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IEEE Symposium on Real-Time and Embedded technology and Applications

作者： Xue-Yang Zhu Marc Geilen Twan Basten Sander Stuijk State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Electrical Engineering Eindhovan University of Technology Eindhoven Netherlands

This paper presents an exact method and a heuristic method for static rate-optimal multiprocessor scheduling of real-time multi rate DSP algorithms represented by synchronous data flow graphs (SDFGs). Through exploring the state-space generated by a self-timed execution (STE) of an SDFG, a static rate-optimal schedule via explicit retiming and implicit unfolding can be found by our exact method. By constraining the number of concurrent firings of actors of an STE, the number of processors used in a schedule can be limited. Using this, we present a heuristic method for processor-constrained rate-optimal scheduling of SDFGs. Both methods do not explicitly convert an SDFG to its equivalent homogenous SDFG. Our experimental results show that the exact method gives a significant improvement compared to the existing methods, our heuristic method further reduces the number of processors used.

关键词： Schedules Program processors Delay Digital signal processing Optimal scheduling Processor scheduling Transient analysis

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Bacterial foraging with PSO algorithm and its application on attribute reduction

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International Journal of Innovative Computing and Applications 2012年第2期4卷 100-108页

作者： Zhao, Qingshan Meng, Guoyan Wu, Zhijian Department of Computer Science and Technology Xinzhou Teachers University XinZhou Shanxi Province 034000 China State Key Laboratory of Software Engineering Wuhan University Wuhan Hubei Province 430072 China

Attribute reduction is the important part in rough set theory. Enlightened by bacterial foraging processing, this paper combines the idea of bacterial foraging algorithm with particle swarm optimisation and proposes a new algorithm-BFPSO algorithm. In this algorithm, the chemotaxis of bacterial foraging can guide the particles to evolve towards much better direction, in turn, the convergence speed and optimisation capabilities are increasing by using PSO. The proposed algorithm is applied to the attribute reduction. Experiments show that attribute reduction based on BFPSO algorithm achieve much better result in optimisation capabilities by comparing with other algorithms, and show that the better minimal attribute reduction can been found by the algorithm. Copyright © 2012 Inderscience Enterprises Ltd.

关键词： Rough set theory

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Multiple clustered instance learning for histopathology cancer image classification, segmentation and clustering

Multiple clustered instance learning for histopathology canc...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yan Xu Jun-Yan Zhu Eric Chang Zhuowen Tu State Key Laboratory of Software Development Environment Key Laboratory of Biomechanics and Mechanobiology of Ministry of Education Beihang University China Microsoft Research Asia China Department of Computer Science and Technology Tsinghua University China Laboratory of Neuro Imaging and Department of Computer Science UCLA USA

Cancer tissues in histopathology images exhibit abnormal patterns; it is of great clinical importance to label a histopathology image as having cancerous regions or not and perform the corresponding image segmentation. However, the detailed annotation of cancer cells is often an ambiguous and challenging task. In this paper, we propose a new learning method, multiple clustered instance learning (MCIL), to classify, segment and cluster cancer cells in colon histopathology images. The proposed MCIL method simultaneously performs image-level classification (cancer vs. non-cancer image), pixel-level segmentation (cancer vs. non-cancer tissue), and patch-level clustering (cancer subclasses). We embed the clustering concept into the multiple instance learning (MIL) setting and derive a principled solution to perform the above three tasks in an integrated framework. Experimental results demonstrate the efficiency and effectiveness of MCIL in analyzing colon cancers.

关键词： Cancer Image segmentation Biomedical imaging Colon Boosting Standards Clustering algorithms

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Wielding Statistical Fault Localization Statistically

Wielding Statistical Fault Localization Statistically

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IEEE International Conference on software Reliability Engineering Workshops (ISSRE Wksp)

作者： Yunqian Zhang Lin Chen Bo Jiang Zhenyu Zhang Chinese Academy of Sciences Institute of Software Beijing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science Beihang University Beijing China

ISBN: (纸本)9781467350488

Program debugging is a laborious but necessary phase of software development. It generally consists of fault localization, bug fix, and regression testing. Statistical software fault localization automates the manual and error-prone first task. It predicts fault locations by analyzing dynamic program spectrum captured in program runs. Previous studies mostly focused on how to provide reliable input data to such a technique and how to process the data accurately, but inadequately studied how to wield the output result of such a technique. In this work, we raise the assumption of symmetric distribution on the effectiveness of such a technique in locating faults, based on empirical results. We use maximum likelihood estimate and linear programming to develop a tuning method to enhance the result of a statistical fault localization technique. Experiments with two representative such techniques on two realistic UNIX utility programs validate our assumption and show our method effective.

