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Congress on Evolutionary Computation

作者： Lishan Kang Zhuo Kang Yan Li Pu Liu Yuping Chen State Key Laboratory of Parallel and Distributed Processing State Key Laboratory of Software Engineering Wuhan University of China Wuhan China

Recently Tao Guo (1999) proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the subspace search method (a general multi-parent recombination strategy) with the population hill-climbing method. The former keeps a global search for the overall situation, and the latter maintains the convergence of the algorithm. Guo's algorithm has many advantages, such as the simplicity of its structure, the high accuracy of its results, the wide range of its applications, and the robustness of its use. In this paper a preliminary theoretical analysis of the algorithm is given and some numerical experiments are performed using Guo's algorithm to demonstrate the theoretical results. Three asynchronous parallel algorithms with different granularities for MIMD machines are designed by parallelizing Guo's algorithm.

关键词： Algorithm design and analysis parallel algorithms Constraint optimization Software algorithms Optimization methods Laboratories Design optimization distributed processing Software engineering Electronic mail

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iRank: Supporting Proximity Ranking for Peer-to-Peer Applications

iRank: Supporting Proximity Ranking for Peer-to-Peer Applica...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yongquan Fu Yijie Wang National Key Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology China

Proximity ranking according to end-to-end network distances (e.g., Round-Trip Time, RTT) can reveal detailed proximity information, which is important in network management and performance diagnosis in distributed systems. However, to the best of our knowledge, there has been no similar work on this subject in the P2P computing field. We present a distributed rating method iRank, that enables proximity rankings by providing discrete ratings in a distributed manner. It formulates the proximity ranking as a rating problem that faithfully captures the proximity based on noisy distance measurements scalably and practically. The primary challenge in inferring proximity rankings is enforcing distributed ratings with complex rating policies. Our solution is based on reconstructing ratings by decomposing a centralized rating method Maximum Margin Matrix Factorization (MMMF) into independent sub-problems, that can be efficiently solved in a decentralized manner. By relaxing the dependence on infrastructure nodes that are a single point of failure and limit scalability, iRank can gracefully handle network churns. Through real network latency data sets, we demonstrate that iRank can predict ratings with low distortion, which are smaller than 20 percentage worse than the centralized method, in the context of synthetic complex rating policies.

关键词： Peer to peer computing distributed computing Computer networks Network servers Application software Laboratories distributed processing Concurrent computing Computer network management Conference management

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Routing with uncertainty in wireless mesh networks

Routing with uncertainty in wireless mesh networks

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2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010

作者： Chen, Fajun Liu, Jiangchuan Li, Zongpeng Wang, Yijie Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer National University of Defense Technology China School of Computing Science Simon Fraser University Canada Department of Computer Science University of Caglary Canada

ISBN: (纸本)9781424459889

Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the transient link uncertainties at PHY and MAC layers, a pseudo-deterministic routing protocol that relies on average or historic statistics can hardly explore the full potentials of a multi-hop wireless mesh. We study optimal WMN routing using probing-based online anypath forwarding, with explicit consideration of transient link uncertainties. We show the underlying connection between WMN routing and the classic Canadian Traveller Problem (CTP) [1]. Inspired by a stochastic recoverable version of CTP (SRCTP), we develop a practical SRCTP-based online routing algorithm under link uncertainties. We study how dynamic next hop selection can be done with low cost, and derive a systematic selection order for minimizing transmission delay. We conduct simulation studies to verify the effectiveness of the SRCTP algorithms under diverse network configurations. In particular, compared to deterministic routing, reduction of end-to-end delay (51:15∼73:02%) and improvement on packet delivery ratio (99:76%) are observed.

