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Autonomic Performance and Power Control on Virtualized Servers:Survey, Practices, and Trends

Journal of Computer Science & Technology 2014年第4期29卷 631-645页

作者：周笑波蒋昌俊 IEEE ACM Department of Computer Science University of Colorado Colorado Springs U.S.A. The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University CCF Department of Computer Science and Technology Tongji University

Modern datacenter servers hosting popular Internet services face significant and multi-facet challenges in performance and power control. The user-perceived performance is the result of a complex interaction of complex workloads in a very complex underlying system. Highly dynamic and bursty workloads of Internet services fluctuate over multiple time scales, which has a significant impact on processing and power demands of datacenter servers. High-density servers apply virtualization technology for capacity planning and system manageability. Such virtuMized computer systems are increasingly large and complex. This paper surveys representative approaches to autonomic performance and power control on virtualized servers, which control the quality of service provided by virtualized resources, improve the energy efficiency of the underlying system, and reduce the burden of complex system management from human operators. It then presents three designed self-adaptive resource management techniques based on machine learning and control for percentile-based response time assurance, non-intrusive energy-efficient performance isolation, and joint performance and power guarantee on virtualized servers. The techniques were implemented and evaluated in a testbed of virtualized servers hosting benchmark applications. Finally, two research trends are identified and discussed for sustainable cloud computing in green datacenters.

关键词： autonomic computing joint performance and power control virtualized server Internet application sustainable computing

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New tight upper bounds on the capacity for general deterministic dissemination in wireless ad hoc networks

New tight upper bounds on the capacity for general determini...

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IEEE International Conference on Performance, computing and Communications (IPCCC)

作者： Cheng Wang Jieren Zhou Tianci Liu Lu Shao Huiya Yan Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science Tongji University Shanghai China School of Software Tsinghua University Beijing China Mathematics Department University of Wisconsin-La Crosse La Crosse WI

In this paper, we study capacity scaling laws of the deterministic dissemination (DD) in random wireless networks under the generalized physical model (GphyM). This is truly not a new topic. Our motivation to readdress this issue is two-fold: Firstly, we aim to propose a more general result to unify the network capacity for general homogeneous random models by investigating the impacts of different parameters of the system on the network capacity. Secondly, we target to close the open gaps between the upper and the lower bounds on the network capacity in the literature. We derive the general upper bounds on the capacity for the arbitrary case of (λ, nd, ns) by introducing the Poisson Boolean model of continuum percolation, where λ, nd, and ns are the general node density, the number of destinations for each session, and the number of sessions, respectively. We prove that the derived upper bounds are tight according to the existing general lower bounds constructed in the literature.

关键词： Roads Mathematics Unicast Signal to noise ratio Interference

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Response Policies to Process Module Failure in Single-Arm Cluster Tools Subject to Wafer Residency Time Constraints

Response Policies to Process Module Failure in Single-Arm Cl...

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作者： Qiao, Yan Pan, Chun-Rong Wu, Nai-Qi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou510006 China School of Mechatronics and Electrical Engineering Jiangxi University of Science and Technology Ganzhou341000 China Institute of Systems Engineering Macau University of Science and Technology Taipa China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102-1982 United States

In semiconductor manufacturing, wafer residency time constraints make the scheduling problem of cluster tools complicated. A process module (PM) in cluster tools is prone to failure. It is crucial to deal with any such failure in a proper and timely manner. If there are feasible periodic schedules in operating a cluster tool before and after a PM failure, it is desired to make it operate continuously when such a failure occurs. However, due to wafer residency time constraints, it is highly challenging to control a tool such that it can be correctly transferred from a feasible schedule before failure to another after it. To solve this problem, a Petri net model is developed to describe the dynamic behavior of a single-arm cluster tool and failure response policies are proposed. The proposed policies are formulated via simple control laws for their easy implementation. Examples are given to show them. © 2015 IEEE.

关键词： Scheduling

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Incorporation of Ordinal Optimization into Learning Automata for High Learning Efficiency

Incorporation of Ordinal Optimization into Learning Automata...

