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Application Constraints and Safety Aware Mapping of AUTOSAR Applications on Multi-core Platforms

Application Constraints and Safety Aware Mapping of AUTOSAR ...

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ieee International conference on Embedded Software and Systems (ICESS)

作者： Vasu, Aishwarya Ramaprasad, Harini Southern Illinois Univ Dept Elec & Comp Engn Carbondale IL 62901 USA Univ North Carolina Charlotte Dept Comp Sci Charlotte NC USA

ISBN: (纸本)9781728164663

In order to reduce the size, weight, power, and cost (SWaP-C), adoption of high-performance multi-core platforms has received significant interest in the field of Automotive electronics. Deploying real-time automotive applications that adhere to the AUTomotive open System ARchitecture (AUTOSAR) standards and guidelines on multi-core platforms has several architectural challenges. In this paper, we propose heuristic-based approaches for the safe and efficient allocation of AUTOSAR applications on multi-core platforms with the consideration of application level constraints and architectural features such as Cache Locking. We also formulate an Integer Linear Program (ILP) for the same allocation problem and compare the effectiveness of both heuristic-based and ILP approaches.

关键词： Integer programming

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PTP Security Measures and their Impact on Synchronization Accuracy

PTP Security Measures and their Impact on Synchronization Ac...

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International conference on network and Service Management

作者： Filip Rezabek Max Helm Tizian Leonhardt Georg Carle I8 Network Architectures and Services Technische Universität München Germany

ISBN: (数字)9783903176515

ISBN: (纸本)9781665489928

The Precision Time Protocol (PTP) synchronizes clocks in a network with high precision. The protocol finds use in many areas, such as smart manufacturing, intra-vehicular networks, and critical infrastructure. It becomes clear that striving for security is an important goal. If an attacker succeeds in disturbing the network synchronization, the impact can result in a cascading set of failures. Unfortunately, neither the previous two ieee standards for PTP, nor the popular implementation linuxptp, feature or implement sufficient security *** work focuses on implementing the security extensions for PTP based on the latest PTP standard ieee 1588-2019 to minimize the threat of attacks and their possible impact. We provide a detailed analysis on PTP synchronicity and security. Based on that, we design and implement software-only tooling to quantify the PTP performance using commercial off-the-shelf hardware and open-source solutions on a linear topology with four to nine *** measurements compare the End-to-End (E2E) and Peer-to-Peer (P2P) delay calculation modes and the usage of Transparent Clocks (TC) in parts of the network. Both E2E and P2P show visible degradation of clock synchronization with each hop and standard deviations of 118.6 to 571 ns. The TCs perform better, demonstrating a standard deviation between 90 to 140 ns on four to nine hops. We evaluate different logSyncInterval values corresponding to different PTP profiles and do not observe a major impact on the clock behavior caused by the extensions. The measurement precision of the system is within ±40 *** evaluation of the newly implemented security extensions to linuxptp shows that the security extensions do not have a significant impact on the clock synchronization and our approach is a feasible addition to PTP. Besides, our contributions can aid network managers in assessing their PTP synchronicity systematically.

关键词： Protocols Power system protection Peer-to-peer computing Topology Security Synchronization Power system faults

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Minimal time delivery of multiple robots 59

Minimal time delivery of multiple robots

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59th ieee conference on Decision and Control (CDC)

作者： Aguiar, Miguel da Silva, Jorge Estrela de Sousa, Joao Borges Univ Porto LSTS Porto Portugal Inst Politecn Porto ISEP Porto Portugal

ISBN: (纸本)9781728174471

Consider a set of autonomous vehicles, each one with a preassigned task to start at a given region. Due to energy constraints, and in order to minimize the overall task completion time, these vehicles are deployed from a faster carrier vehicle. This paper develops a dynamic programming (DP) based solution for the problem of finding the optimal deployment location and time for each vehicle, and for a given sequence of deployments, so that the global mission duration is minimal. The problem is specialized for ocean-going vehicles operating under time-varying currents. The solution approach involves solving a sequence of optimal stopping problems that are transformed into a set variational inequalities through the application of the dynamic programming principle (DPP). The optimal trajectory for the carrier and the optimal deployment location and time for each vehicle to be deployed are obtained in feedback-form from the numerical solution of the variational inequalities. The solution is computed with our open source parallel implementation of the fast sweeping method. The approach is illustrated with two numerical examples.