关键词： Routing protocols

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Random Walk Based Inverse Influence Research in Online Social Networks

Random Walk Based Inverse Influence Research in Online Socia...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Zhaoyan Jin Quanyuan Wu Dianxi Shi Huining Yan National Key Laboratory for Parallel and Distributed Processing NUDT Changsha Hunan P.R.China

ISBN: (纸本)9781479909735

In online social networks, social influence of a user reflects his or her reputation or importance in the whole network or to a personalized user. Social influence analysis can be used in many real applications, such as link prediction, friend recommendation and personalized searching. Personalized Page Rank, which ranks nodes according to the probabilities that a random walk starting from a personalized node stops at all nodes, is one of the most popular metrics for influence analysis. In this paper, we study the problem of inverse influence in online social networks. Different from Personalized Page Rank, the inverse influence for a personalized node ranks nodes according to the probabilities that all nodes stop at the personalized node in limited steps. We propose two computation models for inverse influence, i.e., the random walk based and the path based. Both of the models have high computation complexity, and cannot be used in large graphs, so we propose a Monte Carlo based approximation algorithm. Experiments from synthetic and real world datasets show that, our algorithm has equivalent or even better accuracy than related researches in link prediction, and thus can be used in friend recommendation in online social networks.

关键词： Prediction algorithms Social network services Equations Mathematical model Accuracy Approximation algorithms Measurement

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AUModel:A Conceptual model for Adaptive Software

AUModel:A Conceptual model for Adaptive Software

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

作者： Hui Liu Bo Ding Dianxi Shi Huaimin Wang National Key Laboratory for Parallel and Distributed Processing College of Computer ScienceNational University of Defense Technology

Pervasive software should be able to adapt itself to the changing environments and user ***,it will bring great challenges to the software engineering *** paper proposes AUModel,a conceptual model for adaptive software,which takes adaptability as an inherent feature and can act as the foundation of the engineering *** introducing AUModel,the reuse of software adaptation infrastructure as well as the separation of adaptation concerns are enabled,which can facilitate both the development and maintenance of adaptive *** paper also presents our initial attempts to realize this model,including a middleware prototype to support this model and an application to validate its effectiveness.

关键词： pervasive computing adaptive software middleware

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Using redundant threads for fault tolerance of OpenMP programs

Using redundant threads for fault tolerance of OpenMP progra...

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2010 International Conference in Information Science and Applications, ICISA 2010

作者： Fu, Hongyi Ding, Yan Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing National University of Defence Tech. Changsha Hunan 410073 China School of Computer National University of Defence Tech. Changsha Hunan 410073 China

ISBN: (纸本)9781424459438

As the wide application of multi-core processor architecture in the domain of high performance computing, fault tolerance for shared memory parallel programs becomes a hot spot of research. For years, checkpointing has been the dominant fault tolerance technology in this field, and recently, many research works have been engaged with it. However, to those programs which deal with large amount of data, checkpointing may induce massive I/O transfer, which will adversely affect scalability. To deal with such a problem, this paper proposes a fault tolerance approach, making use of redundancy, for shared memory parallel programs. Our scheme avoids saving and restoring computational state during the program's execution, hence does not involve I/O operations, so presents explicit advantage over checkpointing in scalability. In this paper, we introduce our approach and the related compiler tool in detail, and give the experimental evaluation result. ©2010 IEEE.

关键词： Fault tolerance

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Security issues and solutions in cloud computing

Security issues and solutions in cloud computing

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32nd IEEE International Conference on distributed Computing Systems Workshops, ICDCSW 2012

作者： You, Pengfei Peng, Yuxing Liu, Weidong Xue, Shoufu National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha China Jiangsu Automation Research Institute Jiangsu China Air Defense Forces Academy CPLA Zhengzhou Henan China

ISBN: (纸本)9781467314237

Recently, Cloud computing, as one of the hottest words in IT world, has drawn great attention. Many IT companies such as IBM, Google, Amazon, Microsoft, Yahoo and others vigorously develop cloud computing systems and related products to customers. However, there are still some difficulties for customers to adopt cloud computing, in which many security issues exist, because data for a customer is stored and processed in cloud, not in a local machine. This paper briefly introduces cloud computing and its key concepts. In particularly, we intend to discuss security requirements and security issues involving data, application and virtualization in cloud computing, as well as current solutions to these issues. © 2012 IEEE.

