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

作者： Tian-Liang Huang Tian-An Hsieh Kuan-Chou Lai Kuan-Ching Li Ching-Hsien Hsu Hsi-Ya Chang Department of Computer and Information Science National Taichung University Taichung Taiwan Department of Computer Science and Information Engineering Providence University Taichung Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan National Center of High-Performance Computing Hsinchu Taiwan

The robust availability of resources in distributed computing environments is a very important issue. In general, the resources are distributed among geographical distributed sites resulting in the higher failure probability. Therefore, this paper proposes a fault tolerance policy on dynamic load balancing in P2P grids to improve the dynamic availability of resources. This proposed policy duplicates jobs in different computing nodes to avoid job or hardware failure. In the meantime, the proposed fault tolerance policy also considers the load balancing among different computing nodes while keeping the stable job turnaround time. Therefore, the proposed policy could improve the system performance in a varying environment. Experimental results show that the proposed policy could achieve a better job completion rate as the failure rate increases.

关键词： Peer to peer computing Fault tolerance Fault tolerant systems Load management Benchmark testing Protocols

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Malware behavioral analysis system: TWMAN

Malware behavioral analysis system: TWMAN

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IEEE Symposium on Intelligent Agents, IA

作者： Hsien-De Huang Chang-Shing Lee Hung-Yu Kao Yi-Lang Tsai Jee-Gong Chang National Center of High-Performance Computing National Applied Research Laboratories Tainan Taiwan Department Computer Science and Information Engineering National University of Tainan Tainan Taiwan Department Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

Malware is an important topic of security threat research. In this paper, a behavioral malware analysis system TWMAN was presented. This study focuses on using real operation system (OS) environment to analysis malware behavioral. Many researchers try to use virtual machine (VM) system to monitor the malware behaviors. These malware samples will only compromise the virtual operating system or virtual machine, which cannot reflect in the real operating system or real environment. Therefore, some malware researchers don't want their systems to be analyzed in VM environment, because the analyzer cannot much useful information in VM environment. There are many Anti-VM techniques which are used to ward off the collection, analysis, and reverse engineering features of the VM based malware analysis platform. There are differences between these two behaviors: malware behavior in real environment and in virtual environment. Therefore, malware researcher would get inaccurate analysis results from VM based malware analysis platform. In order to retrieve correct malware behavioral information, we need flexible, adaptable, and quickly analysis environment, which could discovery malware behavioral in real operation system environment, and which can quickly restore clear operation system to analysis another malware sample. For this reason, this study developed Taiwan Malware Analysis Net(TWMAN), a real operation system environment for malware behavioral analysis and analysis report. We believe this system would be helpful to improve the correctness of malware analysis result and reduce the loss rate of malware analysis.

关键词： Malware IP networks Internet Software Forensics Image restoration

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Energy-Aware Task Consolidation Technique for Cloud computing

Energy-Aware Task Consolidation Technique for Cloud Computin...

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IEEE International Conference on Cloud computing Technology and science (CloudCom)

作者： Ching-Hsien Hsu Shih-Chang Chen Chih-Chun Lee Hsi-Ya Chang Kuan-Chou Lai Kuan-Ching Li Chunming Rong Department Computer Science & Information Engineering Chung Hua University Hsinchu Taiwan Department Computer Science National Tsing Hua University Hsinchu Taiwan National Center of High-performance Computing Hsinchu Taiwan Department Computer and Information Science National Taichung University Taichung Taiwan Department Computer Science & Information Engineering Providence University Taichung Taiwan Department Computer Science University of Stavanger Norway

Task consolidation is a way of maximizing cloud computing resource, which brings many benefits such as better use of resources, rationalization of maintenance, IT service customization, QoS and reliable services, etc. However, maximizing resource utilization does not mean efficient energy usage. Many literature show that energy consumption and resource utilization in clouds are highly coupled. Some research works aim to decrease resource utilization for saving energy while some try to find the balance between resource utilization and energy consumption. In this paper, an energy-aware task consolidation (ETC) technique is presented aims to optimize energy consumption of virtual clusters in cloud data center. Conforming most cloud systems, a 70% principle of CPU utilization is proposed to manage task consolidation among virtual clusters. The simulation results show that ETC can significantly reduce power consumption in managing task consolidation for cloud systems. Up to 17% improvement as compare to a recent work in [10] that aims to maximize resource utilization can be obtained.

关键词： Energy consumption Virtual machining Loading Power demand Passive optical networks Servers

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Some recent progress on curvilinear imagers and eyeball cameras

Some recent progress on curvilinear imagers and eyeball came...

