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2013 IEEE 8th International Conference on Networking, Architecture and Storage, NAS 2013

作者： Guo, Longjiang Du, Shufang Ren, Meirui Liu, Yu Li, Jinbao He, Jing Tian, Ning Li, Keqin Heilongjiang University School of Computer Science and Technology Harbin 150080 China Key Laboratory of Database and Parallel Computing Heilongjiang China Kennesaw State University Department of Computer Science Kennesaw GA 30144 United States State University of New York Department of Computer Science New Paltz NY 12561 United States

ISBN: (纸本)9780769550343

Approximate string matching using the k-difference technique has been widely applied to many fields such as pattern recognition and computational biology. Data dependency exists in the traditional sequential algorithm. Therefore, it is hard to design a parallel algorithm for approximate string matching with k differences. This paper presents a technique to eliminate data dependency. Based on this technique, this paper also presents a parallel algorithm which can calculate the elements in the same row of the edit distance matrix in parallel by eliminating data dependency. The algorithm has high parallelism, but requires synchronization. To validate the proposed algorithm, it is implemented on GPU and multiple-core CPUs. Moreover, the CUDA optimization techniques are also presented in the paper. Finally, experimental results show that, compared with the traditional sequential algorithm on CPU with twenty-four cores, the proposed parallel algorithm achieves speedup of 7-42 on GPU. © 2013 IEEE.

关键词： Graphics processing unit

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An implementation of the QR iterations for finding eigenvalues of matrices with CUDA on GPU

An implementation of the QR iterations for finding eigenvalu...

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International Conference on Mechatronic Science, Electric Engineering and Computer

作者： Meirui Meihui Weiping Zhang Tao Wang Ning Tian Jinbao Li Longjiang Guo School of Computer Science and Technology Heilongjiang University Harbin 150080 China Harbin Research Institute of Electrical Instrumentation 150028 China School of Computer Science and Technology Heilongjiang University Harbin China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781479925667

Based on the principle of QR loop iterations, this paper implements a parallel algorithm based on the hardware of GPU (Graphic Process Unit) by using routines from CUDA (Computer Unified Device Architecture) to find the eigenvalues of general matrices. CPU and GPU computing card form a client-server computing framework. Here, CPU can be regarded as a client and GPU card is considered as a computing server. For the experiment environment, this paper chooses a GPU card with the model of NVIDIA GeForce GTX460 as a server side and a CPU with the model of Intel Core i5-760 quad-core as a client side. Win7 64-bit is selected as the operating system. The parallel implementation consists of two parts:PA H and PA QR. PA H is a procedure that transforms a matrix A into the Hessenberg matrix B. PA QR is the actual parallel algorithm of the QR iterations that is imposed on the Hessenberg matrix B for finding eigenvalues of the general matrix A. The speedup ratio of the proposed algorithm is jarless when the number of iterations becomes greater. The experimental results show that the parallel implementation with CUDA on GPU only makes use of less running time than traditional sequential algorithms. The speedup ratio of PA H is between 1.79 and 7.81. The speedup ratio of PA QR is between 3.24 and 118.9. Especially, when the order of general matrix equals 8192, the amount of iterations becomes 10000. The speedup ratio of the PA-H and the PA QR can run up to 7.81 and 118.9 respectively.

关键词： Graphics processing units Eigenvalues and eigenfunctions Hardware Kernel Instruction sets

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Distributed Aggregation Algorithms for Mobile Sensor Networks with Group Mobility Model

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Tsinghua Science and Technology 2012年第5期17卷 512-520页

作者： Qianqian Ren Longjiang Guo Jinghua Zhu Meirui Ren Junqing Zhu School of Computer Science and Technology Heilongjiang UniversityHarbin 150080China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin 150080China

In many applications of mobile sensor networks, such as water flow monitoring and disaster rescue, the nodes in the network can move together or separate temporarily. The dynamic network topology makes traditional spanning-tree-based aggregation algorithms invalid in mobile sensor networks. In this paper, we first present a distributed clustering algorithm which divides mobile sensor nodes into several groups, and then propose two distributed aggregation algorithms, Distance-AGG （Aggregation based on Distance）, and Probability-AGG （Aggregation based on Probability）. Both of these two algorithms conduct an aggregation query in three phases： query dissemination, intra-group aggregation, and inter-group aggregation. These two algorithms are efficient especially in mobile networks. We evaluate the performance of the proposed algorithms in terms of aggregation accuracy, energy efficiency, and query delay through ns-2 simulations. The results show that Distance-AGG and Probability-AGG can obtain higher accuracy with lower transmission and query delay than the existing aggregation algorithms.

