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Proceedings of 2011 IEEE 6th International Symposium on Service Oriented System (SOSE)

作者： Lu Liu Osama Masfary Jianxin Li Distributed and Intelligent Systems Research Group School of Computing and Mathematics University of Derby UK School of Computing Beihang University Beijing China

Service oriented computing (SOC) and cloud computing paradigm has emerged as an approach which enables ubiquitous, on-demand network accesses to a shared pool of flexibly reconfigurable computing resources. The increasing trends of electrical consumption within data centres are a growing concern for business owners as they are quickly becoming a large fraction of the total cost of ownership. There are several challenges and opportunities within a data centre to lower the electrical costs and improve the energy efficiency. Since servers and air conditioners represent the top users of electrical power in the data centre, this research sets out to explore methods from each subsystem of the data centre as part of an overall energy efficient solution. In this paper, we investigate the current trends of Green IT awareness and how the deployment of IT equipment and Site Infrastructure equipment optimization techniques which can offer a solution to a global issue by reducing carbon emissions.

关键词： Servers Power demand Hardware Software Workstations Virtual machine monitors Monitoring

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ANCAEE: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

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Wireless Sensor Network 2011年第9期3卷 307-312页

作者： A. P. Abidoye N. A. Azeez A. O. Adesina K. K. Agbele Wireless Sensor Networks & Natural Language Research Group Grid Computing & Distributed Systems Laboratory Department of Computer Science University of the Western Cape

One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.

关键词： Sensor Nodes Clusters Cluster heads Wireless Sensor Networks Base Station Clustering Algorithms Energy Efficiency

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Rank-SIFT: Learning to rank repeatable local interest points

Rank-SIFT: Learning to rank repeatable local interest points

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作者： Li, Bing Xiao, Rong Li, Zhiwei Cai, Rui Lu, Bao-Liang Zhang, Lei Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Microsoft Research Asia Beijing 100190 China MOE Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781457703942

Scale-invariant feature transform (SIFT) has been well studied in recent years. Most related research efforts focused on designing and learning effective descriptors to characterize a local interest point. However, how to identify stable local interest points is still a very challenging problem. In this paper, we propose a set of differential features, and based on them we adopt a data-driven approach to learn a ranking function to sort local interest points according to their stabilities across images containing the same visual objects. Compared with the handcrafted rule-based method used by the standard SIFT algorithm, our algorithm substantially improves the stability of detected local interest point on a very challenging benchmark dataset, in which images were generated under very different imaging conditions. Experimental results on the Oxford and PASCAL databases further demonstrate the superior performance of the proposed algorithm on both object image retrieval and category recognition. © 2011 IEEE.

关键词： Image retrieval

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Handling drifts and shifts in on-line data streams with evolving fuzzy systems

Handling drifts and shifts in on-line data streams with evol...

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作者： Lughofer, E. Angelov, P. Department of Knowledge-based Mathematical Systems Johannes Kepler University of Linz Altenbergerstrasse 69 A-4040 Linz Austria Intelligent Systems Research Laboratory School of Computing and Communications Lancaster University LA1 4WA United Kingdom

In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact that their structure (rule base and parameters) is not fixed and not pre-determined, but is extracted from data streams on-line and in an incremental manner. When dealing with so-called drifts and s hifts in data streams, one needs to take into account (1) automatic detection of drifts and shifts and (2) automatic reaction to the drifts and shifts. This is important to avoid interruptions in the learning process and downtrends in predictive accuracy. To address the first problem, we propose an approach based on the concept fuzzy rule age. The second problem is addressed by including gradual forgetting of (1) antecedent parts and (2) consequent parameters. The latter can be achieved by including a forgetting factor in the recursive local learning process of the parameters, whose value is automatically extracted based on the intensity of the shift/drift. For addressing the former problem, we introduce two alternative methods: one is based on the evolving density-based clustering (eClustering) used to form the antecedents in the eTS approach;the other is based on the automatic adaptation of the learning rate of the evolving vector quantization (eVQ) method used to form the antecedent in the FLEXFIS approach. The paper concludes with an empirical evaluation of the impact of the proposed approaches in (on-line) real-world data sets in which drifts and shifts occur. © 2010 Elsevier B.V. All rights reserved.