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Imaging Systems and Applications, ISA 2011

作者： Jung, Inhwa Xiao, Jianliang Malyarchuk, Viktor Lu, Chaofeng Li, Ming Liu, Zhuangjian Yoon, Jongseung Huang, Yonggang Rogers, John A. Department of Materials Science and Engineering Beckman Institute for Advanced Science and Technology Frederick Seitz Materials Research Laboratory University of Illinois at Urbana-Champaign Urbana IL 61801 United States Department of Civil Engineering Zhejiang University Hangzhou Zhejiang 310058 China Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 United States State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of Technology Dalian 116024 China Institute of High Performance Computing 1 Fusionopolis Way #16-16 Connexis 138632 Singapore Department of Mechanical Engineering Northwestern University Evanston IL 60208 United States

We present curvilinear imagers using photodetector arrays on elastomeric membranes, capable of reversible deformation into hemispherical shapes via hydraulics. Combining with tunable, fluidic plano-convex lenses yield... 详细信息

ISBN: (纸本)9781557529145

关键词： Arrays Detector arrays Image quality Photodetectors Thin films Zoom lenses

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Flexible Electronics: Imbricate Scales as a Design Construct for Microsystem Technologies (Small 6/2012)

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Small 2012年第6期8卷

作者： Seok Kim Yewang Su Agustin Mihi Seungwoo Lee Zhuangjian Liu Tanmay K. Bhandakkar Jian Wu Joseph B. Geddes III Harley T. Johnson Yongwei Zhang Jung-Ki Park Paul V. Braun Yonggang Huang John A. Rogers Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign 1206 West Green Street Urbana IL 61801 USA Department of Civil and Environmental Engineering Department of Mechanical Engineering Northwestern University 2145 Sheridan Road Evanston IL 61208 USA Department of Materials Science and Engineering Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 1304 West Green Street Urbana IL 61801 USA Department of Chemical and Biomolecular Engineering Korea Advanced Institute of Science and Technology 373-1 Guseong-dong Yuseong-gu Daejeon 305-701 Republic of Korea Institute of High Performance Computing Fusionopolis Way #16-16 Connexis 138632 Singapore Department of Engineering Mechanics Tsinghua University Beijing 100084 China Department of Materials Science and Engineering Frederick Seitz Materials Research Laboratory Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 1304 West Green Street Urbana IL 61801 USA

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Parallel performance Measurement of Heterogeneous Parallel Systems with GPUs

Parallel Performance Measurement of Heterogeneous Parallel S...

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International Conference on Parallel Processing (ICPP)

作者： Allen D. Malony Scott Biersdorff Sameer Shende Heike Jagode Stanimire Tomov Guido Juckeland Robert Dietrich Duncan Poole Christopher Lamb Department of Computer and Information Science University of Oregon Eugene USA Innovative Computing Laboratory (ICL) University of Tennessee Knoxville USA Center of Information Services and High Performance Computing (ZIH) Technische Universität Dresden Germany NVIDIA Corporation Santa Clara CA USA

The power of GPUs is giving rise to heterogeneous parallel computing, with new demands on programming environments, runtime systems, and tools to deliver high-performing applications. This paper studies the problems associated with performance measurement of heterogeneous machines with GPUs. A heterogeneous computation model and alternative host-GPU measurement approaches are discussed to set the stage for reporting new capabilities for heterogeneous parallel performance measurement in three leading HPC tools: PAPI, Vampir, and the TAU performance System. Our work leverages the new CUPTI tool support in NVIDIA's CUDA device library. Heterogeneous benchmarks from the SHOC suite are used to demonstrate the measurement methods and tool support.

关键词： Graphics processing unit Kernel performance evaluation Libraries Hardware Radiation detectors

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Topology design and performance analysis for networked earth observing small satellites

Topology design and performance analysis for networked earth...

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MILCOM, Military Communications Conference

作者： Paul Muri Janise McNair Joe Antoon Ann Gordon-Ross Kathryn Cason Norman Fitz-Coy Wireless and Mobile (WAM) Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville FL USA NSF Center of High Performance Reconfigurable Computing (CHREC) Department of Electrical and Computer Engineering University of Florida Gainesville FL USA Space Systems Group (SSG) Department of Mechanical and AeroSpace Engineering University of Florida Gainesville FL USA

