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A Task Allocation Method for Stream Processing with Recovery Latency Constraint

Journal of computer science & Technology 2018年第6期33卷 1125-1139页

作者： Hong-Liang Li Jie Wu Zhen Jiang Xiang Li Xiao-Hui Wei College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer and Information Sciences Temple University Philadelphia PA 19122 U.S.A. Department of Computer Science West Chester University of Pennsylvania West Chester PA 19383 U.S.A.

Stream processing applications continuously process large amounts of online streaming data in real time or nearreal time. They have strict latency constraints. However, the continuous processing makes them vulnerable to any failures,and the recoveries may slow down the entire processing pipeline and break latency constraints. The upstream backupscheme is one of the most widely applied fault-tolerant schemes for stream processing systems. It introduces complexbackup dependencies to tasks, which increases the difficulty of controlling recovery latencies. Moreover, when dependenttasks are located on the same processor, they fail at the same time in processor-level failures, bringing extra recovery latencies that increase the impacts of failures. This paper studies the relationship between the task allocation and therecovery latency of a stream processing application. We present a correlated failure effect model to describe the recoverylatency of a stream topology in processor-level failures under a task allocation plan. We introduce a recovery-latency awaretask allocation problem （RTAP） that seeks task allocation plans for stream topologies that will achieve guaranteed recoverylatencies. We discuss the difference between RTAP and classic task allocation problems and present a heuristic algorithmwith a computational complexity of O（n log2 n） to solve the problem. Extensive experiments were conducted to verify thecorrectness and effectiveness of our approach. It improves the resource usage by 15%-20% on average.

关键词： stream processing task allocation fault-tolerance upstream backup, recovery latency

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Genomic perspective on sociosexual behavior: Quantitative analysis of receptor sequences in vertebrates

Next Research

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Next Research 2025年第2期2卷

作者： Moumita Sil Debaleena Nawn Sk. Sarif Hassan Subhajit Chakraborty Arunava Goswami Pallab Basu Lalith Roopesh Emma Wu Kenneth Lundstrom Vladimir N. Uversky Biological Science Division Indian Statistical Institute 203 B.T Road Kolkata 700108 West Bengal India Department of Computer Science and Engineering Adamas University Adamas Knowledge City Barasat - Barrackpore Road Kolkata 700126 West Bengal India Department of Mathematics Pingla Thana Mahavidyalaya Maligram Paschim Medinipur 721140 West Bengal India School of Physics University of the Witwatersrand Johannesburg Braamfontein 2000 South Africa Department of Molecular Medicine Morsani College of Medicine University of South Florida Tampa FL 33612 USA PanTherapeutics Rte de Lavaux 49 Lutry CH1095 Switzerland

Research has shown that genetics and epigenetics regulate mating behavior across multiple species. Previous studies have generally focused on the signaling pathways involved and spatial distribution of the associated receptors. However a thorough quantitative characterization of the receptors involved may offer deeper insight into mating behavioral patterns. Here oxytocin, arginine-vasopressin 1a, dopamine 1, and dopamine 2 receptors were investigated across 76 vertebrate species. The receptor sequences were characterized by polarity-based randomness, amino acid frequency-based Shannon entropy and Shannon sequence variability, intrinsic protein disorder, binding affinity, stability and pathogenicity of homology-based SNPs, structural and physicochemical features. Hierarchical clustering of species was derived based on structural and physicochemical features of the four receptor sequences separately, which eventually led to proximal relationships among 29 species. Humans were found to be significantly distant phylogenetically from the prairie voles, a representative of monogamous species based on sociosexual behavior. Furthermore, the mouse (polygamous), the prairie deer mouse (polygamous), and the prairie vole (monogamous) although being proximally related (based on quantitative genomics of receptors), differed in their sociosexual behavioral pattern, mostly, due to behavioral epigenetic regulations. This study adds a perspective that receptor genomics does not directly translate to behavioral patterns.

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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Endurable SSD-Based Read Cache for Improving the Performance of Selective Restore from Deduplication Systems

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Journal of computer science & Technology 2018年第1期33卷 58-78页

作者： Jian Liu Yun-Peng Chai Xiao Qin Yao-Hong Liu Division of Computer Science and Engineering Louisiana State University Baton Rouge LA 70803 U.S.A. Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Shelby Center for Engineering Technology Department of Computer Science and Software Engineering Samuel Ginn College of Engineering Auburn University Auburn AL 368~9-53~7 U.S.A.

Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based （i.e., SSD-based） re^d cache cm, be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes （e.g., LRU and LFU） significantly shorten SSDs＇ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution -- LOP-Cache to greatly improve tile write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular （LOP） data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its pertbrmance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs＇ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.

关键词： data deduplication solid state drive （SSD） flash cache endurance

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Using restart heuristics to improve agent performance in angry birds

arXiv

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arXiv 2019年

作者： Liu, Tommy Renz, Jochen Zhang, Peng Stephenson, Matthew Research School of Computer Science Australian National University CanberraACT Australia Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands

Over the past few years the Angry Birds AI competition has been held in an attempt to develop intelligent agents that can successfully and efficiently solve levels for the video game Angry Birds. Many different agents and strategies have been developed to solve the complex and challenging physical reasoning problems associated with such a game. However none of these agents attempt one of the key strategies which humans employ to solve Angry Birds levels, which is restarting levels. Restarting is important in Angry Birds because sometimes the level is no longer solvable or some given shot made has little to no benefit towards the ultimate goal of the game. This paper proposes a framework and experimental evaluation for when to restart levels in Angry Birds. We demonstrate that restarting is a viable strategy to improve agent performance in many cases. Copyright © 2019, The Authors. All rights reserved.

关键词： Birds

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Improved reinforcement learning with curriculum

arXiv

引用

arXiv 2019年

作者： West, Joseph Maire, Frederic Browne, Cameron Denman, Simon School of Electrical Engineering and Computer Science Queensland University of Technology BrisbaneQLD4500 Australia Department of Data Science and Knowledge Engineering Maastricht University Maastricht6211 Netherlands

Humans tend to learn complex abstract concepts faster if examples are presented in a structured manner. For instance, when learning how to play a board game, usually one of the first concepts learned is how the game ends, i.e. the actions that lead to a terminal state (win, lose or draw). The advantage of learning end-games first is that once the actions which lead to a terminal state are understood, it becomes possible to incrementally learn the consequences of actions that are further away from a terminal state - we call this an end-game-first curriculum. Currently the state-of-the-art machine learning player for general board games, AlphaZero by Google DeepMind, does not employ a structured training curriculum;instead learning from the entire game at all times. By employing an end-game-first training curriculum to train an AlphaZero inspired player, we empirically show that the rate of learning of an artificial player can be improved when compared to a player not using a training curriculum. Copyright © 2019, The Authors. All rights reserved.

关键词： Curricula

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SHREC'19 track: Extended 2D scene sketch-based 3D scene retrieval 12

SHREC'19 track: Extended 2D scene sketch-based 3D scene retr...

引用

12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer Graphics, EG 2019

作者： Yuan, Juefei Abdul-Rashid, Hameed Li, Bo Lu, Yijuan Schreck, Tobias Bui, Ngoc-Minh Do, Trong-Le Nguyen, Khac-Tuan Nguyen, Thanh-An Nguyen, Vinh-Tiep Tran, Minh-Triet Wang, Tianyang School of Computing Sciences and Computer Engineering University of Southern Mississippi United States Department of Computer Science Texas State University United States Institute of Computer Graphics and Knowledge Visualization Graz University of Technology Austria Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Software Engineering Lab Vietnam National University Ho Chi Minh City Viet Nam University of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Department of Computer Science and Information Technology Austin Peay State University United States

ISBN: (纸本)9783038680772

Sketch-based 3D scene retrieval is to retrieve 3D scene models given a user's hand-drawn 2D scene sketch. It is a brand new but also very challenging research topic in the field of 3D object retrieval due to the semantic gap in their representations: 3D scene models or views differ from non-realistic 2D scene sketches. To boost this interesting research, we organized a 2D Scene Sketch-Based 3D Scene Retrieval track in SHREC'18, resulting a SceneSBR18 benchmark which contains 10 scene classes. In order to make it more comprehensive, we have extended the number of the scene categories from the initial 10 classes in the SceneSBR2018 benchmark to 30 classes, resulting in a new and more challenging benchmark SceneSBR2019 which has 750 2D scene sketches and 3,000 3D scene models. Therefore, the objective of this track is to further evaluate the performance and scalability of different 2D scene sketch-based 3D scene model retrieval algorithms using this extended and more comprehensive new benchmark. In this track, two groups from USA and Vietnam have successfully submitted 4 runs. Based on 7 commonly used retrieval metrics, we evaluate their retrieval performance. We have also conducted a comprehensive analysis and discussion of these methods and proposed several future research directions to deal with this challenging research topic. Deep learning techniques have been proved their great potentials again in dealing with this challenging retrieval task, in terms of both retrieval accuracy and scalability to a larger dataset. We hope this publicly available benchmark, together with its evaluation results and source code, will further enrich and promote 2D scene sketch-based 3D scene retrieval research area and its corresponding applications. © 2019 The Author(s)