关键词： Fuzzy inference

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Risk, Uncertainty and Possible Worlds

Risk, Uncertainty and Possible Worlds

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IEEE International Conference on and IEEE International Confernece on Social computing (SocialCom) Privacy, Security, Risk and Trust (PASSAT)

作者： Xun Wang Mary-Anne Williams Innovation and Enterprise Research Laboratory Centre of Quantum Computing and Intelligent Systems University of Technology Sydney Australia

Risk is an important and ubiquitous concept that plays a crucial role in decision makings across domains. Risk is also a vague notion that carries different meaning under different domain context and perspectives. This paper aims to provide a formal generalised definition of risk based on the possible world paradigm and expected utility theory and the meanings of risk from both qualitative and quantitative level. This definition of risk is developed from the perspective an intelligent agent or information system. It provides a solid theoretical foundation upon which we can construct an intelligent generalised risk modelling and management framework using techniques from Artificial Intelligence research. This framework can be implemented as an integral part of an information system for better decision support and management of businesses.

关键词： Uncertainty Risk management Reactive power intelligent agents Companies intelligent systems

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Edgel index for large-scale sketch-based image search

Edgel index for large-scale sketch-based image search

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yang Cao Changhu Wang Liqing Zhang Lei Zhang MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University China Microsoft Research Asia Beijing China

Retrieving images to match with a hand-drawn sketch query is a highly desired feature, especially with the popularity of devices with touch screens. Although query-by-sketch has been extensively studied since 1990s, it is still very challenging to build a real-time sketch-based image search engine on a large-scale database due to the lack of effective and efficient matching/indexing solutions. The explosive growth of web images and the phenomenal success of search techniques have encouraged us to revisit this problem and target at solving the problem of web-scale sketch-based image retrieval. In this work, a novel index structure and the corresponding raw contour-based matching algorithm are proposed to calculate the similarity between a sketch query and natural images, and make sketch-based image retrieval scalable to millions of images. The proposed solution simultaneously considers storage cost, retrieval accuracy, and efficiency, based on which we have developed a real-time sketch-based image search engine by indexing more than 2 million images. Extensive experiments on various retrieval tasks (basic shape search, specific image search, and similar image search) show better accuracy and efficiency than state-of-the-art methods.

关键词： Image edge detection Indexing Shape Search problems Search engines

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Learning heterogeneus cooperative linguistic fuzzy rules using local search: Enhancing the COR search space

Learning heterogeneus cooperative linguistic fuzzy rules usi...

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International Conference on intelligent systems Design and Applications (ISDA)

作者： Javier Cózar Luis delaOssa Jose A. Gámez Department of Computing Systems Intelligent Systems and Data Mining Laboratory Albacete Research Institute of Informatics University of Castilla-La Mancha Albacete Spain

The COR methodology allows the learning of Linguistic Fuzzy Rule-Based systems by considering cooperation among rules. In order to do that, COR firstly finds the set of candidate fuzzy rules that can be fired by the examples in the training set, and then uses a search algorithm to find the final set of rules. In the algorithms proposed so far, all candidate rules have the same number of antecedents, which is the number of input variables. However, these rules could be too specific, and rules more generic are not considered. In this paper we study the effect of considering all possible rules, regardless of their number of antecedents. Experiments show that the rule bases obtained use simpler rules, and the results for the error of prediction improve upon those obtained by using classical COR methods.