关键词： Tuning Circuit faults Flexible printed circuits Histograms software Maximum likelihood estimation Complexity theory

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Research of a resource to influence on the software aging and rejuvenation cycle

Research of a resource to influence on the software aging an...

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2012 7th IEEE Conference on Industrial Electronics and Applications, ICIEA 2012

作者： Yang, Tianshe Wu, Qinge Bao, Junpeng State Key Laboratory of Astronautic Dynamics Xi'an Satellite Control Center Xi'an China College of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou China Department of Computer Science and Technology Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9781457721175

This paper studies the aging amount of damnification and the cost of rejuvenation, in order to effectively reduce the average downtime costs of systems at the time of software aging existence, to increase the availability and reliability of system. For the reason that the resource are exhausted to result in attenuation of system performance and decline of processing capacity, this paper will study the memory resource from another point of view, and studies the software rejuvenation time. Moreover, the simulation is given. The simulation results show the optimal rejuvenation time intervals, which can effectively improve the availability of system. © 2012 IEEE.

关键词： Cost functions

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Assessing physical network vulnerability under random line-segment failure model

Assessing physical network vulnerability under random line-s...

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IEEE Workshop on High Performance Switching and Routing

作者： Xiaoliang Wang Xiaohong Jiang Achille Pattavina Sanglu Lu State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China Future University Hokkaido Japan Department of Electronics and Information Politecnico di Milano Milano Italy

The communication network is now one of the critical infrastructures in our society. However, the current communication networks are facing more and more large-scale region failure threats, such as natural disasters (e.g. earthquake, tornado) and physical attacks (e.g. dragging anchors or EMP attack). Therefore, a deep understanding of network behaviors under region failure is essential for the design and maintenance of future highly survivable networks. In this paper, we focus on the network vulnerability assessment under the geographically correlated region failure(s) caused by a random “line-segment” cut, an important region failure model that can efficiently capture the behaviors of some region failures like earthquake, tornado and anchor cutting. To facilitate such vulnerability assessment, we apply the geometrical probability theory to design a grid partition-based estimation scheme for Disrupted Link Capacity, Pairwise Traffic Reduction and Pairwise Disconnection Probability, three commonly used metrics for statistical vulnerability assessment. A theoretical framework is also established to determine a suitable grid partition such that a specified estimation error requirement is satisfied.

关键词： Measurement Zinc Approximation algorithms Routing Needles Estimation error

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Asymptotic throughput for large-scale wireless networks with general node density

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Wireless Networks 2012年第5期19卷 559-575页

作者： Cheng Wang Changjun Jiang Xiang-Yang Li Yunhao Liu Department of Computer Science Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China The Tsinghua National Laboratory for Information Science and Technology (TNLIST) Department of Computer Science and Engineering Tongji University Shanghai China The Department of Computer Science Illinois Institute of Technology Chicago USA The TNLIST and School of Software Tsinghua University Beijing China CSE The Hong Kong University of Science and Technology Kowloon Hong Kong

We study the asymptotic throughput for a large-scale wireless ad hoc network consisting of n nodes under the generalized physical model. We directly compute the throughput of multicast sessions to unify the unicast and broadcast throughputs. We design two multicast schemes based on the so-called ordinary arterial road system and parallel arterial road system, respectively. Correspondingly, we derive the achievable multicast throughput by taking account of all possible cases of n s = ω(1) and 1 ≤ n d ≤ n − 1, rather than only the cases of $$n_s=\Uptheta(n)$$ as in most related works, where n s and n d denote the number of sessions and the number of destinations of each session, respectively. Furthermore, we consider the network with a general node density $$\lambda \in [1,n]$$ , while the models in most related works are either random dense network (RDN) or random extended network (REN) where the density is λ = n and λ = 1, respectively, which further enhances the generality of this work. Particularly, for the special case of our results by letting λ = 1 and $$n_s=\Uptheta(n)$$ , we show that for some regimes of n d , the multicast throughputs achieved by our schemes are better than those derived by the well-known percolation-based schemes.

