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IEEE Secure Development (IEEE SecDev) Conference

作者： Yavuz, Tuba Bai, Ken (Yihang) Univ Florida ECE Dept Gainesville FL 32611 USA

ISBN: (纸本)9781728183886

Analyzing real-world software is challenging due to complexity of the software frameworks or APIs they depend on. In this paper, we present a tool, PROMPT, that facilitates analysis of software components using programming model guided symbolic execution. PROMPT has a specification component, PROSE, that lets users define a programming model, which consists of a set of data constraints and life-cycle rules that define control-flow constraints among sequentially composed API functions. Given a PROSE model and a software component, PROMPT symbolically executes the component while enforcing the specified programming model. PROMPT has been implemented on top of the KLEE symbolic execution engine and has been applied to Linux device drivers from the video, sound, and network subsystems. PROMPT detected two new and two known memory vulnerabilities in some of the device drivers. The proposed tutorial on PROMPT will empower practitioners as well as researchers in analyzing components of system code for deep memory vulnerabilities.

关键词： symbolic execution memory vulnerabilities component-level analysis programming model

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Accessible Near -Storage Computing with FPGAs 20

Accessible Near -Storage Computing with FPGAs

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15th European Conference on Computer Systems (EuroSys)

作者： Schmid, Robert Plauth, Max Wenzel, Lukas Eberhardt, Felix Polze, Andreas Univ Potsdam Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9781450368827

Data transfers impose a major bottleneck in heterogenous system architectures. As a mitigation strategy, compute resources can be introduced in places where data occurs naturally. The increased diversity of compute resources in turn affects programming models and practicalities of software development for near-data compute kernels and raises the question of how those resources can be made accessible to users and applications. We introduce the Metal FS framework to improve the accessibility of FPGA-based near-storage accelerators: Firstly, we present a near-storage-compute-aware file system that enables self-contained, reusable compute kernels to operate on the granularity of file data streams. Secondly, we provide an integrated build process for FPGA overlay images that starts with the acquisition of compute kernels through a package manager and finally allows to dynamically configure near-storage compute pipelines consisting of them. Thirdly, we integrate the framework into Linux as a file system driver and repurpose UNIX Pipes as a well-known operating system primitive to orchestrate near -storage compute pipelines.

关键词： Near -Storage Computing Near -Data Processing FPGA programming model Data -Flow Paradigm

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programming the CLEARSY Safety Platform with B 7th

Programming the CLEARSY Safety Platform with B

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7th International Conference on Rigorous State-Based Methods (ABZ)

作者： Lecomte, Thierry ClearSy 320 Ave Archimede Aix En Provence France

ISBN: (纸本)9783030480769;9783030480776

The CLEARSY Safety Platform (CSSP) is aimed at easing the development and the deployment of safety critical applications, up to the safety integrity level 4 (SIL4). It relies on the smart integration of the B formal method, redundant code generation and compilation, and a hardware platform that ensures a safe execution of the software. This paper exposes the programming model of the CSSP used to develop control & command applications based on digital I/Os.

关键词： B method Safety critical programming model

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X-Centric: A Survey on Compute-, Memory- and Application-Centric Computer Architectures

X-Centric: A Survey on Compute-, Memory- and Application-Cen...

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International Symposium on Memory Systems (MEMSYS)

作者： Rheindt, Sven Sabirov, Temur Lenke, Oliver Wild, Thomas Herkersdorf, Andreas Tech Univ Munich Munich Germany

ISBN: (纸本)9781450388993

Big Data and machine learning constitute the multifaceted challenge of computer engineering in the past decade. The meaningful processing of vast amounts of unstructured data from a myriad of sensors and devices is a complicated endeavor already. Aggravated by the need to enter the extremely power- and resource-constrained pocket-size mobile domain, the computing as we know it is rapidly evolving. Data-centric in- and near-memory computing, as well as highly heterogeneous accelerator-equipped application-centric architectures, are on the rise to tackle the unsatisfiable demand for evermore compute performance and efficiency. To learn from these innovations, this paper surveys compute-, memory-, and application-centric architectures and related programming paradigms and analyzes prominent chances and challenges. The key insights from the particular domains are: 1) The high nominal processing performance of compute-centric systems is thwarted by massively decreasing data-to-task locality and increased data movement. Nevertheless, the commodity of shared-memory programming and the presence of widespread legacy applications keep this domain alive. 2) Memory-centric designs help to mitigate the data locality wall and significantly improve power and performance efficiency. However, a memory-centric programming paradigm is still missing. 3) Heterogeneity, customization, and established ecosystems (like for mobile devices) enable application-centric optimization under often tight thermal, power, and resource constraints. However, a holistic SoC-level design approach is required to utilize and program the diversity of processing units in different application domains efficiently. A one-size-fits-all architecture approach seems not in sight because of the wide diversity in domain-specific requirements and constraints. Therefore, established ecosystems, 3D-stacked logic-enhanced memory devices, and commoditized architecture-aware programming models seem fundamental for perform

