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作者： Liu, Yang Ma, Chenxiao Xu, Lixiong Shen, Xiaodong Li, Maozhen Li, Pengcheng School of Electrical Engineering and Information Sichuan University Chengdu610065 China Department of Electronic and Computer Engineering Brunel University London UxbridgeUB8 3PH United Kingdom Key Laboratory of Embedded Systems and Service Computing Ministry of Education Tongji University Shanghai200092 China State Grid Shanxi Electric Power Company Xi'an710048 China

Gene expression programming (GEP) algorithm is one of the most effective function mining algorithms in enabling the mathematical equation fitting for the input dataset. However, GEP algorithm encounters low efficiency issue in big data processing due to large overhead in its evolution when it handles the large-scale data. In order to solve the issue, this paper presents two parallelized GEP algorithms using MapReduce. Based on data separation, the first algorithm aims at speeding up the large-scale classification. However, it is lack of ability to output the mined equation explicitly. Therefore, based on the further improvements of the first algorithm, the second parallelized GEP algorithm aims at mining the equation efficiently and also outputs the equation explicitly and directly. The experimental results show that both algorithms are effective for processing large volume of data. © 2017 John Wiley & Sons, Ltd.

关键词： MapReduce

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Short-term load forecasting for electric vehicle charging stations based on time series distance measuring

Short-term load forecasting for electric vehicle charging st...

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IEEE International Conference on Electronic Measurement & Instruments

作者： Shi Xin Qiu Lei Tian Li Liang Miaozhu Yi Lizheng College of Automation Chongqing University Chongqing China MOE Key Laboratory of Service Computing in Cyber Physical Society Chongqing China State Grid Chongqing Electric Power Company Chongqing China

To improve the efficiency and the precision of short-term load forecasting of the electric vehicle charging stations, this paper proposed a new algorithm for short - term load forecasting for electric vehicle charging stations based on time series distance measuring. Applying the editing distance to load the load sequence into the load segment and the time segment respectively to measure, so as to measure the distance between the load sequences accurately, And simplify the complexity of model which can improve the efficiency of prediction. Based on the actual historical load data of electric vehicle charging stations, the simulation analysis is given to verify that the proposed method has high prediction efficiency and accuracy.

关键词： Electric Vehicle Charging Station Short-term load forecasting Edit Distance Time Series distance measuring

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A User-Centric Approach to Activity Recognition and Guidance in Semantic Smart Home

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China Communications 2015年第S2期12卷 103-113页

作者： LI Haitao GUO Kun LU Yueming LI Yonghua South China University of Technology Guangdong Power Grid Co. Ltd Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

Wireless smart home system is to facilitate people's lives and it trend to adopt a more intelligent way to provide services. It is very desirable in the recent SH market for the system to recognize users' behaviors and automatically response the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually defined separately through knowledge-driven methods. These approaches cause that the activity models can't be matched with the services dynamically. To address the problem, we develop the semantic association model and a novel approach of activity recognition and guidance is presented. In our approach, the smart devices and users' requirements are described by semantic models. When the requirements are detected and understood, smart gateway can provide appropriate services, achieving activity assistance. The semantic association model allows all related elements in smart home connect with each other logically. The approach has been implemented and the results show that the success rate of the approach based on semantic association model is higher than 33% at average as compared to the approach based on predefined models. The proposed approach can effectively help people who are in trouble with learning or remembering in the common life.

关键词： Internet of Things smart home activity recognition activity guidance semantic model

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Some classes of complete permutation polynomials over Fq

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Science China Mathematics 2015年第10期58卷 2081-2094页

作者： WU GaoFei LI Nian HELLESETH Tor ZHANG YuQing State Key Laboratory of Integrated Service Networks Xidian University Information Security and National Computing Grid Laboratory Southwest Jiaotong University Department of Informatics University of Bergen National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences

By using a powerful criterion for permutation polynomials, we give several classes of complete permutation polynomials over finite fields. First, two classes of complete permutation monomials whose exponents are of Niho type are presented. Second, for any odd prime p, we give a sufficient and necessary condition for a-1xdto be a complete permutation polynomial over Fp4 k, where d =(p4k-1)/(pk-1)+ 1 and a ∈ F*p4k. Finally, we present a class of complete permutation multinomials, which is a generalization of recent work.

