Radar Polarimetric information can effectively expand the understanding of target shape and structure, and have potential of exploring materials and local fine features of targets. In this paper, based on the theory o...
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ISBN:
(纸本)9781665446006
Radar Polarimetric information can effectively expand the understanding of target shape and structure, and have potential of exploring materials and local fine features of targets. In this paper, based on the theory of coherent and incoherent polarimetric decomposition, we extract features of multiple types of unmanned aerial vehicles with full polarization. Then communication with local agents (CLA) method is used to overcome shortcomings of difficulty of obtaining target training samples under real electromagnetic environment conditions. Based on the extracted polarimetric scattering mechanism, we can realize the accurate identification of UAVs without training samples. The validity of the proposed algorithm is verified based on electromagnetic data measured in anechoic chamber and calculated by the software. The experiment proves that the recognition rate of the proposed algorithm is higher than that of conventional algorithms, and it has the ability to characterize the fine structure of unmanned aerial vehicles.
Future network architectures supporting 5G, 6G, Internet of Things (IoT), and fixed line networks face diverse service requirements in various scenarios, particularly by growing Ultra Low-Latency and Reliable Applicat...
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ISBN:
(纸本)9781665439848
Future network architectures supporting 5G, 6G, Internet of Things (IoT), and fixed line networks face diverse service requirements in various scenarios, particularly by growing Ultra Low-Latency and Reliable Applications (ULLRA) such as: autonomous driving, remote surgery, augmented reality, virtual reality, IoT applications, etc. Network Function Virtualization (NFV) and software Defined Networking (SDN) are two promising complementary solutions to meet diverse service requirements. In this study, we propose a novel application- and reliability-aware SFC embedding algorithm aiming to (a) decrease the latency and (b) increase the reliability of ULLRA. In this regard, we prioritize ULLRA as high priority SFC requests and reserve an amount of physical resources (bandwidth, memory, CPU) for embedding only high priority SFC requests to improve their latency and reliability. We formulate our proposed algorithm in the form of an Integer Linear Programming (ILP) optimization model to obtain optimal results. We also offer a heuristic algorithm to obtain near optimal results to reduce the execution time and make it usable for real-world networks. We consider constraints on maximum tolerable end-to-end delay, physical resource utilization (bandwidth, memory, CPU), and reliability. We examine our proposed SFC embedding algorithm in different test scenarios such as changing the number and the length of SFC requests, the proportion of reserved physical resources for high priority SFC requests, and the proportion of low-latency traffic flows to the total traffic flows. The results show that our proposed algorithms effectively improve the latency and reliability of ULLRA with minimal side effects on other applications compared to state of the art algorithms.
In existing wireless networks, path loss and signal interference have a negative impact on the user experience. Network coding is a technique that brings higher throughput and more stable *** network coding based algo...
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ISBN:
(纸本)9781665439848
In existing wireless networks, path loss and signal interference have a negative impact on the user experience. Network coding is a technique that brings higher throughput and more stable *** network coding based algorithms for end-to-end network performance is seldom addressed which might limit the opportunities applying network coding in reality. In this paper, we propose a network coding platform that consist of Network Simulator 3 (ns-3) and a programmable switch (NetFPGA). The former is used to emulate a wireless network environment for an application while the latter is used to enhance the performance running the network coding based algorithms which are computationally intensive in realtime. We will demonstrate the usage of the proposed platform to evaluate the performance in terms of end-to-end throughput and latency in a WiFi network. Based on such platform, various computationally intensive algorithms can be further designed and investigated in different networks in the future.
The article presents the relevance of developing a method for recovering lost sections of the map of the underlying surface. The study aims to create a high-speed and highly efficient system for recovering the lost im...
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The article presents the relevance of developing a method for recovering lost sections of the map of the underlying surface. The study aims to create a high-speed and highly efficient system for recovering the lost image area map of the underlying surface. The methods of modeling radar images are considered. The object of research are methods for constructing and restoring images of a map of the area. We consider spatial autocorrelation as image pre-processing for its subsequent analysis when restoring a part of the map in the direction of the radar carrier course. Imitation of visual attention is presented. The algorithm for recovering images of lost areas is investigated and its software implementation is developed. The effectiveness of the developed algorithm was evaluated on a test example using a statistical criterion.
This article is a proof that it is now possible to create modern technological solutions to human problems using open-source software. As a function for testing, this work implements a simple face recognition function...
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ISBN:
(数字)9781665404761
ISBN:
(纸本)9781665446426
This article is a proof that it is now possible to create modern technological solutions to human problems using open-source software. As a function for testing, this work implements a simple face recognition function, namely, it uses the Haar algorithm for which the testing was carried out. During the work of the system, the problem of the recognition method is investigated.
In this work, authors present a Hardware (HW) based loopback strategy which is a new paradigm in network processing, for HW efficient and cost-effective integration of Time Sensitive Networking (TSN) functionalities w...
