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International Conference of Young computer Scientists, Engineers and Educators, ICYCSEE 2015

作者： Li, Jia Wang, Changjian Li, Dongsheng Huang, Zhen National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783662462478

Stragglers can temporize jobs and reduce cluster efficiency seriously. Many researches have been contributed to the solution, such as Blacklist[8], speculative execution[1, 6], Dolly[8]. In this paper, we put forward a new approach for mitigating stragglers in MapReduce, name Hummer. It starts task clones only for high-risk delaying tasks. Related experiments have been carried and results show that it can decrease the job delaying risk with fewer resources consumption. For small jobs, Hummer also improves job completion time by 48% and 10% compared to LATE and Dolly. © Springer-Verlag Berlin Heidelberg 2015.

关键词： MapReduce

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Providing information services for wireless sensor networks through cloud computing

Providing information services for wireless sensor networks ...

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2012 7th IEEE Asia-Pacific Services Computing Conference, APSCC 2012

作者： You, Pengfei Peng, Yuxing Gao, Hang National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9780769548975

Wireless sensor networks (WSN) is a critical technology for information gathering covering many areas, including health-care, transportation, air traffic control and environment monitoring. Despite wide use, the fast increasing data emanating from WSN is not fully utilized due to the limitation for structure of WSN itself. Along with the further development of WSN, the data form which is not be efficiently managed and applied to supply information services for users. As the emerging IT technology, cloud computing supplies powerful utilization ability for IT resources, which makes many traditional applications migrate to cloud computing. In this paper, we propose a framework integrating cloud computing paradigm and WSN, which fully uses data process ability and service model for cloud computing. In the framework, data form WSN are efficiently utilized and managed, depending on which, information services for WSN are well provided to users. © 2012 IEEE.

关键词： Virtualization

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A survey on approaches and applications of knowledge representation learning 5

A survey on approaches and applications of knowledge represe...

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5th IEEE International Conference on Data Science in Cyberspace, DSC 2020

作者： Li, Chenchen Li, Aiping Wang, Ye Tu, Hongkui Song, Yichen National University of Defense Technology College of Computer ChangSha China National University of Defense Technology College of Computer Science and Technology on Parallel and Distributed Processing Laboratory ChangSha China

ISBN: (纸本)9781728195582

Knowledge representation learning (KRL) is one of the important research topics in artificial intelligence and Natural language processing. It can efficiently calculate the semantics of entities and relations in a low-dimensional space, and effectively solve the problem of data sparsity, which significantly improve the performance of knowledge acquisition, fusion and reasoning and so on. Starting from the five perspectives of distance-based, semantic matching, bilinear-based, neural network model and additional information model, this paper first introduces the overall framework and specific model design, and then correspondingly introduces the experimental evaluation tasks, metrics and benchmark datasets of each model. On this basis, how to apply KRL to various downstream tasks is summarized. © 2020 IEEE.

关键词： Knowledge representation

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Collaborative search in large-scale unstructured peer-to-peer networks

Collaborative search in large-scale unstructured peer-to-pee...

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36th International Conference on parallel processing in Xi'an, ICPP

作者： Zhang, Yiming Li, Dongsheng Chen, Lei Lu, Xicheng National Laboratory for Parallel and Distributed Processing NUDT Department of Computer Science Hong Kong University of Science and Technology

ISBN: (纸本)076952933X

Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, cOllaborative and Probabilistic search mechanism, in which query messages are viewed as search units to collaborate with each other and aggregate the distributed hints during the search process. A scheme called distributed Bloom Filter (DBF) is presented to propagate the hints with a bandwidth-aware manner, in which a node divides the received Bloom filter vector into subvectors and disseminates the fragments to its neighbors according to their bandwidth capacity. The effectiveness of POP is demonstrated through theoretical analysis and extensive simulations. © 2007 IEEE.

关键词： Bandwidth

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An example-based decoder for spoken language machine translation 6

An example-based decoder for spoken language machine transla...

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6th SIGHAN Workshop on Chinese Language processing, SIGHAN 2008

作者： Li, Zhou-Jun Chao, Wen-Han Chen, Yue-Xin National Laboratory for Parallel and Distributed Processing Changsha China School of Computer Science and Engineering Beihang University China

In this paper, we propose an example-based decoder for a statistical machine translation (SMT) system, which is used for spoken language machine translation. In this way, it will help to solve the re-ordering problem and other problems for spoken language MT, such as lots of omissions, idioms etc. Through experiments, we show that this approach obtains improvements over the baseline on a Chinese-English spoken language translation task. © IJCNLP 2008. All rights reserved.