关键词： mobile sensor networks data aggregation group mobility model distributed algorithms

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An Efficient Graph Isomorphism Algorithm Based on Canonical Labeling and Its parallel Implementation on GPU

An Efficient Graph Isomorphism Algorithm Based on Canonical ...

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

作者： Renda Wang Longjiang Guo Chunyu Ai Jinbao Li Meirui Ren Keqin Li School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang China Key Laboratory of Database and Parallel Computing Harbin Heilongjiang China Department of Computer Science University of South Carolina Upstate Spartanburg SC USA Department of Computer Science State University of New York New Paltz New York USA

The Graph Isomorphism (GI) problem has been extensively studied due to its significant applications. The most effective class of GI algorithms, i.e., canonical labeling algorithms, are suitable for either graphs with high randomness or symmetry, or graphs for which both of them are not strongly held. Also, the core operations of canonical labeling algorithms, i.e., individuation-refinement (IR) and certificate comparison, usually occupy more than 70% of the total running time. How to weaken the limitations of structures and improve the efficiency of these operations are challenges. In this paper, we present an efficient GI algorithm called PEACE, which is particularly suitable for graphs with high randomness or symmetry. We present a parallel implementation of our algorithm on GPUs. We design some new techniques and also use some existing methods to speed up calculations under CUDA. More importantly, these techniques can be applied to all IR-based GI algorithms. We evaluate the proposed algorithm on various graphs to make comprehensive comparison with currently the most efficient canonical labeling algorithms on CPUs. Experimental results show that PEACE is superior to other algorithms on graphs with high symmetry or many automorphisms, and up to 50% performance increase can be achieved in the best case. We also apply our parallel techniques on these algorithms, and compare the performance on CPU and multiple GPU devices. The results show that the techniques make all algorithms gain 15~55 speedup.

关键词： Labeling Graphics processing units Algorithm design and analysis Indexes Arrays Instruction sets Partitioning algorithms

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parallel Algorithm for Approximate String Matching with K Differences

Parallel Algorithm for Approximate String Matching with K Di...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Longjiang Guo Shufang Du Meirui Ren Yu Liu Jinbao Li Jing He Ning Tian Keqin Li Key Laboratory of Database and Parallel Computing Heilongjiang China Heilongjiang University School of Computer Science and Technology Harbin China Department of Computer Science Kennesaw State University Kennesaw Georgia USA Department of Computer Science Srate University of New York New Paltz New York USA

关键词： parallel algorithms Graphics processing units Approximation algorithms Algorithm design and analysis Heuristic algorithms Pattern matching

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Wireless nerve: Invisible anti-theft system in wireless sensor network

Wireless nerve: Invisible anti-theft system in wireless sens...

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Int. Workshops on Web-Age Information Management, WAIM 2012: 1st Int. Workshop on GDMM 2012, 2nd Int. Wireless Sensor Networks Workshop, IWSN 2012, 1st Int. Workshop on MDSP 2012, 3rd Int. Workshop on USDM 2012, 4th Int. Workshop on XMLDM 2012

作者： Ren, Meirui Duan, Jinsheng Qu, Hao Wang, Xinjing Du, Lei School of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing Heilongjiang Province Harbin 150001 China

ISBN: (纸本)9783642330490

There are limitations in traditional anti-theft technologies. All the technologies have a common ground, that is: the devices are exposed to the space, also easily found and destroyed by adversaries. This paper demonstrates a Hidden Anti-theft System (HAS) based on wireless sensor network. The sensors can be hidden in walls and furniture. The intruder influences the transmitting link, and RSSI of the link changes. According to the changes, the system can detect the movement in monitoring area, and keep invisible. HAS is applied in indoor environment. Experiment results show that HAS achieves very low false positive and no false negative. © 2012 Springer-Verlag.

