaller prior austenite grain size. This is because, Nb forms Nb(C,N) to inhibit the grain growth, thus inhibiting the formation of GB and BF. The Nb-added low-Mo CGHAZ specimen with the highest AF fraction and smallest average grain size had the highest Charpy-absorbed energy. However, articles in the Journal of Welding and Joining reported that the other CGHAZ specimens with high volume fractions of GB and BF with coarse packets showed low Charpy-absorbed energy.

Integrating the IEEE 1451 and IEC 61499 Standards with the Industrial Internet Reference Architecture.

Industrial Internet of Things focuses on the manufacturing process and connects with other associated concepts such as Industry 4.0, Cyber-Physical Systems, and Cyber-Physical Production Systems. Because of the complexity of those components, it is necessary to define reference architectures models to manage Industry 4.0 and the Industrial Internet of Things. The reference architecture models aim to solve the interoperability problem enabling the syntactical and semantic levels of interoperability. A reference architecture model provides a bottom/top view of an industrial process, from the physical transducers at the physical layer to the business layer. The physical layer provides access to a twin representation of a physical thing in the digital world, extending the functionalities in the manufacturing process. This paper studies the syntactic interoperability between the IEEE 1451 and IEC 61499 in an industrial environment. The IEEE 1451 family of standards has the essential characteristics to support the information exchange between smart transducers (sensors and actuators), building the digital elements and meeting the Industry 4.0 requirements. The IEC 61499 standard enables industrial control and automation. These two standards combined at the syntactic level solve an interoperability problem. The IEC 61499 also provides data to the framework layer, supplying all the parameters defined for the communication layer specified by a reference architecture model. This paper combines the IEEE 1451 with the IEC 61499, enabling data exchange in a reference architecture model proposed for Industry 4.0. Network performance at the communication level of a reference architecture model in a local network and an external network is evaluated for the proposed application. The IEEE 1451 standard implementation and adoption to acquire data and communicate it inside an industrial process allowed the IEC 61499 standard to control an industrial process. The IEEE 1451 standard is implemented in a MSP430 low power microcontroller. A Raspberry Pi running FORTE and 4diac in the USA and Portugal were used to test a local network in Portugal and an external network in USA. Data related to network performance was obtained with Wireshark and processed with MATLAB. Tests using the Message Queuing Transport Telemetry Transport and Hypertext Transport Protocols verified the performance of these protocols, supported by the IEEE 1451 and IEC 61499 standards, showing that communication inside an Industry 4.0 environment is possible. MQTT protocol is faster, has a small packet size, and consumes less bandwidth. The HTTP protocol uses more bandwidth but is more reliable for real-time communication, essential for Industry 4.0.

Design of a novel austenitising bending process in forming characteristics of high-strength quenched and micro-alloyed steel: Experiment and simulation

A systematic study was carried out on a novel designed austenitising bending process to explore the effects of quenching temperatures on the evolution of microstructure and mechanical properties of high-strength micro-alloyed steel. Results reveal that the qualified parts could be bent into a satisfactory shape without spring-back and cracks in bending temperatures of 850–1000 °C. The simulation was applied to predict the equivalent stress, stress neutral layer (SNL) and plate thickness. Strength presents a decreasing trend with the increase of bending temperature owing to integrated influences of high-temperature dynamic recovery (DRV) and dynamic recrystallisation (DRX). Beyond that, SNL nearby the geometrical centre line throughout the plate thickness and dislocation pile-ups on the tension/compression zones are responsible for the smaller hardness on middle regions while higher hardness on the surface areas. Through austenite reconstruction, a smaller martensite packet size would directly improve the strength of the plates bent at a lower temperature. The prior austenite size may be related to the appearance of martensite variants but not necessary. Furthermore, the high accuracy by comparing the experimental results with simulation would provide a high-value reference for the practical manufacturing process of railway spring clips.