关键词： finite field complete permutation polynomials Walsh transform Niho exponents Dickson polynomials

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System Level Power Characterization of Multi-core Computers with Dynamic Frequency Scaling Support

System Level Power Characterization of Multi-core Computers ...

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IEEE International Conference on Cluster computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Congfeng Jiang Grid and Service Computing Technology Laboratory Hangzhou Dianzi University Hangzhou China

Multi-core architecture has become prominent in modern processors including personal computers, large scale server systems and embedded systems. While multi core processors provide higher computing performance, they have higher power density and also consume more energy than traditional single core processors. Therefore, Dynamic Frequency Scaling (DFS) is mostly implemented in multi-core processors in order to reduce power and energy consumptions. However, the built-in dynamic frequency scaling ability in processors is not enough for highly dynamic and mixed workloads including computing intensive and I/O intensive computing workloads. In this paper we conducted extensive experiments to characterize the processor utilization, power consumption, and application performance. We provide the experiment results and observations. We found that: (1) There is no power model that is capable for different computing systems, even for the same workloads. (2) Processor utilization is not always the indicator for power consumption. For example, in some scenarios such as mixed type and I/O intensive applications, the power consumption is not proportional to the processor utilization and even keeps approximately unchanged. (3) Different computing systems with different subsystems configurations, i.e., processors, memories, and disks, have different power curves due to their proportion in total system-level power consumption because these different subsystems consume different basic power and dynamic power when running different workloads.

关键词： Energy consumption Time frequency analysis Program processors Power demand Multicore processing Computational modeling Hardware

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Resource Allocation in Contending Virtualized Environments through VM Performance Modeling and Feedback

Resource Allocation in Contending Virtualized Environments t...

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Chinagrid Annual Conference (Chinagrid)

作者： Congfeng Jiang Xianghua Xu Jilin Zhang Yunfa Li Jian Wan Grid and Service Computing Technology Laboratory Hangzhou Dianzi University Hangzhou China

With active deployment of virtualization in large scale data centers and cloud computing environments, allocation and scheduling of virtual and physical resources raise more challenges and may have negative impacts on system performance due to: (1) the isolation between the guest Virtual Machines (VMs) and the Virtual Machines Monitor (VMM), and (2) the independent and even conflicting operations between multiple VMs. In this paper a stochastic model of resources in virtualized environments is proposed and resource allocation and scheduling algorithm are proposed to provide performance guarantees and service differentiation in contending conditions. In the proposed algorithm user behavior and workloads are characterized through the historical and real time performance profiling and estimation from hosted agents within individual VMs. The resources are allocated according to the demand as well as the performance of the targeted VMs based on the Suffer age aggregation and performance feedback. Experiments on a real Xen based virtualization environment with 3 VMs are conducted and evaluated for accuracy, efficiency, sensitivity, and overhead. The results show that the performance feedback based allocation can achieve a higher SLA satisfaction rate as 97.5%, a lower load imbalance index as 17.6%. The results also show that this algorithm is valid, effective and scalable for implementation in real virtualized environments.

关键词： Resource management Time factors Stochastic processes Accuracy Indexes Real time systems Estimation

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Java Multi Threaded Based Parallel Remote Sensing Image Interpretation in Desktop grid

Java Multi Threaded Based Parallel Remote Sensing Image Inte...

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Chinagrid Annual Conference (Chinagrid)

作者： Congfeng Jiang Xianghua Xu Jian Wan Jilin Zhang Yunfa Li Grid and Service Computing Technology Laboratory Hangzhou Dianzi University Hangzhou China

Typical remote sensing image interpretation consists of large number of long-lived independent computation jobs such as calibration, correction, and transformation and computation. These time consuming jobs are suitable for execution in desktop grid with high performance commodity PCs for its lower cost and high management ability. In this paper, a framework of parallel remote sensing image interpretation in desktop grid is proposed. The framework consists of modules such as job partitioning and scheduling, load balancing, communication, and image processing. We also provided an implementation based on java multi threaded programming. The computation results on real application of soil moisture estimation workload show that the average speedup is 6.1 in a 9-node heterogeneous desktop grid environment and failure rate of jobs is less than 5.6%.

