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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Guo, Yahong Guo, Xiaohang Zhang, Yanqing Zhu, Jinghua Li, Jinbao School of Information Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Heilongjiang University Harbin Heilongjiang 150080 China

ISBN: (纸本)9783642362514

In this paper, we investigate on the opportunistic routing in Multi-Power Wireless Sensor Networks (MP WSNs). We first propose a routing metric called METT of opportunistic routing in MP WSNs, and model the power selecting process as a Markov decision process for computing the METT metric. We describe the METT-based opportunistic routing problem, and design a polynomial time optimal algorithm for getting the optimal routing and power selection scheme. Theory analysis and experiments show that the proposed multi-power opportunistic routing can improve the data transmission efficiency, significantly reduce the energy consumption and the end-to-end transmission delay. © 2013 Springer-Verlag.

关键词： Wireless sensor networks

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Session-Recommendation Based on Gated Neural Network to Extract Item Structure Feature Graph 22

Session-Recommendation Based on Gated Neural Network to Extr...

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5th International Conference on Data Storage and Data Engineering, DSDE 2022

作者： Zhang, Wei Yang, Yan Zhong, Yingli College of Computer Science and Technology Heilongjiang University China Heilongjiang Key Laboratory of Database and Parallel Computing Heilongjiang University China School of Computer Science and Technology Heilongjiang University China

ISBN: (纸本)9781450395724

The issue of inaccurate user portrait recommendations for short-Term conversations is solved. The classical recommendation is based on an assumption: The user's historical behavior can represent the user's stable long-Term preferences, and the result is generated based on the user's historical behavior. However, there is sparseness in the user's historical behavior information record in the actual data set, and the obtained data cannot accurately represent the user's preferences. Research on a session recommendation focuses on user behavior data in the short term, and aims at predict anonymous user behavior based on in-session behavior information. It plays a vital role in application scenarios where user behavior information is scarce. Feature extraction is performed on the user's anonymous behavior information graph generated in a fixed period of time as the embedding representation of user's interest preference;the graph structure of the same item in the global click interaction graph is combined with the input a gated graph neural network as the item attribute embedding representation. The prediction part adopts simulated interactive calculation to produce results. With the help of gated graph neural network, features extraction and analysis of data in short-Term sessions: session-based user behavior data and in-session item attributes are obtained from the graph data structure, which reduces errors caused by inconsistent data processing methods. The user's current interest is captured based on the behavior information in the session, the global inter-item conversion graph is generated based on the sequence of click moments, and the feature vector is obtained through graph neural network processing. The generation of recommendation results is more time-sensitive, complete the anonymity problem due to the scarcity of user's information, and improves the accuracy of recommendations. © 2022 ACM.

关键词： Graph neural networks

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DMSA: Dynamic Multi-Scale Unsupervised Semantic Segmentation Based On Adaptive Affinity 48

DMSA: Dynamic Multi-Scale Unsupervised Semantic Segmentation...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Yang, Kun Lu, Jun Heilongjiang University College of Computer Science and Technology Harbin150080 China Jiaxiang Industrial Technology Research Institute of Hlju Jining China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin China

ISBN: (纸本)9781728163277

The proposed method in this paper proposes an end-to-end unsupervised semantic segmentation architecture DMSA based on four loss functions. The framework uses Atrous Spatial Pyramid Pooling (ASPP) module to enhance feature extraction. At the same time, a dynamic dilation strategy is designed to better capture multi-scale context information. Secondly, a Pixel-Adaptive Refinement (PAR) module is introduced, which can adaptively refine the initial pseudo labels after feature fusion to obtain high quality pseudo labels. Experiments show that the proposed DSMA framework is superior to the existing methods on the saliency dataset. On the COCO 80 dataset, the MIoU is improved by 2.0, and the accuracy is improved by 5.39. On the Pascal VOC 2012 Augmented dataset, the MIoU is improved by 4.9, and the accuracy is improved by 3.4. In addition, the convergence speed of the model is also greatly improved after the introduction of the PAR module. © 2023 IEEE.