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Ant colony optimization for enhancing scheduling reliability in wireless sensor networks

Ant colony optimization for enhancing scheduling reliability...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Xiao-Min Hu Jun Zhang Department of Computer Science Key Laboratory of Intelligent Sensor Networks Ministry of Education Key Laboratory of Software Technology Education Department of Guangdong Province Sun Yat-sen University China

In the application of wireless sensor networks (WSNs), energy efficiency is always an important topic for extending the network lifetime. Scheduling the operation modes of sensors can reduce the energy wasted by redundant sensors, but frequent alterations of sensors' modes and different data transmission routes influence the reliability of the WSN. In this paper, a novel algorithm for maximizing the reliable working lifetime of a WSN is proposed. The considered problem restricts the minimum working period of the sensors before changing their operation modes. In order to extend the working lifetime of a reliable WSN, the proposed algorithm adopts the ant colony optimization (ACO) for finding the maximum number of reliable working periods of sensors. The performance of the proposed algorithm has been tested on various WSNs and compared with the state-of-the-art algorithms. The results show that the proposed algorithm can enhance the scheduling reliability of WSNs.

关键词： Sensors Wireless sensor networks Reliability Energy consumption Heuristic algorithms Data communication Approximation algorithms

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Guided mutation operation based on search degree and fitness estimation

Guided mutation operation based on search degree and fitness...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Liang Yin Jun Zhang Department of Computer Science Key Laboratory of Machine Intelligence and Sensor Network Ministry of Education Key Laboratory of Software Technology Education Department of Guangdong Sun Yat-sen University China

Mutation is a fundamental operation in genetic algorithm (GA) for it has a significant impact on global search ability and convergence rate. Traditional mutation operation of GA changes chromosomes randomly (or blindly), which would waste a lot of computational cost in searching less promising regions or those have been searched frequently. To address these drawbacks, this paper proposes a novel guide mutation. The proposed guide mutation makes use of history search experience to estimate the average fitness and search degree of sub-regions in the search space. New chromosomes generated by the guide mutation are more likely to be in regions with higher average fitness and less search degree. In this way, the search efficiency can be improved and the algorithm can have a stronger ability of jumping out of local optima. The proposed guide mutation is incorporated into a simple GA, forming a guided mutation GA (GMGA). The GMGA is validated by testing 23 benchmark functions and the experimental results reveal that the proposed guide mutation is very effective in improving the performance of GA.

关键词： Biological cells Genetic algorithms Convergence Sociology Statistics Equations Mathematical model

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Efficient Median Estimation for RFID Systems

Efficient Median Estimation for RFID Systems

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International Conference on Computing, Measurement, Control and Sensor Network (CMCSN)

作者： Huda El Hag Mustafa Xiaojun Zhu Qun Li Department of Computer Science College of William and Mary Williamsburg VA USA Department of Computer Science University Of Khartoum Sudan State Key Laboratory for Novel Software Technology Nanjing University P. R. China

Radio frequency identification (RFID) tags are used in a lot of applications such as production line and inventory management. Sensors are also a widely adopted wireless technology. This large scale deployment of both RFID technology and sensor technology has opened the door to innovative ways to integrate RFID and sensor technology. Sensor-tags are tags that can report sensed information to an RFID reader. The traditional way to obtain information from tags is to query each tag for its value. This works, however, only for a relatively small number of tags. When the number of tags becomes large it is prohibitive to query one by one due to the high delay. In this paper we present a probabilistic algorithm for estimating the median of a set of RFID tags using binary search. We then evaluate the accuracy and time efficiency of our algorithm.

关键词： Estimation Protocols RFID tags Accuracy Aggregates Algorithm design and analysis

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