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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Yan Liu Yongwei Li Yihong Zhao Xiaoming Chen College of Computer Science and Electronic Engineering Key Laboratory for Embedded and Network Computing of Hunan Province Changsha China

ISBN: (纸本)9781509040940

The increasing scale of multi-core processors are likely to be randomly heterogeneous by design or because of diversity and flaws. The latter type of heterogeneity introduced by some unforeseen variable factors such as the manufacturing process variation is especially challenging because of its unpredictability. In this environment, thread scheduler and global power manager must handle such randomly heterogeneous. Furthermore, these algorithms must supply high efficiency, scalability and low overhead because future multi-core processors may have a number of cores on a single die. This paper presents a variation-aware scheduling algorithm for application scheduling and power management. Thread switching and sampling among different cores in the multi-core processor introduce obvious overhead than previous many-core scheduling algorithms. Proposed scheme records the information of swapped thread of preferential core and uses tabu search-based randomly heterogeneous scheduling algorithm(TSR) to avoid the occurrence of repeated sampling and reduce the migration frequency and sampling frequency of a thread. The experimental results show that TSR algorithm has decreased 45.7% of thread migration and 42.2% of the sampling time as compared with local search algorithm. This paper regards the transcendental Hungarian offline scheduling algorithm as the baseline. ED2 of TSR only decrease by 8.58% as compared with that of Hungarian offline scheduling algorithm, but compared with the random search scheduling algorithm, ED2 of TSR decreased by 39.4%.

关键词： Scheduling algorithms Scheduling Multicore processing Algorithm design and analysis Heuristic algorithms Optimal scheduling Schedules

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Security-aware Signal Packing Algorithm for CAN-based Automotive Cyber-physical Systems

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IEEE/CAA Journal of Automatica Sinica 2015年第4期2卷 422-430页

作者： Yong Xie Liangjiao Liu Renfa Li Jianqiang Hu Yong Han Xin Peng Key Laboratory for Application Technology of Internet of Things of Fujian Educational Bureau Xiamen University of Technology Key Laboratory of Embedded and Networking Computing of Hunan Province Hunan University Key Laboratory on Complex Systems Optimization & Controlling of Hunan High Education Institutions Hunan Institute of Science and Technology

Network and software integration pose severe challenges in cyber-security for controller area network (CAN)-based automotive cyber-physical system (ACPS), therefore we employ message authentication code (MAC) to defend CAN against masquerade attack, but the consequent bandwidth overhead makes it a necessity to find the tradeoff among security, real-time and bandwidth utilization for signal packing problem (SPP) of CAN. A mixed-security signal model is firstly proposed to formally describe the properties and requirements on security and real-time for signals, and then a mixed-integer linear programming (MILP) formulation of SPP security-aware signal packing (SASP) is implemented to solve the tradeoff problem, where the bandwidth utilization is improved and the requirements in both security and real-time are met. Experiments based on both society of automotive engineers (SAE) standard signal set and simulated signal set showed the effectiveness of SASP by comparing with the state-of-the-art algorithm. © 2014 Chinese Association of Automation.

关键词： Algorithms Bandwidth Communication channels (information theory) Control system synthesis embedded systems Integer programming

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Minimizing Schedule Length of Energy Consumption Constrained Parallel Applications on Heterogeneous Distributed Systems

Minimizing Schedule Length of Energy Consumption Constrained...

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Xiongren Xiao Guoqi Xie Renfa Li Keqin Li College of Computer Science and Electronic Engineering Hunan University China Key Laboratory for Embedded and Network Computing of Hunan Province China Department of Computer Science State University of New York USA

ISBN: (纸本)9781509032068

Energy consumption is one of the primary design constraints in heterogeneous parallel and distributed systems ranging from small embedded devices to large-scale data centers. The problem of minimizing schedule length of an energy consumption constrained parallel application has been studied recently in homogeneous systems with shared memory. To adapt the heterogeneity and distribution of high-performance computing systems, this study solves the problem of minimizing schedule length of an energy consumption constrained parallel application on heterogeneous distributed systems based on dynamic voltage and frequency scaling (DVFS) energy-efficient design technique. Such problem is decomposed into two sub-problems in this study, namely, satisfying energy consumption constraint and minimizing schedule length. The first sub-problem is solved by transferring the energy consumption constraint of the application to that of each task, and the second sub-problem is solved by heuristically scheduling each task with low time complexity. Experiments with Fast Fourier transform parallel applications show that not only the actual energy consumptions always do not exceed and are close to given energy consumption constraints, but also the minimum schedule lengths are generated by using the proposed algorithm.