关键词： Remote sensing Monitoring Processor scheduling Resource management Program processors Java Image processing

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Power Aware Resource Allocation in Virtualized Environments through VM Behavior Identification

Power Aware Resource Allocation in Virtualized Environments ...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social computing (CPSCom) Green computing and Communications (GreenCom)

作者： Congfeng Jiang Jilin Zhang Jian Wan Xianghua Xu Yuyu Yin Ritai Yu Changping Lv Grid and Service Computing Technology Laboratory Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781424497799

Virtualization technology enables server and service consolidation to save more power and operational costs of large scale computing systems. However, the consolidation nature of virtualization intensifies the power densities in a rack, thus resulting in higher probability of failures and service Level Agreements violations under constrained power budget. In this paper, we proposed a power aware resource allocation algorithm, named PaRA, to coordinate and tradeoff the power and performance. In order to provide enough information about power characteristics of individual VM and applications, we use agent for workload characterization and estimation. The real actuation of resource allocation is realized within the Virtual Machines Monitor (VMM). We evaluated our algorithm on a real Xen based virtualization environments with 3 VMs. The results show that the proposed approach can achieve a higher SLA satisfaction rate as 99.6 percent in RUBiS web application, and power consumption savings up to 17.6 percent compared to default Xen resource allocator. The results also show the potential of our algorithm to be used in real virtualization environments.

关键词： Resource management Power demand Hardware Estimation Servers Power measurement Adaptation model

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An Event Based GUI Programming Toolkit for Embedded System

An Event Based GUI Programming Toolkit for Embedded System

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IEEE Asia-Pacific Conference on services computing (APSCC)

作者： Xu Hu Congfeng Jiang Wei Zhang Jilin Zhang Ritai Yu Changping Lv Grid and Service Computing Technology Laboratory Hangzhou Dianzi University Hangzhou China

Due to various differences in hardware architectures of devices in ubiquitous computing systems, portability and platform-independency become the main challenge for graphics programming in system design. In this paper, we propose an adaptive user interface programming toolkit for system design in ubiquitous computing environment. The toolkit leverages an existing system software infrastructure, making the application programming straightforward and platform independent. This proposed toolkit can be divided into two parts: the first part consists of open source cross-platform graphics libraries which are encapsulated into the platform dependent part of backend library for interacting with specific system. While another one, called core library, is responsible for the functions of control logics, graphics drawing and backend management. To demonstrate the practical use of this toolkit and its portability, a case study is provided for demonstration. The test results on three different embedded systems show its good adaptability on multi-platforms.

关键词： Libraries Graphical user interfaces Graphics Mice Programming Operating systems

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CantorSim: Simplifying Acceleration of Micro-architecture Simulations

CantorSim: Simplifying Acceleration of Micro-architecture Si...

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International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)

作者： Zhibin Yu Hai Jin Jian Chen Lizy K. John Service Computing Technology and System Laboratory Cluster and Grid Computing Laboratory Huazhong University of Science and Technology Wuhan China Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

Many techniques have been developed to accelerate micro-architecture simulation since it is becoming increasingly urgent as the complexity of workloads and simulated processors increases. However, most of popular techniques need profiles or trial simulations to determine parameters before real simulations. When the number of dynamic instructions of workloads such as SPEC CPU2006 is huge, the profiles or trial simulations often take a long time. What's worse, any changes of benchmarks need to repeat the above work. This paper proposes a novel approach based on fractals to solve this problem. It employs the generation procedure of trisection Cantor Set, a classic fractal, to select instructions simulated in detail. We implement a simulator named CantorSim using the trisection Cantor fractal approach. The simulator is evaluated with benchmark programs from SPEC CPU2000 and SPEC CPU2006. We show that our approach is micro-architecture independent as the same parameter value for a single program yields similar results on processors with different configurations. The unified analytical model used to determine sampling parameters for different benchmarks indicates the proposed approach can save a lot of time for preparing parameters. On the other hand, for SPEC CPU2000 and SPEC CPU2006, CantorSim is slightly faster than SMARTSim. The validated average CPI relative errors of the SPEC CPU2000 and SPEC CPU2006 are 3.2% and 2.2% respectively. Therefore, our proposed approach can simplify acceleration of simulations significantly without sacrificing speed and accuracy.

关键词： Fractals Benchmark testing Acceleration Computational modeling Accuracy Predictive models Program processors

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