Fast and lean encrypted Internet traffic classification

Identifying the type of a network flow or a specific application has many advantages but becomes harder in recent years due to the use of encryption, e.g., by VPN. As a result, there is a recent wave of solutions that harness deep learning for traffic classification. These solutions either require a rather long time (15–60 Seconds) of flow data or rely on handcrafted features for solutions that classify flows faster.In this work, we suggest a novel approach for classification that extracts the most out of the two simple yet defining features of a flow: packet sizes and inter-arrival times. We employ a model that uses the inter-arrival times to parameterize the derivative of the flow hidden-state using a neural network (Neural ODE). We compare our results with a solution that uses the same data without the ODE solver and show the benefit of this approach.Our results can classify flows based on 20 or 30 consecutive packets taken from anywhere in one direction of a flow. This reduces the amount of traffic between the sampling point and the analyzer and does not require matching between two directions of the flow. As a result, our solution can classify traffic with good accuracy within a few seconds, and we show how to combine it with a more accurate (and a slower) classifier to achieve (mostly) fast and accurate classifications.

Capacitive Sensor and Alternating Drive Mixing for Microfluidic Applications Using Micro Diaphragm Pumps.

Microfluidic systems are of paramount importance in various fields such as medicine, biology, and pharmacy. Despite the plethora of methods, accurate dosing and mixing of small doses of liquid reagents remain challenges for microfluidics. In this paper, we present a microfluidic device that uses two micro pumps and an alternating drive pattern to fill a microchannel. With a capacitive sensor system, we monitored the fluid process and controlled the micro pumps. In a first experiment, the system was set up to generate a 1:1 mixture between two fluids while using a range of fluid packet sizes from 0.25 to 2 µL and pumping frequencies from 50 to 100 Hz. In this parameter range, a dosing accuracy of 50.3 ± 0.9% was reached, validated by a gravimetric measurement. Other biased mixing ratios were tested as well and showed a deviation of 0.3 ± 0.3% from the targeted mixing ratio. In a second experiment, Trypan blue was used to study the mixing behavior of the system. Within one to two dosed packet sets, the two reagents were reliably mixed. The results are encouraging for future use of micro pumps and capacitive sensing in demanding microfluidic applications.

Efficient models for enhancing the link adaptation performance of LTE/LTE-A networks

Link adaptation (LA) is the ability to adapt the modulation scheme (MS) and the coding rate of the error correction in accordance with the quality of the radio link. The MS plays an important role in enhancing the performance of LTE/LTE-A, which is typically dependent on the received signal to noise ratio (SNR). However, using the SNR to select the proper MSs is not enough given that adaptive MSs are sensitive to error. Meanwhile, non-optimal MS selection may seriously impair the system performance and hence degrades LA. In LTE/ LTE-A, the LA system must be designed and optimized in accordance with the characteristics of the physical (e.g., MSs) and MAC layers (e.g., Packet loss) to enhance the channel efficiency and throughput. Accordingly, this study proposes using two LA models to overcome the problem. The first model, named the cross-layer link adaptation (CLLA) model, is based on the downward cross-layer approach. This model is designed to overcome the accuracy issue of adaptive modulation in existing systems and improve the channel efficiency and throughput. The second model, named the Markov decision process over the CLLA (MDP-CLLA) model, is designed to improve on the selection of modulation levels. Besides that, our previous contribution, namely the modified alpha-Shannon capacity formula, is adopted as part of the MDP-CLLA model to enhance the link adaptation of LTE/LTE-A. The effectiveness of the proposed models is evaluated in terms of throughput and packet loss for different packet sizes using the MATLAB and Simulink environments for the single input single output (SISO) mode for transmissions over Rayleigh fading channels. In addition, phase productivity, which is defined as the multiplication of the total throughput for a specific modulation with the difference between adjacent modulation SNR threshold values, is used to determine the best model for specific packet sizes in addition to determine the optimal packet size for specific packet sizes among models. Results generally showed that the throughput improved from 87.5 to 89.6% for (QPSK rightarrow 16-QAM) and from 0 to 43.3% for (16-QAM rightarrow 64-QAM) modulation transitions, respectively, using the CLLA model when compared with the existing system. Moreover, the throughput using the MDP-CLLA model was improved by 87.5–88.6% and by 0–43.2% for the (QPSK rightarrow 16-QAM)and (16-QAM rightarrow 64-QAM) modulation transitions, respectively, when compared with the CLLA model and the existing system. Results were also validated for each model via the summation of the phase productivity for every modulation at specific packet sizes, followed by the application one-way analysis of variance (ANOVA) statistical analysis with a post hoc test, to prove that the MDP-CLLA model improves with best high efficiency than the CLLA model and the existing system.