In order to network small satellite constellations for Earth observation and communication, several limitations must be addressed, including distributed topology management, slow down-link data-rates, and single point-to-point communication. Since distributed satellite constellations exacerbate the severity of these limitations, thorough analysis of a constellation's network performance is required to ensure that task objectives are achievable. In this paper, we designed network topologies using Satellite Toolkit (STK) for two low Earth orbit (LEO) Earth observing small satellite constellations: a sun-synchronous repeating ground track constellation and a flower (an elliptical repeating ground track) constellation. Both constellations include six sink satellites that provide a high speed down-link relay point to a ground station. We compared the constellations' inter-satellite links and down-links with respect to network metrics including access window time, drop-ratio, and throughput. We evaluated these network metrics using the Network Simulator (ns-2). Though previous works have proposed sun-synchronous and flower small satellite constellations for Earth observation, these constellations have not been analyzed for these network metrics. Results show that the sun-synchronous constellation with a repeating ground track outperforms the flower constellation with respect to more access time, lower drop-ratio, and higher throughput. Additionally, our simulations determined the optimum media access control slot time and packet transmission intervals for long distance satellite links. Further, our method of designing satellite constellation topologies in STK and exporting them to ns-2 can be used for future studies on any desired constellation network performance evaluations.

关键词： Satellites Satellite broadcasting Orbits Earth Satellite constellations Databases Mobile communication

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Distributed Power and Rate Allocation with Fairness for Cognitive Radios in Wireless Ad Hoc Networks

Distributed Power and Rate Allocation with Fairness for Cogn...

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2011 IEEE Global Telecommunications Conference - GLOBECOM 2011

作者： Songtao Guo Yunqiang Zhang Yuanyuan Yang High Performance Networking Research Center State Key Laboratory of Power Transmission Equipment and System Security College of Computer Science Chongqing University Chongqing China Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY USA

In this paper, we propose a distributed resource allocation framework for cognitive radio networks by using the orthogonal frequency division multiple access (OFDMA) modulation. We jointly consider the constraints of quality of service (QoS), maximum power, and minimum rates in the network to obtain optimal available subcarrier sets and transmission power. The fairness of resource allocation is guaranteed by incorporating the probability that a subcarrier is occupied into the link capacity expression. We present a distributed subcarrier selection and power allocation algorithm and evaluate the algorithm through simulations. Our results confirm that the proposed algorithm outperforms the existing algorithms in terms of throughput, the number of secondary links admitted, and the fairness of resource allocation.

关键词： Resource management Optimization Cognitive radio Ad hoc networks Interference Throughput Joints

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Implementation of an RFID-based biological sample identification and tracking system

Implementation of an RFID-based biological sample identifica...

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IEEE International Conference on RFID-Technology and Applications (RFID-TA)

作者： Atieh Zarabzadeh Farzad Hayati R. William G. Watson Geoff Bradley Jane Grimson Centre for Health Informatics Department of Computer Science Trinity College Dublin Ireland Department of Electronic Electrical & Computer Engineering University of Birmingham UK UCD School of Medicine and Medical Science UCD Conway Institute of Biomolecular & Biomedical Research University College Dublin Ireland Trinity Centre for High Performance Computing Trinity College Dublin Ireland

Collection, processing, storage and maintenance of samples to facilitate long-term cohort studies in biobanks, requires a system to manage samples in an effective way to prevent sample mix up and loss. Sample identification and tracking system aims to reserve data on the samples at all the times, hence RFID technology is employed. This technology allows information to be stored on the tags attached to tubes containing samples. A system is proposed, designed and prototype in the Prostate Cancer Research Consortium biobank.

关键词： Radiofrequency identification Databases Zigbee Electron tubes Biology Educational institutions Memory management

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An Energy-Efficient Kernel Framework for Large-Scale Data Modeling and Classification

An Energy-Efficient Kernel Framework for Large-Scale Data Mo...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Paul D. Yoo Jason W.P. Ng Albert Y. Zomaya Department Computer Engineering Etisalat British Telecom (BT) Innovation Centre Khalifa University of Science Technology and Research Abu Dhabi UAE Centre of Distributed and High Performance Computing School of Information Technologies (J12) University of Sydney NSW Australia

Energy-efficient computing has now become a key challenge not only for data-center operations, but also for many other energy-driven systems, with the focus on reducing of all energy-related costs, and operational expenses, as well as its corresponding and environmental impacts. Intelligent machine-learning systems are typically performance driven. For instance, most non-parametric model-free approaches are often known to require high computational cost in order to find the global optima. Designing more accurate machine-learning systems to satisfy the market needs will hence lead to a higher likelihood of energy waste due to the increased computational cost. This paper thus introduces an energy-efficient framework for large-scale data modeling and classification. It can achieve a test error comparable to or better than the state-of-the-art machine-learning models, while at the same time, maintaining a low computational cost when dealing with large-scale data. The effectiveness of the proposed approaches has been demonstrated by our experiments with two large-scale KDD datasets: Mtv-1 and Mtv-2.

关键词： Electromyography Machine learning Energy efficiency Distributed processing

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