关键词： Energy consumption Program processors Schedules Time-frequency analysis Processor scheduling Optimization Job shop scheduling

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An Improved algorithm of parameters reconfiguration in cognitive radio networks using ant colony optimization

An Improved algorithm of parameters reconfiguration in cogni...

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2015 3rd International Conference on Manufacturing Engineering and Technology for Manufacturing Growth(METMG 2015)

作者： Shaoyuan Liu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University

Recent years, cognitive radio techniques have becoming a promising solution to tackle the bottleneck of spectrum scarcity. As an essential characteristics for CRN, the cognitive parameter reconfiguration can automatically adjust the parameters to meet the user demands and adapt to the timevarying environment. However parameter reconfiguration and complex environment cognition are still challenging due to their need for high speed parallel computation and multi-objects optimization. In this aspect, ant colony optimization(ACO) technique, as an intelligent technology to solve the complex issues, is introduced to the reconfiguration process to achieve the assignment. The goal of this paper is to present a parameters reconfiguration scenario using ACO with a comprehensive fitness function for reconfiguration decision making with regard to the multiple and complex objectives. Finally, series of results have demonstrated the stability and validity of the ACO based reconfiguration algorithm in CRN.

关键词： ACO simulation An Improved algorithm of parameters reconfiguration in cognitive radio networks using ant colony optimization

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Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio Networks with Energy Harvesting

Multi-Users Cooperative Spectrum Sensing in Distributed Cogn...

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2nd International Conference on Simulation and Modeling Methodologies,Technologies and Applications(SMTA 2015)

作者： H.Wang F.Z.Zeng Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University

In this paper we propose an improved sensing scheme in cognitive radio networks, which allows the secondary users to utilize the spectrum of primary users when these resources are not being used currently. We first apply multi-user cooperative spectrum sensing in cognitive radio networks to improve both energy efficiency and spectrum utility. Secondly, we investigate the energy harvesting communication model. Finally, we analysis the probability of the proposed spectrum sensing scheme, and obtain an optimal solution under the scenarios of non-energy harvesting scheme and energy harvesting scheme respectively. The simulation results demonstrate the high performance of our proposed scheme.

关键词： Multi-Users Cooperative Spectrum Sensing in Distributed Cognitive Radio Networks with Energy Harvesting Radio

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A novel energy efficient cooperative spectrum sensing scheme for cognitive radio sensor network based on evolutionary game

A novel energy efficient cooperative spectrum sensing scheme...

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IEEE Workshop on Local and Metropolitan Area Networks (LANMAN)

作者： Xiaolong Ma Fanzi Zeng Jisheng Xu Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China

ISBN: (纸本)9781467367639

In this paper, we focused on how to get CRs collaborate effectively as well as maximize energy savings in cognitive radio sensor network. We have established a model of evolutionary game between a cognitive sensors. In order to let cognitive sensors sense spectrum effectively, we designed a contribution-punishment mechanism, which can stimulate high SNR sensors to participate in spectrum sensing. Additionally, in order to reduce the wasted energy of sensors in idle, we introduced periodic sleep-listen mechanism. Finally, we simulated behavior dynamics for a 6-player polymorphic population game and compared our proposed scheme with non-periodic sleep-listen mechanism scheme. Result shows that our proposed scheme can stimulate high SNR sensors to participate in spectrum sensing effectively and can make the system more energy efficient.