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IEEE International Conference on Automation Science and Engineering

作者： JunQi Zhang Cheng Wang Di Zang MengChu Zhou Department of Computer Science and Technology the Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

ISBN: (纸本)9781467381840

Learning automata (LA) represent important leaning mechanisms with applications in automated system design, biological system modeling, computer vision, and transportation. They play the critical roles in modeling a process as well as generating the appropriate signal to control it. They update their action probabilities in accordance with the inputs received from the environment and can improve their own performance during operations. The action probability vector in LA takes charge of two functions: 1) The cost of convergence, i.e., the size of sampling budget;2) The allocation of sampling budget among actions to identify the optimal one. These two intertwined functions lead to a problem: The sampling budget mostly goes to the currently estimated optimal action due to its high action probability regardless whether it can help identify the real optimal action or not. This work proposes a new class of LA that separates the allocation of sampling budget from the action probability vector. It uses the action probability vector to determine the size of sampling budget and then uses Optimal computing Budget Allocation (OCBA) to accomplish the allocation of sampling budget in a way that maximizes the probability of identifying the true optimal action. Simulation results verify its significant speedup ranging from 10.93% to 65.94% over the best existing LA algorithms.

关键词： Convergence Optimization Resource management Learning automata Computational modeling Pursuit algorithms Accuracy

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ADHD Discrimination Based on Social Network

ADHD Discrimination Based on Social Network

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International Conference on Cloud computing and Big Data (CCBD)

作者： Xiaojiao Guo Lianghua He The key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

ISBN: (纸本)9781479966226

Attention Deficit Hyperactivity Disorder (ADHD) is one of the common diseases of brain and has brought the growth of teenagers and even the adult indelible damage. It is very different to classify the ADHD symptoms and normal by the existing research. In this paper, the contributions are as two aspects: one is that the attributes of brain network of the resting state fMRI data have been calculated to discriminate three categories ADHD from the controls. And the average accuracies of various categories are 42.49% and 63.46% on the ADHD-200 datasets of NYU and KKI respectively, which is better than the average best imaging-based diagnostic performance of 35.19% and 61.90% achieved in the ADHD-200 global competition. The other one is that we put forward a new method named G-algorithm to construct the whole brain network, which based on certain rules. The same or even better classification results have been achieved by this method, which also verifies its feasibility and effectiveness.

关键词： Social network services Accuracy Support vector machines Correlation Synchronization Diseases Organizations

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Using estimation of distribution algorithm to coordinate decentralized learning automata for meta-task scheduling

Using estimation of distribution algorithm to coordinate dec...

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Congress on Evolutionary Computation

作者： Jie Li Junqi Zhang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Shanghai CN

Learning automaton (LA) is a reinforcement learning model that aims to determine the optimal action out of a set of actions. It is characterized by updating a selection probability vector through a sequence of repetitive feedback cycles interacting with an environment. Decentralized learning automata (DLAs) consists of many learning automata (LAs) that learn at the same time. Each LA independently selects an action based on its own selection probability vector. In order to provide an appropriate central coordination mechanism in DLAs, this paper proposes a novel decentralized coordination learning automaton (DCLA) using a new selection probability vector which is combined with the probability vectors derived from both LA and estimation of distribution algorithm (EDA). LA contributes to the own learning experience of each LA while EDA estimates the distribution of the whole swarm's promising individuals. Thus, decentralized LAs can be coordinated by EDA using the swarm's comprehensive knowledge. The proposed automaton is applied to solve the real problem of meta-task scheduling in heterogeneous computing system. Extensive experiments demonstrate a superiority of DCLA over other counterpart algorithms. The results show that the proposed DCLA provides an effective and efficient way to coordinate LAs for solving complicated problems.

关键词： Vectors Learning automata Sociology Statistics Processor scheduling Scheduling Estimation

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A framework of video coding for compressing near-duplicate videos

A framework of video coding for compressing near-duplicate v...