A Reliable Load Balancing Fault Tolerant Multi-SDN Controller approach in a typical Software Defined Network

INTRODUCTION: In the 21st Century, we have an emerging, modernized networking approach for efficient transfer of data in the form of packets i.e Software defined Networking (SDN). It is often recognized as the network paradigm acquired by an isolated independent control plane by the means of the underlying networking interface. As the communication medium is getting rapidly increased, the usage of the number of resources are also increasing in the same ratio, this results to connectivity problem in communication networks as well. If the development in technology is gaining more interest, the resource utilization will also increase.OBJECTIVES: In the proposed work here, we need to establish the connection between the client (or the end user) and the server by calculating the network performance using the parameters such as server response time and the throughput of the network by the method of load balancing.METHODS: This paper aims to identify the new methods or techniques to improve the performance of SDN with the increase in reliability, specifically required to improve the real-time data delivery. Alternatively, a reliable disjoint, distributed Multi- SDN controller will be used, to collect the updated network information like packet size, connectivity, packet flow etc. The methods involved are ideal controller optimization technique, distruption acquiscent technique and Maximum flow shortest route technique.RESULTS: From the results obtained by the simulation, the Reliable Load balancing Fault Tolerant Multi-SDN Controller(RLFTMS) approach is more reliable, fault tolerant compared to the other existing traditional mechanisms.CONCLUSION: Load balancing based on the server response time, throughput is being compared , this improves the server workload ditribution among various datacenters. Ultimately the customers or clients will have a great experience in terms of the reducing response time and increase in the throughput.

METHODOLOGY FOR THE FORMATION OF INFORMATION SYSTEMS FALSE NETWORK TRAFFIC FOR PROTECTION AGAINST NETWORK RECONNAISSANCE

Simulation of false network traffic in order to protect the structural and functional characteristics of information systems is a difficult task in view of the self-similarity of its statistical properties in IP networks, not only in the current moment, but also retrospectively. A Hurst index based algorithm for assessing the degree of self-similarity of network traffic of information systems has been proposed. The connection between the fractal dimension of the attractor of the model of information system functioning and the Hurst index is shown. A technique has been developed to substantiate the characteristics of false network traffic to simulate the functioning of information systems in the process of reconfiguration of their structural and functional characteristics caused by an intruder conducting network reconnaissance. The methodology allows to solve the problem of improving the protection of information systems from network reconnaissance by providing the maximum likelihood of false network traffic by pseudophase reconstruction of the dynamic system attractor, approximating the time series of information traffic of the protected object. The approaches to the description of the network traffic of the information system are considered, the parameters determining the network interaction between the two nodes of the data transmission network are selected as follows: source IP-address, source port, destination IP-address, destination port, protocol, packet size, duration of connection. The process of functioning of information system in different situations is formalized and the dependences allowing to synthesize parameters of false network traffic, statistically similar to the reference ones are received.