关键词： Dynamic programming

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Application of advanced learning methods for detecting network configuration in a smart water distribution system 22

Application of advanced learning methods for detecting netwo...

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22nd ieee International conference on Automation, Quality and Testing, Robotics (AQTR)

作者： Predescu, Alexandru Mocanu, Mariana Lupu, Ciprian Univ Politehn Bucuresti Automat Control & Comp Bucharest Romania

ISBN: (纸本)9781728171661

Water distribution is one of the main pillars of modern society and accounts for a constant need of innovative solutions to age-old problems. There are many challenges associated to the aging infrastructure in large metropolitan areas as well as efficient operation of control structures, requiring improved decision support systems and autonomous operation based on available data. An extension of traditional methods with modern concepts is required such as using learning algorithms, smart meters and reactive programming for improving the quality of service in water distribution systems. This paper extends an IoT-based model with Deep Learning and automated test scenarios, while showing the effective application and comparison of learning techniques on experimental data in this domain. The experimental model is described from the hardware level to the IoT platform in a modern approach using the current state of software development and architectures for real-time data management.

关键词： Smart Water networks Internet of Things Deep Learning Machine Learning

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Information Classification Strategy for Blockchain-based Secure SDN in IoT Scenario

Information Classification Strategy for Blockchain-based Sec...

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39th ieee International conference on Computer Communications (ieee INFOCOM)

作者： Zhang, Peiying Liu, Fanglin Kumar, Neeraj Aujla, Gagangeet Singh China Univ Petr East China Coll Comp Sci & Technol Qingdao Peoples R China Thapar Inst Engn & Technol Comp Sci & Engn Dept Patiala Punjab India Newcastle Univ Sch Comp Newcastle Upon Tyne Tyne & Wear England

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186955

As people's dependence on the Internet increases, traditional network architectures with rigid characteristics will gradually fail to meet all demands. It has higher flexibility and provides a convenient platform for technologies and concepts such as the Internet of Things, cloud computing, and network function virtualization. However, the flexibility of SDN also brings various security risks. For example, (i) the fault-tolerant mechanism is not sound enough, if communication with the controller fails, then the forwarding layer device may not be able to obtain the routing information;(ii) more complex applications have lower reliability, and new applications may have hidden unknown vulnerabilities;and (iii) the open programmable interface is also in danger of being illegally intruded. To address these problems, this paper proposes a blockchain-based SDN monitoring system that uses the information invariance of the blockchain and a distributed consensus mechanism to enhance the security of SDN. It also uses the distributed storage feature of P2P network to enhance the disaster resistance of SDN. In addition, in order to prevent stakeholders and non-professionals from affecting the reliability of supervision, we use multicast instead of broadcasting for information transmission. While taking full advantage of the functions of flow control and protocol deployment, the overall security of the system can be effectively improved. Encouragingly, the simulation results show that the scheme can effectively control the traffic and balance the load at the same time. Furthermore, we also outlined some challenges and future research directions.

关键词： Software Defined network Blockchain Multicast Routing Algorithm network Security

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Analysis of the popularity of programming languages in open source software communities

Analysis of the popularity of programming languages in open ...