关键词： Scalability

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Additively LWE based homomorphic encryption for compact devices with enhanced security

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International Journal of Network Security 2019年第3期21卷 378-383页

作者： Challa, Ratnakumari Kumari, Gunta Vijaya Department of Computer Science Engineering Rajiv Gandhi University of Knowledge Technologies IIIT-AP RKValley Kadapa Dist Andhra Pradesh India Department of Computer Science Engineering Jawaharlal Nehru Technological University Hyderabad Kukatpally Hyderabad Telangana India

LWE based homomorphic encryption scheme has been proven as secured technique and consequently widely implemented since the last decade. However, the scheme is not considered to be practical because of its larger size of public keys and ciphertexts. In this paper, LWE based additively homomorphic encryption technique is further modified to enhance the performance in minimizing the space required for public keys and ciphertext without compromising the security of the scheme. This makes the scheme suitable for implementation in low space devices. The practical implementation of the scheme is explored and its performance analysis has been presented here. The scheme is also compared with the standard LWE. © 2019, International Journal of Network Security.

关键词： Additives

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Retrospective motion correction of MR images using prior-assisted deep learning

arXiv

引用

arXiv 2020年

作者： Chatterjee, Soumick Sciarra, Alessandro Dünnwald, Max Oeltze-Jafra, Steffen Nürnberger, Andreas Speck, Oliver Department of Biomedical Magnetic Resonance Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke Univeristy Magdeburg Germany MedDigit Department of Neurology Medical Faculty University Hopspital Department of Biomedical Magnetic Resonance Otto-von-Guericke Univeristy Magdeburg Germany MedDigit Department of Neurology Medical Faculty University Hopspital Faculty of Computer Science Otto-von-Guericke Univeristy Magdeburg Germany MedDigit Department of Neurology Medical Faculty University Hopspital German Centre for Neurodegenerative Diseases Center for Behavioral Brain Sciences Magdeburg Germany Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke Univeristy Center for Behavioral Brain Sciences Magdeburg Germany Department of Biomedical Magnetic Resonance Otto-von-Guericke Univeristy German Centre for Neurodegenerative Diseases Leibniz Institute for Neurobiology Center for Behavioral Brain Sciences Magdeburg Germany

In MRI, motion artefacts are among the most common types of artefacts. They can degrade images and render them unusable for accurate diagnosis. Traditional methods, such as prospective or retrospective motion correction, have been proposed to avoid or alleviate motion artefacts. Recently, several other methods based on deep learning approaches have been proposed to solve this problem. This work proposes to enhance the performance of existing deep learning models by the inclusion of additional information present as image priors. The proposed approach has shown promising results and will be further investigated for clinical validity. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Abnormal behaviour detection at traffic junctions using Lucas Kanade and Harris Corner detector 4

Abnormal behaviour detection at traffic junctions using Luca...

引用

4th IEEE International Conference on Recent Advances in Information Technology, RAIT 2018

作者： Jain, Charvi Gautam, Diwakar Department of Computer Science and Engineering Indian Institute of Information Technology UnaHimachal Pradesh India Department of Computer Science and Engineering Sharda University Knowledge Park III Greater NoidaUttar Pradesh India

ISBN: (纸本)9781538630396

Image processing has played a vital role in every aspect of human life. Video surveillance has reached a major out through by the application of advanced image processing and frame modeling techniques. Video surveillance is the most recent issue regarding community security and welfare. Detection of behavior of moving objects in video streams is a vital aspect. In this article, automatic real-time object's behavior detection is implemented using Lucas Kanade and Harris Corner based approach. The velocity of moving element is reported and their association with anomalous activity is also an inseparable part of this art. This work can be used to develop a surveillance system of static camera and robotic automation visual systems. Whenever a new object comes in the camera frame, the system uses the concepts of frame based processing using Lucas Kanade approach incorporated with Harris Corner Detector. In this work, an investigation is carried out to define the optimum value of velocity parameters for declaring a behavior as anomalous. Moreover, it is analyzed that proposed algorithm for video behaviour detection at traffic points perform well but its accuracy can be further enhanced using three dimensional imaging and mapping of moving elements in a hyperspace. © 2018 IEEE.

关键词： Object detection

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