Design and Analysis of Improved Dynamic Source Routing Protocol in Vehicular Ad-Hoc Network

Background and Objective: The present issues faced by the transport systems include enormous traffic jams and congestion, unexpected road accidents, unwanted time delays, pedestrians' crossings on main roads, wastage of fuel, and many more. ITS and some other technologies work together to overcome such factors contributing to a much more desirable transport system. This paper aims to identify the security measures that could increase the security of the routing protocol and improve the performance of the DSR routing protocol. If the number of establishing links is frequently broken, then the performance of the DSR routing protocol is not very good. A new modified DSR algorithm has been designed that would help in reducing the network overhead and increase the network quality. A comparison between the performances of both algorithms has also been studied, and the results show that improved DSR routing protocol has better efficiency in parameters like end-to-end network load delays and packet delivery ratio. Methods & Materials: The paper mainly focuses on securing the Dynamic Source routing algorithm by designing its modified version and simulating it. We have Proposed Modified DSR and discussed so far that the basic functionality of the DSR algorithm, its advantages and disadvantages. The main drawbacks include the end-to-end Delay, network overhead and packet delivery ratio. Following is a modified version of the dynamic source routing algorithm, which tries to overcome all the limitations of the basic algorithm at a certain level. In the Dynamic Source Routing algorithm, the Route Maintenance phase is used for the successful propagation of the packet within the network. The nodes that are involved in the transmission acknowledge the receiving of the packet to the preceding node. Results and Discussion: The present study aims at modifying the existing algorithm and designing a new modified algorithm that has less routing overhead, less Delay in packet transmission and high network quality. Modified DSR routing algorithm is examined on the parameters like E-2-E delay, Normalize Routing Overhead, PDR. When we compare the performance of the proposed method with the Existing protocol AODV, and DSR at a number of nodes equal to 50 then we get the Proposed DSR, which has the least end-to-end Delay among all the three protocols. Conclusion: In this paper, acomparison of Exiting DSR and Modified DSR in terms of end-to-end Delay, routing load and packet delivery ratio is made. After studying the readings, the conclusion drawn was that there is less network overhead and a high delivery ratio in modified DSR as compared to the existing DSR algorithm. The corrupted and destroyed packets are detected by the receiver, and in DSR, the mobility of mobile nodes is moderate. Under certain conditions, bidirectional and unidirectional links can be accepted. DSR routing protocols are highly dependent on the parameters such as area size, packet size, packet type, and others.

A Novel Routing Strategy Towards Achieving Ultra-Low End-to-End Latency in 6G Networks

Compared to 5G, 6G networks will demand even more ambitious reduction in endto-end latency for packet communication. Recent attempts at breaking the barrier of end-to-end millisecond latencies have focused on re-engineering networks using a hybrid approach consisting of an optical-fiber based backbone network architecture coupled with high-speed wireless networks to connect end-devices to the backbone network. In our approach, a wide area network (WAN) is considered with a high-speed optical fiber grid network as its backbone. After messages from a source node enter the backbone network through a local wireless network, these are delivered very fast to an access point in the backbone network closest to the destination node, followed by its transfer to the local wireless network for delivery to the destination node. We propose a novel routing strategy which is based on distributing the messages in the network in such a way that the average queuing delay of the messages through the backbone network is minimized, and also the route discovery time at each router in the backbone network is drastically reduced. Also, multiple messages destined towards a particular destination router in the backbone network are packed together to form a mailbag, allowing further reductions in processing overheads at intermediate routers and pipelining of mailbag formation and route discovery operations in each router. The performance of the proposed approach green based on these ideas has been theoretically analyzed and then simulated using the ns-3 simulator. Our results show that the average end-to-end latency is less than 380 µs (with only 46-79 µs within the backbone network under varying traffic conditions) for a 1 KB packet size, when using a 500 Gbps optical fiber based backbone network laid over a 15 Km × 15 Km area, a 50 Mbps uplink channel from the source to the backbone network, and a 1 Gbps downlink channel from the backbone network to the destination. The significant reduction in end-to-end latency as compared to existing routing solutions clearly demonstrates the potential of our proposed routing strategy for meeting the ultra-low latency requirements of current 5G and future 6G networks, particularly for mobile edge computing (MEC) application scenarios.