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2020 International conference on Big Data and Social Sciences, ICBDSS 2020

作者： Lu, Dongdong Wu, Jie Sheng, Yongxiang Liu, Peng Yang, Mengmeng Jiangsu University of Science and Technology School of Economics and Management Zhenjiang China Jiangsu University of Science and Technology School of Deep Blue Honor Zhenjiang China

ISBN: (纸本)9781728197517

Choosing a suitable programming language during the development of the project can get twice the result with half the effort the open source software community Gitee was taken as an example to explore the popularity of programming languages. We use pycharm to capture the corresponding number of followers, collections and forks of the projects and programming languages in the community then we use cluster analysis to classify programming languages and construct a binary matching network of programming languages and projects to verify the results of language popularity division the study found that programming languages can be divided into 5 types according to their popularity. Java, c and python belong to the first level, with higher popularity. Although the Go language is not widely used, it has attracted the attention of the majority of developers, and it is bound to develop into a mainstream language in the future. © 2020 ieee.

关键词： Cluster analysis

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Towards Cross-Platform Performance Portability of DNN Models using SYCL

Towards Cross-Platform Performance Portability of DNN Models...

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ieee/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC)

作者： Goli, Mehdi Narasimhan, Kumudha Reyes, Ruyman Tracy, Ben Soutar, Daniel Georgiev, Svetlozar Fomenko, Evarist M. Chereshnev, Eugene Codeplay Res London England Codeplay London England Intel Corp Santa Clara CA 95051 USA

ISBN: (纸本)9781665422871

The incoming deployment of Exascale platforms with a myriad of different architectures and co-processors have prompted the need to provide a software ecosystem based on open standards that can simplify maintaining HPC applications on different hardware. Applications written for a particular platform should be portable to a different one, ensuring performance is as close to the peak as possible. However, it is not expected that key performance routines on relevant HPC applications will be performance portable as is, especially for common building blocks such as BLAS or DNN. The oneAPI the initiative aims to tackle this problem by combining a programming model, SYCL, with a set of interfaces for common building blocks that can be optimized for different hardware vendors. In particular, oneAPI includes the oneDNN performance library, which contains building blocks for deep learning applications and frameworks. By using the SYCL programming model, it can integrate easily with existing SYCL and C++ applications, sharing data and executing collaboratively on devices with the rest of the application. In this paper, we introduce a cuDNN backend for oneDNN, which allows running oneAPI applications on NVIDIA hardware taking advantage of existing building blocks from the CUDA ecosystem. We implement relevant neural networks (ResNet-50 and VGG-16) on native CUDA and also a version of oneAPI with a CUDA backend, and demonstrate that performance portability can be achieved by leveraging existing building blocks for the target hardware.

关键词： Cross-performance Portability Deep Neural network cuDNN oneDNN SYCL High Performance Computing

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Semantic Data Pre-Processing for Machine Learning Based Bankruptcy Prediction Computational Model 22

Semantic Data Pre-Processing for Machine Learning Based Bank...

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22nd ieee International conference on Business Informatics (CBI)

作者： Yerashenia, Natalia Bolotov, Alexander Chan, David Pierantoni, Gabriele Univ Westminster Sch Comp Sci & Engn London England

ISBN: (纸本)9781728199269

This paper studies a Bankruptcy Prediction Computational Model (BPCM model) - a comprehensive methodology of evaluating a company's bankruptcy level, which combines storing, structuring and pre-processing of raw financial data using semantic methods with machine learning analysis techniques. Raw financial data are interconnected, diverse, often potentially inconsistent, and open to duplication. The main goal of our research is to develop data pre-processing techniques where ontologies play a central role. We show how ontologies are used to extract and integrate information from different sources, prepare data for further processing, and enable communication in natural language. Our Ontology of Bankruptcy Prediction (OBP Ontology) which provides a conceptual framework for a company's financial analysis, is built in the widely established Protege environment. An OBP Ontology can be effectively described with a Graph database (DB). A Graph DB expands the capabilities of traditional databases by tackling the interconnected nature of economic data and providing graph-based structures to store information, allowing the effective selection of the most relevant input features for the machine learning algorithm. To create and manage the BPCM Graph DB, we use the Neo4j environment and Neo4j query language, Cypher, to perform feature selection of the structured data. Selected key features are used for the supervised Neural network with a Sigmoid activation function. The programming of this component is performed in Python. We illustrate the approach and advantages of semantic data pre-processing, applying it to a representative use case.