关键词： Machine translation

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Meeting deadlines for approximation processing in MapReduce environments

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Frontiers of Information Technology & Electronic Engineering 2017年第11期18卷 1754-1772页

作者： Ming-hao HU Chang-jian WANG Yu-xing PENG National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

To provide timely results for big data analytics, it is crucial to satisfy deadline requirements for MapReduce jobs in today＇s production environments. Much effort has been devoted to the problem of meeting deadlines, and typically there exist two kinds of solutions. The first is to allocate appropriate resources to complete the entire job before the specified time limit, where missed deadlines result because of tight deadline constraints or lack of resources; the second is to run a pre-constructed sample based on deadline constraints, which can satisfy the time requirement but fail to maximize the volumes of processed data. In this paper, we propose a deadline-oriented task scheduling approach, named ＇Dart＇, to address the above problem. Given a specified deadline and restricted resources, Dart uses an iterative estimation method, which is based on both historical data and job running status to precisely estimate the real-time job completion time. Based on the estimated time, Dart uses an approach-revise algorithm to make dynamic scheduling decisions for meeting deadlines while maximizing the amount of processed data and mitigating stragglers. Dart also efficiently handles task failures and data skew, protecting its performance from being harmed. We have validated our approach using workloads from OpenCloud and Facebook on a cluster of 64 virtual machines. The results show that Dart can not only effectively meet the deadline but also process near-maximum volumes of data even with tight deadlines and limited resources.

关键词： MapReduce Approximation jobs Deadline Task scheduling Straggler mitigation

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Software ranking and analysis based on mining market requirements and characteristics 15

Software ranking and analysis based on mining market require...

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7th Asia-Pacific Symposium on Internetware, Internetware 2015

作者： Liu, Bingxun Yin, Gang Wang, Tao Zhang, Fang Wang, Huaimin National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781450336413

As the rapid growth of open source software, how to choose software from many alternatives becomes a great challenge. Traditional ranking approaches mainly focus on the characteristics of the software themselves, such as qualities, security, reliable and so on. In this paper we investigate the market demands for software engineers, and propose a novel approach for ranking software by analyzing the market requirements for special software. At the same time we conclude the characteristics of software advertisements and analyze the reasons that why these situations emerge and tendency of software market requirements. As industries always need to balance several different factors for selecting software, the market demands can be a good indicator for ranking software and software evaluating. This paper provides quite a different perspective and some interesting inferences on software market requirements, and it can be a valuable supplement for traditional ranking methods, as well as software evaluating. © 2015 ACM.

关键词： Open source software

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An integration framework of cloud computing with wireless sensor networks

An integration framework of cloud computing with wireless se...

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7th International Conference on Ubiquitous Information Technologies and Applications, CUTE 2012

作者： You, Pengfei Li, Huiba Peng, Yuxing Li, Ziyang National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology 410073 Changsha China

ISBN: (纸本)9789400758568

Wireless sensor networks (WSN) is a key technology extensively applied in many fields, such as transportation, health-care and environment monitoring. Despite rapid development, the exponentially increasing data emanating from WSN is not efficiently stored and used. Besides, the data from multiple different types and locations of WSN needs to be well analyzed, fused and supplied to various types of clients, such as PC, workstation and smart phone. The emerging cloud computing technology provides scalable data process and storage power and some types of connectable services, which can helpfully utilize sensor data from WSN. In this paper, we propose an integration framework of cloud computing with WSN, in which sensor data is transmitted from WSN to cloud, and processed and stored in cloud, then mined and analyzed so as to be supplied to various clients. By applying virtualization and cloud storage technology, and Infrastructure as a Service (IaaS) and Software as a Service (SaaS) of cloud service model, the framework can fully process and store mass sensor data from multiple types of WSN. Besides, it efficiently mines and analyzes sensor data, based on which the data applications are well supplied to various types of clients in form of services. © 2013 Springer Science+Business Media.

关键词： Virtualization

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NVLAN: A Novel VLAN Technology for Scalable Multi-tenant Datacenter Networks 2

NVLAN: A Novel VLAN Technology for Scalable Multi-tenant Dat...

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2nd International Conference on Advanced Cloud and Big Data, CBD 2014

作者： Hu, Yang Li, Huiba Peng, Yuxing Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Computer Science Department China

ISBN: (纸本)9781479980857

Nowadays, cloud providers of 'Infrastructure as a service' require datacenter networks to support virtualization and multi-tenancy at large scale, while it brings a grand challenge to datacenters. Traditional network technologies of datacenters and common commodity devices of network can not meet these new needs. In this paper, we present NVLAN, a novel VLAN technology for scalable multi-tenant datacenter networks. NVLAN eliminates the quantity limitation of logic isolated networks on VLAN through a slight modification. NVLAN can be applied to very large-scale datacenter networks, without the need of expensive and dedicated switches. Through encapsulation of tenant's packets, NVLAN provides tenants with full address space virtualization to configure their own logic network. We implemented NVLAN on a test bed, and demonstrated that it can be scaled up to large numbers of multi-tenant networks with negligible overhead. © 2014 IEEE.

关键词： Virtualization

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Tree-Structured parallel Regeneration for Multiple Data Losses in distributed Storage Systems Based on Erasure Codes

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China Communications 2013年第4期10卷 113-125页

作者：孙伟东王意洁裴晓强 National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology

To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.

关键词： distributed storage system erasure code replication regeneration tree

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