关键词： computer architecture programming model architecture evolution memory-centric application-centric near-memory computing survey roofline model heterogeneous architecture mobile device

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A new procedure for hesitant multiplicative preference relations

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2019年第5期34卷 819-857页

作者： Meng, Fanyong Tang, Jie An, Qingxian Chen, Xiaohong Cent S Univ Sch Business Changsha 410083 Hunan Peoples R China Nanjing Univ Informat Sci & Technol Sch Management Sci & Engn Nanjing Jiangsu Peoples R China Univ Technol Troyes Charles Delaunay Inst Ind Syst Optimizat Lab Troyes France Hunan Univ Commerce Sch Accounting Changsha Hunan Peoples R China

Hesitant information is powerful and flexible to denote decision maker's judgments. Hesitant multiplicative preference relations (HMPRs) own the advantages of preference relations and hesitant fuzzy sets that permit the decision makers (DMs) to compare objects by using several values. Just as other types of preference relations, how to derive the priority weight vector is a crucial step. According to the principle of the consistency concept for multiplicative preference relations, this paper first introduces a new consistency concept for HMPRs, which avoids the disadvantages of the previous ones. Using the new concept, models to judge the consistency of HMPRs are built. Then, a consistency probability-based method to derive the hesitant fuzzy priority weight vector from HMPRs is offered. Considering the incomplete case, consistency-based programming models to determine the missing values are constructed. To address group decision making with HMPRs, a distance measure is defined to determine the weights of the DMs, and a consensus index is proposed. Then, a consistency and consensus-based group decision-making algorithm is performed. Finally, two practical examples, an investment problem and a water conservancy problem are offered to illustrate the feasibility and efficiency of the new algorithm. Comparison analysis from the numerical and theoretical aspects verifies the potential application of the new procedure.

关键词： consensus consistency group decision making hesitant multiplicative preference relation programming model

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Consistency-Based Algorithms for Decision-Making With Interval Fuzzy Preference Relations

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2019年第10期27卷 2052-2066页

作者： Meng, Fan-Yong Tang, Jie Fujita, Hamido Cent S Univ Sch Business Changsha 410083 Hunan Peoples R China Nanjing Univ Informat Sci & Technol Sch Management & Econ Nanjing 210044 Jiangsu Peoples R China Cent S Univ Business Sch Changsha 410083 Hunan Peoples R China Iwate Prefectural Univ Takizawa 0200693 Japan

This paper reviews and analyzes several consistency concepts for interval fuzzy preference relations (IFPRs). On the basis of the comparisons, one can find that Krejs additive and multiplicative consistency concepts are more reasonable and flexible. Considering the issues that previous methods cannot fully address regarding incomplete and inconsistent IFPRs, this paper studies incomplete and inconsistent IFPRs using custom programming models based on Krejs concepts. Meanwhile, programming models for judging the additive and multiplicative consistency of IFPRs are constructed, respectively. Considering the consensus of IFPRs in group decision-making, a consensus index is defined, and programming models for improving the consensus levels of individual IFPRs are built. On the basis of the consistency and consensus analysis, two consistency-based algorithms for group decision-making with inconsistent and incomplete IFPRs are offered. One method is based on Krejs additive consistency concept, and the other uses Krejs multiplicative consistency concept. Meanwhile, associated examples are provided to show the application of the new methods.

关键词： Additives Decision making programming Biological system modeling Indexes Finite element analysis Additive and multiplicative consistency consensus decision-making IFPR programming model

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Towards Energy-Efficient Heterogeneous Multicore Architectures for Edge Computing

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IEEE ACCESS 2019年 7卷 49474-49491页

作者： Gamatie, Abdoulaye Devic, Guillaume Sassatelli, Gilles Bernabovi, Stefano Naudin, Philippe Chapman, Michael Univ Montpellier LIRMM CNRS F-34095 Montpellier France Cortus SA Co F-34130 Mauguio France

In recent years, the edge computing paradigm has been attracting much attention in the Internet-of-Things domain. It aims to push the frontier of computing applications, data, and services away from the usually centralized cloud servers to the boundary of the network. The benefits of this paradigm shift include better reactivity and reliability, reduced data transfer costs toward the centralized cloud servers, and enhanced confidentiality. The design of energy-efficient edge compute nodes requires, among others, low power cores such as microprocessors. Heterogeneous architectures are key solutions to address the crucial energy-efficiency demand in modern systems. They combine various processors providing attractive power and performance trade-offs. Unfortunately, no standard heterogeneous microcontroller-based architecture exists for edge computing. This paper deals with the aforementioned issue by exploring typical low power architectures for edge computing. Various heterogeneous multicore designs are developed and prototyped on FPGA for unbiased evaluation. These designs rely on cost-effective and inherently ultra-low power cores commercialized by Cortus SA, a world-leading semiconductor IP company in the embedded ultra-low power microcontroller domain. Some microarchitecture-level design considerations, e.g.,floating point and out-of-order computing capabilities, are taken into account for exploring candidate solutions. In addition, a tailored and flexible multi-task programming model is defined for the proposed architecture paradigm. We analyze the behavior of various application programs on available core configurations. This provides valuable insights on the best architecture setups that match program characteristics, so as to enable increased energy-efficiency. Our experiments on multi-benchmark programs show that on average 22% energy gain can be achieved (up to 45%) compared to a reference system design, i.e., a system with the same execution architecture,