关键词： Wireless sensor networks

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An effective top-k keyword search algorithm based on classified Steiner tree

An effective top-k keyword search algorithm based on classif...

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作者： Yang, Yan Tang, Mingzhu Zhong, Yingli Zhang, Zhaogong Guo, Longjiang School of Computer Science and Technology Heilongjiang University 150080 Harbin China Key Laboratory of Database and Parallel Computing Heilongjiang University 150080 Harbin China

ISBN: (纸本)9783642330490

keyword search has become one of hot topics in the field of information retrieval. It can provide users a simple and friendly interface. But the efficiency of some existing keyword search algorithms is low and there are some draws in sorting results. Most algorithms are suited for either unstructured data or structured data. This paper proposes a new kind of top-k keyword search algorithm. No matter the data is unstructured, semi-structured or structured, the algorithm is always effective. It introduces the concept of neighbor sets of nodes and uses set join algorithm to narrow the search space. We also propose the definition of classified Steiner tree, which can reduce the draw phenomenon in results. In addition, the algorithms can output the results of the classified Steiner tree at the same time of computing them. So it can reduce the waiting time of the users and improve the efficiency of keywords search. © 2012 Springer-Verlag.

关键词： Efficiency

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Data query based on data cache and channel switch in multi-radio wireless sensor networks

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Jisuanji Xuebao/Chinese Journal of Computers 2012年第11期35卷 2403-2414页

作者： Zhang, Yan-Qing Li, Jin-Bao Guo, Long-Jiang Zhu, Jing-Hua School of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin 150080 China

Due to the nature of multi-radio multi-channel wireless sensor networks, such as the quality of service of the links, channel conflict etc., we investigated the problem of data query based on data cache and channel switch, and proved it to be an NP-complete problem. Firstly, we constructed a LP equation based on the data flow conservation and link-channel constraint etc. to formulate the problem, then designed a polynomial approximate algorithm. The algorithm used dynamic programming strategy to minimize the delay of unit data packet transmission from cache nodes to the query node, greedily chose a cache node with the smallest delay of unit data packet transmission, and collected the new covered data packets. Theoretical analysis and experimental results indicate that the proposed algorithm can reduce the communicate delay and improve the efficiency of query effectively.

关键词： Dynamic programming

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MPMC: An algorithm for data aggregation scheduling in multi-channel and multi-power wireless sensor networks

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2012年第7期49卷 1568-1578页

作者： Fan, Wenbin Guo, Longjiang Li, Jinbao Ren, Meirui School of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing Heilongjiang Province Harbin 150001 China

Data aggregation is a fundamental and yet time-consuming task in WSNs, especially in high-density WSNs. Therefore, people have focused on the problem of minimum-latency data aggregation. The problem has been already proved that it is an NP-hard. This paper proposes a cluster-based data aggregation scheduling algorithm called MPMC in multi-channel and multi-power WSNs to minimize the data aggregation latency. The paper adopts the idea of that the low power is used for packet transmission in inner-cluster and high power is used for packet transmission between clusters. This paper analyzes the number of channel under different topologies that approaches a constant. In simulation experiments, MPMC compares with the best algorithm based on single channel and the best algorithm based on multi-channel. Simulation results show that the MPMC algorithm proposed in this paper achieves the minimum average latency.

关键词： Wireless sensor networks

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Distributed multi-dimensional probabilistic Top-k query processing in sensor networks

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2012年第SUPPL.1期40卷 389-393+397页

作者： Zhu, Jinghua Guan, Xuemin Department of Computer Science and Technology Heilongjiang University Harbin 150080 China Key Laboratory of Database and Parallel Computing Heilongjiang Province Harbin 150080 China

A distributed multi-dimensional probabilistic Top-k (DMPT) query processing algorithm was proposed for sensor networks. DMPT exploited Skyline operator to get the Top-k results and reduced data transmissions and query delay through feedback and filtering mechanism. Data uncertainty, multi-dimensional attributes, distributed network and energy limitation were considered in DMPT, and the Top-k results were attained by computing Skylayers of data. Experiments on real and simulated data are conducted to demonstrate that DMPT has better energy efficiency and faster response compared with traditional algorithm.

关键词： Sensor networks

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