关键词： Pragmatics Training intelligent systems Cities and towns Input variables Genetic algorithms Cybernetics

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M-MEP:基于多层染色体多基因表达式编程的遗传进化算法

M-MEP:基于多层染色体多基因表达式编程的遗传进化算法

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2012全国高性能计算学术年会

作者： ZHANG Qing-Ke 张庆科 Yang Bo 杨波 Wang Lin 王琳 Zhu Fu-Xiang 朱福祥 Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of JinanJinan 济南大学山东省网络环境智能计算技术重点实验室中国济南 250022 Computer Networks and distributed Systems Laboratory Beijing institute of technologyBeijing100081 北京理工大学计算机学院网络与分布式计算研究所中国北京 10081

本文提出了一种新的基于多层多基因表达式编程的进化算法M-MEP.本算法引入了多层超级染色体概念并采用多层染色体模型对个体进行并行表达，算法在解决函数发现和预测问题中取得了良好的效果.本文的主要贡献：(1)提出了基于多层染色体的... 详细信息

本文提出了一种新的基于多层多基因表达式编程的进化算法M-MEP.本算法引入了多层超级染色体概念并采用多层染色体模型对个体进行并行表达，算法在解决函数发现和预测问题中取得了良好的效果.本文的主要贡献：(1)提出了基于多层染色体的多基因表达式编程算法M-MEP;(2)建立了不同子层染色体内部微基因跨层引用的模型以及多级存储结构;(3)提出了基于二维空间的染色体多元化遗传操作，包括二维交叉操作和二维变异操作.通过三组不同类别的数值分析实验和一组工业应用实验的对比分析结果表明M-MEP算法收敛速度快，进化结果精度高，算法的平均进化代数大幅降低.

关键词：遗传进化算法多基因表达式编程超级染色体微基因跨层引用

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Efficient and sound evaluation when learning Bayesian networks in the space of orderings based on local methods

Efficient and sound evaluation when learning Bayesian networ...

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International Conference on intelligent systems Design and Applications (ISDA)

作者： Juan I. Alonso-Barba Luis delaOssa Jose M. Puerta Department of Computing Systems Intelligent Systems and Data Mining Laboratory Albacete Research Institute of Informatics. University of Castilla-La Mancha Albacete Spain

There are methods that allow building a Bayesian network when an ordering among variables is provided. Based on them, structural learning of Bayesian networks can be carried out by searching for the ordering which generates the best network, instead of directly searching in the space of Directed Acyclic Graphs. In a previous work, a simple Hill-Climbing algorithm defined over the space of orderings was proposed by the authors. Although it achieves competitive results when comparing with the state of the art algorithms, such as GES, it is not very efficient when the number of variables is high. In this work, we propose a more efficient version of the method that improves its scalability in high dimensional domains and is equivalent to the original. We also propose an asymptotically equivalent algorithm based not only on the orderings, but also on the properties of the underlying network. Besides, we prove the correctness of the operations used in both versions, as well as the correctness of the improvements proposed. The algorithms have been tested over a set of different domains, showing that changes introduced lead to significant reductions on execution time, which become more important as the number of variables grows.

关键词： Bayesian methods Algorithm design and analysis intelligent systems Complexity theory Measurement Buildings Heuristic algorithms

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An Innovative Self-Adaptive Configuration Optimization System in Cloud computing

An Innovative Self-Adaptive Configuration Optimization Syste...

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IEEE International Symposium on Dependable, Autonomic and Secure computing (DASC)

作者： Jing Jiang Jie Lu Guangquan Zhang Decision Systems & E-Service Intelligence Research Laboratory Center of Quantum Computing and Intelligent System Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW Australia

Cloud computing has emerging as an extremely popular and cost-effective computational service model using pay-as-you-go executing environments that scale transparently to the user. However, cloud providers should tackle the challenge of configuring their systems to provide maximal performance while minimizing customer's cost of computing resources, which satisfy the customers' various workload requirements. To solve the above challenge, in this paper, we propose an innovative architecture of self-adaptive configuration optimization system which supports dynamic reconfiguration when workloads change. In addition, we develop an optimization algorithm by using genetic algorithm for this system. By using queuing theory and statistic techniques, we model and compute the SLAs metrics which are defined as the fitness function in the optimization algorithm. This optimization system can guide cloud customers to purchase appropriate resources and make decision of deployment configuration such as scale, scheduling and capacity.

关键词： Optimization Computational modeling Cloud computing Throughput Predictive models Measurement Analytical models

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