关键词： Sensors Signal to noise ratio Games Sociology Statistics Energy consumption Energy efficiency

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Sensor data fusion based on an improved dempaster-shafer evidence theory in vehicular cyber-physical systems

Sensor data fusion based on an improved dempaster-shafer evi...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： Mengmeng Ma Jiyao An Zhong Huang Zhangbao Cao Key Laboratory of Embedded and Network Computing of Hunan Province Hunan University Changsha PR China

ISBN: (纸本)9781479977895

In Vehicular Cyber-Physical Systems (VCPS), the collected sensor data are always uncertain and conflicting. Dempster-Shafer (DS) evidence theory can effectively deal with uncertain information, but the Dempster's rule may produce counter-intuitive results when the information is conflicting. This paper proposed an improved approach for combining conflicting evidence with different weighting factors based on a novel dissimilarity measure. Firstly, a new dissimilarity measure mixing fuzzy nearness with the introduced correlation coefficient is proposed to characterize the divergence degree between two basic probability assignments (BPAs). Then, the weighting factors are developed by using the proposed dissimilarity measure. Finally, the Dempster's rule is chose to combine the revised sources. Simulation experiment shows that the improved method can effectively solve the problem of sensor data fusion in VCPS with better convergence performance.

关键词： Cyber-physical systems Yttrium Real-time systems Weight measurement Data integration Correlation coefficient Reliability

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Online object tracking based on local sparse representation in a Bayesian inference framewo

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Journal of Computational Information Systems 2015年第11期11卷 3919-3928页

作者： Liu, Zekun Xu, Cheng Key Laboratory for Embedded Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Changsha China

Significant research has been devoted to object tracking. Most existing algorithms can track the object well in the controlled environment. However, they may fail in the presence of drastic appearance changes or complex environment variation. In the paper, for robustness object tracking, we proposed an algorithm based on the local sparse representation. Different from most of the traditional object representation which only consider the holistic representation, in our proposed algorithm, the image patch of the object is represented sparsely in the form of a linear combination of dictionary elements constructed online to deal with the target appearance changes. And the aim of the object tracking is posed as a binary classification problem. A linear classifier is learned for discriminate the object target from the background. Furthermore, we combine them in a Bayesian inference framework. To alleviate the tracking drift, we proposed a two-stage particle filtering method. Experiments on several benchmark video sequences has demonstrate that our proposed algorithm performs favorably contrasted with other several state-of-art algorithms. ©, 2015, Binary Information Press. All right reserved.

关键词： Bayesian networks

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On Efficient Feature Ranking Methods for High-Throughput Data Analysis

On Efficient Feature Ranking Methods for High-Throughput Dat...

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作者： Liao, Bo Jiang, Yan Liang, Wei Peng, Lihong Peng, Li Hanyurwimfura, Damien Li, Zejun Chen, Min Key Laboratory for Embedded and Network Computing of Hunan Province College of Information Science and Engineering Hunan University Changsha Hunan410082 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China Department of Computer Science and Engineering Changsha Medical University Changsha Hunan410219 China

Efficient mining of high-throughput data has become one of the popular themes in the big data era. Existing biology-related feature ranking methods mainly focus on statistical and annotation information. In this study, two efficient feature ranking methods are presented. Multi-target regression and graph embedding are incorporated in an optimization framework, and feature ranking is achieved by introducing structured sparsity norm. Unlike existing methods, the presented methods have two advantages: (1) the feature subset simultaneously account for global margin information as well as locality manifold information. Consequently, both global and locality information are considered. (2) Features are selected by batch rather than individually in the algorithm framework. Thus, the interactions between features are considered and the optimal feature subset can be guaranteed. In addition, this study presents a theoretical justification. Empirical experiments demonstrate the effectiveness and efficiency of the two algorithms in comparison with some state-of-the-art feature ranking methods through a set of real-world gene expression data sets. © 2015 IEEE.

关键词： Convex optimization

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Duplication based energy aware scheduling algorithm in heterogeneous many-core system-on-chip

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Journal of Computational Information Systems 2015年第8期11卷 2981-2988页

作者： Liu, Yan An, Mengmeng Chen, Xiaoming Key Laboratory for Embedded and Network Computing of Hunan Province Hunan University Changsha China College of Computer National University of Defense Technology Changsha China

With the rapid development of semiconductor technology, hundreds of processor cores can be integrated into a single chip, known as "many-core system-on-chip". For the problem that performance and power consumption are equally important in heterogeneous many-core system-on-chip, this paper proposes an duplication based energy aware task scheduling algorithm, which balances the relationship between task scheduling time and energy consumption. Simulation experimental results show that the proposed algorithm can reduce the completion time and energy consumption, and leverage the relationship between them effectively. ©, 2015, Binary Information Press. All right reserved.

关键词： System-on-chip

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