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ISBN:
(纸本)9781665439848
In this work, authors present a Hardware (HW) based loopback strategy which is a new paradigm in network processing, for HW efficient and cost-effective integration of Time Sensitive Networking (TSN) functionalities within automotive Gateways (GWs). This innovative HW architecture permits to manage the complexity of TSN functionalities integration within In-Vehicle Networks (IVNs) by reusing the already existing HW resources in GWs, interconnected in such a way that allows to perform all the required processing, independently of the TSN algorithms in place. The proposed architecture follows the software Defined Networking (SDN) approach, separating control plane and data plane. The data plane is kept as simple as possible to maximize performance and reduce latency, while the complexity of the different TSN algorithms integration is handled within the control plane. Furthermore, it provides fully autonomous management of the TSN algorithms in HW, without intervention of the CPU. The newly introduced loopback path provides the capability to send frames from the egress stage back to the processing stage, to be processed again when required, allowing also to replicate them and independently route them wherever needed by the application. The loopback is also scalable, flexible and modular allowing to interconnect as many loopbacks as required by the network device. It also allows to process frames from the loopback path in parallel with frames coming from ingress ports, having thus no negative impact in the throughput of the network device. Moreover, it has a strong focus in low latency, securing a fast track for the loopback path which allows to keep the device performance under control, contributing towards future automotive TSN-compliant networking solutions.
Commercial loads such as food courts, commercial kitchens, and restaurants are growing day by day. Their power consumption shares a considerable amount of the total power consumption of any country. This paper represe...
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ISBN:
(纸本)9781665409636
Commercial loads such as food courts, commercial kitchens, and restaurants are growing day by day. Their power consumption shares a considerable amount of the total power consumption of any country. This paper represents an optimal energy scheduling algorithm for commercial loads like food courts and commercial kitchens with a wind energy source as a small renewable source and a battery as an energy storage system (ESS). As the power generation through wind plant depends upon wind speed which is variable in nature, so in this paper Weibull probability distribution function is used to model this behaviour of wind mathematically. An ESS is also used to reduce the impact of this behaviour of wind on loads. This algorithm also proposes the control strategy for the operation of the air-conditioning system. Then this model utilizes the mixed-integer programming algorithm to optimize the total cost of electrical energy consumption of any food court or restaurant. The CPLEX solver of GAMS software is used to apply the above technique. In this model, a real-time pricing scheme is used as a demand response technique. Further, in the end, the results show the effect of this algorithm on the total cost of energy consumption on a daily basis.
In the era of Industry 4.0, various technologies have been great assisting tools for different industries to improve their work efficiency and enhance customers' satisfaction and loyalty. This paper discusses the ...
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ISBN:
(纸本)9781665437721
In the era of Industry 4.0, various technologies have been great assisting tools for different industries to improve their work efficiency and enhance customers' satisfaction and loyalty. This paper discusses the issue of shipment delay and sales prediction by understanding how various attributes, based on data from the retail industry, will impact on their result. It was found that the locational factors and product category have been determining fluctuating sales or prominent delays. The results of machine learning algorithms are also discussed on how a better correlation in forecast and attribute relationships can be attained.
A growing trend is that network service providers and applications are integrated more closely through open APIs for better end-to-end performance. In particular, the providedaided network information can help applica...
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A growing trend is that network service providers and applications are integrated more closely through open APIs for better end-to-end performance. In particular, the providedaided network information can help applications orchestrate their traffic for a better quality of experience, and is gaining a lot of attention from both the academia and the industry. However, enabling automated network-aware application optimization in today's Internet is difficult because of the multivendor, multi-domain nature of carrier networks. In this paper, we introduce Sextant, a novel network information exposure system, taking a solid step towards enabling network-aware application optimization in carrier networks. Our work is driven by a real requirement from an international ISP, where timely, accurate distance information is critical to fully utilize its CDN caches deployed at different Point-of-Presence (PoP). We design a novel, flexible requirement model, allowing applications to specify their interests. The queries are efficiently carried out using our aggregation and incremental update algorithms. Evaluations demonstrate that our prototype system operates on top of real router software images, and can efficiently handle dynamics from multiple ASes.
Malware programs attack computer systems, smart mobile devices, and some applications. Malware is a program that needs to be watched out for because it can be a threat to computer users and internet networks. Malware ...
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ISBN:
(纸本)9781665439978
Malware programs attack computer systems, smart mobile devices, and some applications. Malware is a program that needs to be watched out for because it can be a threat to computer users and internet networks. Malware was created to steal personal information about a computer user or control a user’s device over a network. Computers are easily infiltrated by various malware programs that can interfere with and even damage user files. Many users are not aware of the entry of malware programs into a computer, one of which is through a network that contains the malware program. To solve this problem, this study discusses malware detection based on network traffic and classifies these types of networks based on their groups so that they can help detect whether the network contains malware or not. The data used in this study was taken from the Kaggle Data Set, namely the Android Network Traffic Malware with a total of 7845 Data in the form of a CSV file containing a collection of data that has been captured based on traffic on the network that contains malware and does not contain malware. The process of training and testing on the Data Set is carried out using the Rapidminer Tools by making a Binary Classification or creating two classes, namely the malicious class and the benign class. The method used is Machine Learning by comparing the Random Forest Algorithm, Decission Tree and Gradient Boosted Tree. The results obtained from the three algorithms show that Random Forest has the highest level of accuracy.
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