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20th Anniversary International Conference on MultiMedia Modeling, MMM 2014

作者： Wang, Hanli Ma, Ming Jiang, Yu-Gang Wei, Zhihua Department of Computer Science and Technology Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China School of Computer Science Fudan University Shanghai China

ISBN: (纸本)9783319041131

With the development of multimedia technique and social network, the amount of videos has grown rapidly, which brings about an increasingly substantial percentage of Near-Duplicate Videos (NDVs). It has been a hot research topic to retrieve NDVs for a number of applications such as copyright detection, Internet video ranking, etc. However, there exist a lot of redundancies in NDVs, and to the best of our knowledge it is an untouched research area on how to efficiently compress NDVs in a joint manner. In this work, a novel video coding framework is proposed to effectively compress NDVs by making full use of the relevance among them. Experimental results demonstrate that a significant storage saving can be achieved by the proposed NDV coding framework. © 2014 Springer International Publishing.

关键词： Video signal processing

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Quasi-synchronization for delayed systems with parameter mismatches via aperiodically intermittent control

Quasi-synchronization for delayed systems with parameter mis...

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International Conference on systems and Informatics (ICSAI)

作者： Xiwei Liu Ping Li Yuan Xu Ying Liu Department of Computer Science and Technology Key Laboratory of Embedded System and Service Computing Shanghai China

ISBN: (纸本)9781479954599

Quasi-synchronization is an important type of synchronization because of the parameter mismatches in the real world, so we will investigate it for a delayed network, which is master-slave coupled. By applying the aperiodically and nonlinearly intermittent control on the network, and assuming the time delay is varying, we will present some useful criteria for exponential quasi-synchronization. The main difference of this paper with previous works is that the intermittent mode is aperiodic while that in previous works is periodic. Finally, simulations are also given to show its validity.

关键词： Synchronization Mathematical model Delay effects Numerical models Observers Equations Educational institutions

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An Efficient and Scalable Algorithm for the Traveling Salesman Problem

An Efficient and Scalable Algorithm for the Traveling Salesm...

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2014 IEEE 5th International Conference on Software Engineering and service Science

作者： Chen Ye Zhongcheng Yang Tianxing Yan Key Laboratory on Embedded System and Service Computing College of Electronics and Information EngineeringTongji University

This paper presents a genetic algorithm based on dynamic programming for solving large-scale instance of the Traveling Salesman Problem(TSP) to ***,an improved dynamic programming algorithm is described to deal with large-scale data,and then it is used as crossover and mutation operator in the genetic *** results show that this novel method with good stability can solve TSP with very-large-scale,effectively reduce the error rate,and improve the solution precision while keeping computational complexity relatively low.

关键词： traveling salesman problem genetic algorithm dynamic programming optimization

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Monitor-based Liveness-enforcing Petri Net Supervisors for Flexible Manufacturing systems 33

Monitor-based Liveness-enforcing Petri Net Supervisors for F...

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第三十三届中国控制会议

作者： YOU Dan WANG Shouguang ZHOU MengChu WU Wenhui School of Information & Electronic Engineering Zhejiang Gongshang University IEEE State Key Laboratory for Manufacturing Systems Engineering Xi’ an Jiaotong University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA

ISBN: (纸本)9781479947249

Deadlocks are a rather undesirable phenomenon in flexible manufacturing systems(FMSs).This work,by adding monitors,develops a deadlock prevention policy for FMSs that can be modeled by a class of Petri nets called-S3 PR ***,an algorithm is given to reduce an S3 PR via *** on it,-resources in-S3 PRs are classified into A--resources and ***,for an-S3 PR with only B--resources,it is proved that a maximally permissive liveness-enforcing supervisor can be designed by M-controlling all the emptied strict minimal siphons(SMSs).For an-S3 PR containing A--resources,a liveness-enforcing supervisor can be designed by iteratively reducing the net via A--resources and adding the corresponding ***,a comprehensive deadlock prevention algorithm for-S3 PRs is *** FMS example is used to illustrate its application.

关键词： Flexible manufacturing system(FMS),Petri nets,deadlock prevention policy,supervisory control

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