关键词： semantic data analysis graph database ontology financial analysis financial ratios bankruptcy prediction computational model neural network Protege Neo4j Python

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The Brittleness of a Non-Reconfigurable Distribution network Topology Approach 8

The Brittleness of a Non-Reconfigurable Distribution Network...

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8th International conference on Condition Monitoring and Diagnosis (CMD)

作者： Chan, Steve Nopphawan, Parnmook Vit Tall Energy Unit Orlando FL 32835 USA IE2SPOMTF Orlando FL 32835 USA

ISBN: (纸本)9781728159317

Terminal distribution substations are central to system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI), as it is estimated that approximately 85% of the customer interruptions are due to failure at the distribution network. Enhancing resiliency within a distribution network typically centers upon the ability to switch to backup distribution feeders. The involved architectures typically involve distinct and disparate feeders connected through normally open tie switches, but the switches can be closed to allow certain interrupted customers to be temporarily transferred to adjacent feeders during outages. This paradigm is known as feeder reconfiguration (FRC), and it is a real-time operational control process within the overarching rubric of distribution automation;in this way, a distribution system can be reconfigured by closing tie (normally-open) switches (to re-energize healthy segments) and opening sectionalizing (normally-closed) switches (to isolate faulty segments). Obviously, the greater the numbers of switches, the greater the possibilities for reconfiguration and resiliency. The principal advantage of FRC is that the opening and closing of switching devices does not typically result in additional costs for distribution utilities. FRC can also be accelerated, via robust Fault detection, isolation, and service restoration (FDIR), which segues to the use of advanced distribution management systems (ADMS). ADMS can leverage artificial intelligence to detect and classify problems (e.g. incorrect load voltage profile, excessive technical power loss, phase voltage and current imbalances overloading of transformers and cables) quickly and accurately within the distribution network and restore services in a shorter period of time. Ironically, certain specious approaches to distribution system and terminal distribution substation "resiliency" do not incorporate robust FRC, do not add a greater number of switches, an

关键词： feeder reconfiguration fault detection isolation and service restoration outage management

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Fixed-Point Back-Propagation Training

Fixed-Point Back-Propagation Training

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ieee/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhang, Xishan Liu, Shaoli Zhang, Rui Liu, Chang Huang, Di Zhou, Shiyi Guo, Jiaming Guo, Qi Du, Zidong Zhi, Tian Chen, Yunji Cambricon Technol Corp Ltd Beijing Peoples R China Chinese Acad Sci State Key Lab Comp Architecture Inst Comp Technol Beijing Peoples R China

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171685

Recent emerged quantization technique (i.e., using low bit-width fixed-point data instead of high bit-width floating-point data) has been applied to inference of deep neural networks for fast and efficient execution. However, directly applying quantization in training can cause significant accuracy loss, thus remaining an open challenge. In this paper;we propose a novel training approach, which applies a layer-wise precision-adaptive quantization in deep neural networks. The new training approach leverages our key insight that the degradation of training accuracy is attributed to the dramatic change of data distribution. Therefore, by keeping the data distribution stable through a layer-wise precision-adaptive quantization, we are able to directly train deep neural networks using low bit-width fixed-point data and achieve guaranteed accuracy, without changing hyper parameters. Experimental results on a wide variety of network architectures (e.g., convolution and recurrent networks) and applications (e.g., image classification, object detection, segmentation and machine translation) show that the proposed approach can train these neural networks with negligible accuracy losses (-1.40%similar to 1.3%, 0.02% on average), and speed up training by 252% on a state-of-the-art Intel CPU.

关键词： Training Quantization (signal) Neural networks Convergence Machine learning network architecture Convolution

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