关键词： Edge computing energy-efficiency heterogeneous multicore architectures programming model embedded systems

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Linguistic intuitionistic fuzzy preference relations and their application to multi-criteria decision making

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INFORMATION FUSION 2019年 46卷 77-90页

作者： Meng Fanyong Tang Jie Fujita, Hamido Cent South Univ Sch Business Changsha 410083 Peoples R China Iwate Prefectural Univ Takizawa Iwate Japan Nanjing Audit Univ Sch Int Audit Nanjing 211815 Jiangsu Peoples R China

Linguistic intuitionistic fuzzy sets can be regarded as a qualitative form of intuitionistic fuzzy sets. This type of fuzzy sets uses a linguistic membership degree and a linguistic non-membership degree to represent the qualitative preferred and non-preferred judgments of decision makers. Preference relation is a useful and efficient tool for decision making that only requires the decision makers to compare two objects at one time. Taking the advantages of linguistic intuitionistic fuzzy sets and preference relations, this paper introduces linguistic intuitionistic fuzzy preference relations (LIFPRs) and studies their application to decision making. To ensure the ranking of objects reasonably, an additive consistency concept is introduced, and several of its desirable properties are discussed. To cope with inconsistent and incomplete LIFPRs, programming model-based methods to derive additively consistent LIFPRs and determine missing values are constructed, respectively. Subsequently, an approach to multi-criteria decision making with LIFPRs is offered, and the application of the new approach is illustrated by using a decision-making problem about evaluating mobile phones.

关键词： Multi-criteria decision making Linguistic intuitionistic fuzzy preference relation Additive consistency programming model

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Deriving priority weights from intuitionistic fuzzy multiplicative preference relations

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INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS 2019年第11期34卷 2937-2969页

作者： Meng, Fanyong Tang, Jie Xu, Zeshui Beijing Wuzi Univ Sch Informat Beijing 101149 Peoples R China Cent S Univ Sch Business Changsha Hunan Peoples R China Sichuan Univ Business Sch Chengdu Sichuan Peoples R China

Intuitionistic fuzzy multiplicative preference relations (IFMPRs), as an extension of multiplicative preference relations, can denote the decision-makers' (DMs') preferred and nonpreferred degrees simultaneously. Just as any other type of preference relations, consistency is crucial to guarantee the rational ranking orders. Thus, this paper introduces a new consistent concept for IFMPRs that is a natural extension of crisp case and overcomes the issues in the previous concepts of consistency. To judge the consistency of IFMPRs, several programming models are constructed, and an approach to deriving completely consistent IFMPRs is presented. Considering incomplete case, consistency-based models are built to determine missing values that can address incomplete IFMPRs with the ignored objects, namely, all information for them is unknown. After that, group decision-making with IFMPRs is studied. To measure the agreement degree between the DMs' individual IFMPRs, a new consensus index is defined, and an interactive algorithm to improve the consensus is offered. Based on the consistency and consensus analysis, a new method to group decision-making with IFMPRs is developed. Finally, case studies are offered to show the application of the new procedure and to compare it with previous methods.

关键词： consensus consistency group decision-making IFMPR programming model

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Consensus building for hesitant fuzzy preference relations with multiplicative consistency

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 128卷 387-400页

作者： Li, Jian Wang, Jian-qiang Hu, Jun-hua Cent S Univ Sch Business Changsha 410083 Hunan Peoples R China Guangxi Univ Sch XingJian Coll Sci & Liberal Arts Nanning 530005 Guangxi Peoples R China

Considering that consensus is an essential part of a group decision-making process, this study focuses on building consensus for hesitant fuzzy preference relations (HFPRs) with multiplicative consistency. To achieve this goal, firstly, a new multiplicative consistency concept for the HFPR is proposed. The main feature of the proposed multiplicative consistency concept is that this concept considers all information provided by decision makers and does not require normalising the HFPR. Secondly, several programming models are constructed to verify the complete multiplicative consistency of the HFPR. If the HFPR fails to demonstrate a complete multiplicative consistency, then a multiplicative consistency index is proposed to measure its consistency degree. Simultaneously, an algorithm is introduced to improve the multiplicative consistency degree. Thirdly, an algorithm is designed to derive priority weight vectors from the HFPR. The proposed algorithm addresses the situation in which the HFPR exhibits not only a complete multiplicative consistency but also an acceptable multiplicative consistency. Fourthly, a consensus measure index based on extraction priority weight vectors is introduced. Concurrently, several programming models are constructed to achieve the expected consensus level. Finally, to illustrate the effectiveness of the proposed method, an example is provided, and comparative studies with several existing methods are presented.

关键词： Group decision-making Consensus Hesitant fuzzy preference relation Multiplicative consistency programming model

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