关键词： Semantic Segmentation

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Density and distance based probabilistic broadcasting algorithm in mobile sensor networks

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2014年第1期51卷 151-160页

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

Broadcasting is the most basic manner to transmit messages in mobile wireless sensor networks. However, existing relevant broadcasting algorithms in mobile wireless sensor networks need a large number of intermediate forwarding nodes. The large number of intermediate forwarding nodes causes a mass of redundant message packages. Massive redundant messages will consume much energy and lead to a short life period of mobile wireless sensor networks. This paper proposes a broadcasting algorithm named node density and distance-based probability (NDDP for short). The average forwarding ratio of the algorithm is only 5S/(Nπr2), where S is the area of the networks, N is the amount of nodes in the networks, and r is communication range. Then the average receipt ratio of NDDP is more than 95 percent in theoretical analysis and more than 92 percent in the ns-2 simulation results. Denser the network is, the more energy saving the algorithm is. Simulation results also show that NDDP outperforms the two algorithms in Smite and Sidewinder not only on the aspect of stability but also on energy conservation.

关键词： Energy conservation

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Data collection using wavelet-segment constant compression in wireless sensor networks

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2013年第1期34卷 119-127页

作者： Li, Yang 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 150080 China

In structural health monitoring system, it usually needs to arrange lots of sensor nodes. In order to get the monitoring data in real time, frequent data collection is essential will consume so much energy, especially when the data is multi-dimensional. To reduce communication messages in the frequent data collection applications and as far as possible to extend the network lifetime. This paper proposes a data collection algorithm based on wavelet-segment constant compression(W-SDC), applies compressive sampling theory, and compress the messages with W-SDC before data transmitted, thereby this algorithm reduces the amount of data transmission. When the network is large-scale, it could save communication costs greatly, and extend the network lifetime. The total messages of traditional data collection method is O(N2), compressive data gathering method is O(MN), while the total communication costs of this algorithm is O(mN), where m

关键词： Sensor nodes

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Minimum latency data aggregation scheduling in MR-MC wireless sensor networks

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Tongxin Xuebao/Journal on Communications 2014年第10期35卷 192-199页

作者： Li, Jin-Bao Wang, Meng Guo, Long-Jiang School of Computer Science and Technology Heilongjiang University Harbin150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China

The problem of minimum latency data aggregation scheduling in single-radio single-channel wireless sensor networks is a NPC problem and many solutions have been proposed. In multi-radio multi-channel networks, the latency may be lower as a node may receive transmission data from other different nodes simultaneously. It formulates the minimum latency data aggregation scheduling into an optimization problem with joint consider of tree structure, time slot assignment, channel assignment and radio assignment. The problem is divided into constructing data aggregation tree and designing a node schedule subproblems. For each subproblem, heuristic algorithm has been proposed. The simulation results show that the proposed algorithm achieve good performance.

关键词： Scheduling

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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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Neighbor discovery algorithm based on the regulation of duty-cycle in mobile sensor network

Neighbor discovery algorithm based on the regulation of duty...

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8th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2013

作者： Li, Jinbao Yang, Jian Zhang, Yanqing Guo, Longjiang Li, Yingshu School of Computer Science and Technology Heilongjiang University Harbin Heilongjiang 150080 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin Heilongjiang 150080 China Department of Computer Science Georgia State University Atlanta GA 30303 United States

ISBN: (纸本)9783642397004

In this paper, aiming at the problem that the node discovers its neighbor nodes, when it is moving in mobile sensor network, we propose an algorithm for dynamical regulating the duty cycle of the node which needs to discover it neighbor node. This algorithm uses the boundary nodes in the communication range of the node to predict potential neighbor nodes, applies passion point process to predict the number of nodes in communication range of the node, regulates the duty-cycle of the node based on the model of balls and boxes, and then schedules the waking time of the node periodically by using the duty-cycle which is regulated to finish the detection. Finally, theoretical analysis and simulation experiments show that the proposed algorithm can discover more neighbor nodes in the short period of time with less energy. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Sensor nodes

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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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2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013

作者： Ren, Meirui Ren, Meihui Zhang, Wei Ping Wang, Tao Tian, Ning Li, Jinbao Guo, Longjiang School of Computer Science and Technology Heilongjiang University Harbin150080 China Harbin Research Institute of Electrical Instrumentation Harbin150028 China Key Laboratory of Database and Parallel Computing of Heilongjiang Province Harbin150080 China

ISBN: (纸本)9781479925650

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 is-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. © 2013 IEEE.

关键词： Matrix algebra

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