Performance of 5G Trials for Industrial Automation

Wireless- and 5G-enabled industrial automation is expected to include a plethora of different applications with a wide variety of requirements. In this article, evaluations are undertaken for the deployment of 5G in realistic industrial production environments with realistic deployment settings. Both deployments using commercial 5G systems and a 5G prototype system including pre-commercial and standard compliant URLLC functionality have been investigated. Systematic latency and reliability measurements were performed, over the air and in live networks, for different packet sizes, different devices, and networks with different capabilities (at different sites) to characterize the expected performance. The results indicate that today’s 5G latency performance significantly depends on packet size, transmission direction (uplink or downlink), and network configuration as well as on the end device’s design and capabilities. Our over-the-air measurements also empirically show that 5G technology and future networks have the capability of providing one-way latency of around 1 ms in both uplink and downlink for the various packet sizes tested. It is concluded that the requirements for very low latencies can be achieved with high reliability guarantees, as required in some of the most stringent industrial IoT applications.

Significant improvement in CGHAZ toughness of HSLA steel via welding with trailing mechanical treatment

The Coarse-grained heat-affected zone (CGHAZ) is well known as the local brittle zone in the welding joints of HSLA steels. In the present work, compressive strain is applied to the specimen during the CGHAZ welding thermal simulation process to achieve microstructure refinement and modification for toughness improvement. The strain is applied to the specimen when the temperature of the simulated thermal cycle decreased to 1100 °C, with the purpose of achieving dynamic recrystallization in the CGHAZ. Parallel experiments without the compressive strain are also conducted as a reference. The microstructure of the CGHAZ with and without the compressive strain was observed by optical microscopy (OM) and scanning electron microscopy (SEM). Transmission electron microscopy (TEM) was used for observation of the matrix and microstructure of martensite-austenite (M-A) constituents. Electron back-scattered diffraction (EBSD) techniques were used to get the information of boundary misorientation distribution. The toughness of the specimens under each condition was assessed through instrumented Charpy impact test at −20 °C. Results showed that the compressive strain refined prior austenite grain (PAG) size and packet size, while the block width and lath width were almost unaffected. Refinement of the PAG also modified the microstructure of M-A constituents. The microstructure refinement and modification of M-A constituents improved crack initiation energy and crack propagation energy, resulting in significant promotion of toughness from 60.20 J to 163.10 J.

Analysis of Web-Based IoT through Heterogeneous Networks: Swarm Computing over LoRaWAN.

The Internet of Things (IoT) leverages added valued services by the wide spread of connected smart devices. The Swarm Computing paradigm considers a single abstraction layer that connects all kinds of devices globally, from sensors to super computers. In this context, the Low-Power Wide-Area Network (LPWAN) emerges, spreading out connection to the IoT end devices. With the upsides of long-range, low power and low cost, LPWAN presents major limitations regarding data transmission capacity, throughput, supported packet length and quantity per day limitation. This situation makes LPWAN systems with limited interoperability integrate with systems based on REpresentational State Transfer (REST). This work investigates how to connect web-based IoT applications with LPWANs. The analysis was carried out studying the number of packets generated for a use case of REST-based IoT over LPWAN, specifically the Swarm OS over LoRaWAN. The work also presents an analysis of the impact of using promising schemes for lower communication load. We evaluated Constrained Application Protocol (CoAP), Static Context Header Compression (SCHC) and Concise Binary Object Representation (CBOR) to make transmission over the restricted links of LPWANs possible. The attained results show the reduction of 98.18% packet sizes while using SCHC and CBOR compared to HTTP and JSON by sending fewer packets with smaller sizes.