关键词： Virtualization

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IWFR:Exploiting Full-duplex in Wireless Relay Networks

IWFR:Exploiting Full-duplex in Wireless Relay Networks

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2014 4th IEEE International Conference on Information Science and Technology

作者： Yong Lu Shaohe Lv Xiaodong Wang Xingming Zhou National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology

Traditional wireless relay networks have large endto-end time delay and low throughput because of the limit that it can't receive and forward at the same *** this paper,we proposed IWFR:Immediate Wireless Full-Duplex Relay which exploits the advantages of full-duplex to shorten the end-to-end time delay and improve the *** the same time,we designed a new implicit acknowledgement mechanism,which can eliminate the ACK overheads and evidently improve the throughput of the *** implement IWFR,we also modified the full-duplex node architecture to make it support for immediate *** shows that IWFR shortens the end-to-end time delay by 60%on average and improves the throughput to 240%of the original relay.

关键词： Relay IWFR:Exploiting Full-duplex in Wireless Relay Networks

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HyperSpring: Accurate and Stable Latency Estimation in the Hyperbolic Space

HyperSpring: Accurate and Stable Latency Estimation in the H...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yongquan Fu Yijie Wang National Key Laboratory of Parallel and Distributed Processing School of Computer National University of Defense Technology China

Predicting network latencies between Internet hosts can efficiently support large-scale Internet applications, e.g., file sharing service and the overlay construction. Several study use the hyperbolic space to model the Internet dense-core and many-tendril structure. However, existing hyperbolic space based embedding approaches are not designed for accurate latency estimation in the distributed context. We present HyperSpring, which estimates latency by modelling a mass spring system in the hyperbolic similar with Vivaldi. HyperSpring adopts coordinate initialization to speed up the convergence of coordinate computation, uses multiple-round symmetric updates to escape from bad local minima, and stabilizes coordinates by compensating RTT measurements to reduce the coordinate drifts. Evaluation results based on a network trace of 226 PlanetLab nodes indicate that, compared to Euclidean-space based Vivaldi, hyperspring provides performance improvements for most nodes, and incurs slightly higher distortions for a small number of nodes.

关键词： Delay IP networks Web and internet services Large-scale systems Peer to peer computing Springs Convergence Coordinate measuring machines Distortion measurement Extraterrestrial measurements

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Crowd intelligence in AI 2.0 era

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Frontiers of Information Technology & Electronic Engineering 2017年第1期18卷 15-43页

作者： Wei LI Wen-jun WU Huai-min WANG Xue-qi CHENG Hua-jun CHEN Zhi-hua ZHOU Rong DING State Key Laboratory of Software Development Beihang University National Laboratory for Parallel and Distributed Processing College of ComputerNational University of Defense Technology Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Technology Zhejiang University National Key Laboratory for Novel Software Technology Nanjing University

The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI 2.0. As one of the most prominent characteristics of research in AI 2.0 era, crowd intelligence has attracted much attention from both industry and research communities. Specifically, crowd intelligence provides a novel problem-solving paradigm through gathering the intelligence of crowds to address challenges. In particular, due to the rapid development of the sharing economy, crowd intelligence not only becomes a new approach to solving scientific challenges, but has also been integrated into all kinds of application scenarios in daily life, e.g., online-tooffline(O2O) application, real-time traffic monitoring, and logistics management. In this paper, we survey existing studies of crowd intelligence. First, we describe the concept of crowd intelligence, and explain its relationship to the existing related concepts, e.g., crowdsourcing and human computation. Then, we introduce four categories of representative crowd intelligence platforms. We summarize three core research problems and the state-of-the-art techniques of crowd intelligence. Finally, we discuss promising future research directions of crowd intelligence.

关键词： Crowd intelligence Artificial intelligence 2.0 Crowdsourcing Human computation

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