The Microstructure and Mechanical Properties of Ferritic-Martensitic Steel EP-823 after High-Temperature Thermomechanical Treatment

The effect of high-temperature thermomechanical treatment (HTMT) with plastic deformation by rolling in austenitic region on the microstructure and mechanical properties of 12% chromium ferritic-martensitic steel EP-823 is investigated. The features of the grain and defect microstructure of steel are studied by Scanning Electron Microscopy with Electron Back-Scatter Diffraction (SEM EBSD) and Transmission Electron Microscopy (TEM). It is shown that HTMT leads to the formation of pancake structure with grains extended in the rolling direction and flattened in the rolling plane. The average sizes of martensitic packets and ferrite grains are approximately 1.5–2 times smaller compared to the corresponding values after traditional heat treatment (THT, which consists of normalization and tempering). The maximum grain size in the section parallel to the rolling plane increases up to more than 80 µm. HTMT leads to the formation of new sub-boundaries and a higher dislocation density. The fraction of low-angle misorientation boundaries reaches up to ≈68%, which exceeds the corresponding value after HTMT (55%). HTMT does not practically affect the carbide subsystem of steel. The mechanical properties are investigated by tensile tests in the temperature range 20–700 °C. It is shown that the values of the yield strength in this temperature range after HTMT increase relative to the corresponding values after THT. As a result of HTMT, the elongation decreases. A significant decrease is observed in the area of dynamic strain aging (DSA). The mechanisms of plastic deformation and strengthening of ferritic-martensitic steel under the high-temperature thermomechanical treatments are also discussed.

Intelligent agent and optimization‐based deep residual network to secure communication in UAV network

Unmanned Aerial Vehicle (UAV) is adapted as a novel unit in upcoming wireless infrastructures wherein UAVs can play various roles in different applications. The UAV is utilized for navigating commands to attain surveillance. However, routing and localization are the major issues that own higher mobility and unstable links. This paper devises a novel technique for initiating secured communication in a UAV network (UAVN). At first, the simulation of the UAVN is done. After that, the data transmission is carried out amongst nodes using a routing path; hence, an optimal routing path is formed using the newly devised Tunicate Swarm Political Optimization (TSPO) algorithm. The newly devised TSPO algorithm integrates the Tunicate Swarm Algorithm and Political Optimizer. In addition, the data communication is done using an evaluation and monitoring agent. In addition, the malicious detection is done by a decision-making agent using the deep residual network (DRN). Here, the newly devised TSPO algorithm is used to train the deep residual. The input parameters considered in the DRN are round trip time, signal strength, packet delivery, packet size, and the number of incoming packets. Once a DRN classifies the attack and genuine users, the defensive agent is employed for attack mitigation. Thus, the attacks in data are mitigated by the defensive agents. The newly devised TSPO-based DRN obtained enhanced performance with the smallest delay of 0.0014 s, the highest detection rate of 0.9325%, and the highest packet delivery ratio of 11491.2%.

Analytical Models of the Performance of IEEE 802.11p Vehicle to Vehicle Communications

The critical nature of vehicular communications requires their extensive testing and evaluation. Analytical models can represent an attractive and cost-effective approach for such evaluation if they can adequately model all underlying effects that impact the performance of vehicular communications. Several analytical models have been proposed to date to model vehicular communications based on the IEEE 802.11p (or DSRC) standard. However, existing models normally model in detail the MAC (Medium Access Control), and generally simplify the propagation and interference effects. This reduces their value as an alternative to evaluate the performance of vehicular communications. This paper addresses this gap, and presents new analytical models that accurately model the performance of vehicle-to-vehicle communications based on the IEEE 802.11p standard. The models jointly account for a detailed modeling of the propagation and interference effects, as well as the impact of the hidden terminal problem. The model quantifies the PDR (Packet Delivery Ratio) as a function of the distance between transmitter and receiver. The paper also presents new analytical models to quantify the probability of the four different types of packet errors in IEEE 802.11p. In addition, the paper presents the first analytical model capable to accurately estimate the Channel Busy Ratio (CBR) metric even under high channel load levels. All the analytical models are validated by means of simulation for a wide range of parameters, including traffic densities, packet transmission frequencies, transmission power levels, data rates and packet sizes. An implementation of the models is provided openly to facilitate their use by the community.

Investigating the Effect of Traffic Sampling on Machine Learning-Based Network Intrusion Detection Approaches

Machine Learning (ML) based Network Intrusion Systems (NIDSs) operate on flow features which are obtained from flow exporting protocols (<i>i.e.,</i> NetFlow). Recent success of ML and Deep Learning (DL) based NIDS solutions assume such flow information (<i>e.g.,</i> avg. packet size) is obtained from all packets of the flow. However, often in practice flow exporter is deployed on commodity devices where packet sampling is inevitable. As a result, applicability of such ML based NIDS solutions in the presence of sampling (<i>i.e.,</i> when flow information is obtained from sampled set of packets instead of full traffic) is an open question. In this study, we explore the impact of packet sampling on the performance and efficiency of ML-based NIDSs. Unlike previous work, our proposed evaluation procedure is immune to different settings of flow export stage. Hence, it can provide a robust evaluation of NIDS even in the presence of sampling. Through sampling experiments we established that malicious flows with shorter size (<i>i.e.,</i> number of packets) are likely to go unnoticed even with mild sampling rates such as 1/10 and 1/100. Next, using the proposed evaluation procedure we investigated the impact of various sampling techniques on NIDS detection rate and false alarm rate. Detection rate and false alarm rate is computed for three sampling rates (<i>i.e.,</i> 1/10, 1/100, 1/1000), for four different sampling techniques and for three (two tree-based, one deep learning based) classifiers. Experimental results show that systematic linear sampler - SketFlow performs better compared to non-linear samplers such as Sketch Guided and Fast Filtered sampling. We also found that random forest classifier with SketchFlow sampling was a better combination. The combination showed higher detection rate and lower false alarm rate across multiple sampling rates compared to other sampler-classifier combinations. Our results are consistent in multiple sampling rates, exceptional case is observed for Sketch Guided Sampling (SGS) as it caused a drastic performance drop when sampling rate was changed from 1/100 to 1/1000. Our results provide valuable insights for network practitioners and researchers regarding on how packet sampling effects ML-based NIDS performance. In this regard full source code for sampling and ML experiments has been released: github.com/Jumabek/sampledFlowMeter and github.com/Jumabek/nids-with-sampling

Performance Evaluation of 5G Millimeter-Wave-Based Vehicular Communication for Connected Vehicles

Due to the drastic increase in the volume of data generated by connected vehicles (CVs), future vehicle-to-infrastructure (V2I) applications will require a communication medium that offers high-speed and high bandwidth communication while maintaining reliability in high-mobility traffic scenarios. The 5G millimeter-wave (mmWave) can solve the communication issues related to V2I applications. However, the performance of the 5G mmWave for vehicular communication in high-mobility urban traffic scenarios is yet to be evaluated. This study presents a case study on assessing the performance of the 5G mmWave-based vehicular communication in such traffic scenarios. We have designed three realistic use cases for performance evaluation based on three challenges: dynamic mobility, increased CV penetration level, and V2I application specifications, such as data rate and packet size. We have also created a simulation-based experimental setup using a microscopic traffic simulator (SUMO) and a communication network simulator (ns-3) to simulate the use cases. We have used delay, packet loss, throughput, and signal-to-interference-plus-noise ratio (SINR) as the communication performance evaluation metrics. Our analyses found that the CV penetration level is the primary determinant of the performance of the 5G mmWave. Moreover, once the data rate is increased by a factor of 40, delay and packet loss increase by factors of 6.8 and 2.8, respectively.