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Multi-path Reliable Routing with Pipeline Schedule in Wireless Sensor Networks 1

11th International Conference on Wireless Algorithms, Systems and Applications (WASA)

作者： Li, Jinbao Zhang, Li Guo, Longjiang Ren, Qianqian Guo, Yahong Heilongjiang Univ Sch Comp Sci & Technol Harbin Peoples R China Key Lab Database & Parallel Comp Harbin Heilongjiang Peoples R China Heilongjiang Univ Sch Informat Sci & Technol Harbin Heilongjiang Peoples R China

ISBN: (数字)9783319428369

ISBN: (纸本)9783319428369;9783319428352

To solve the problem of data missing caused by communication collision in Wireless Sensor Networks (WSNs), this paper proposes a multi-path reliable routing protocol. This protocol combines the technique of pipeline with multi-path reliable routing, and uses Markov chain to predict the period of using pipeline in order to schedule pipeline dynamically. Therefore, the combined techniques improve the network throughput. In the case that data congestion occurs, and the protocol can keep the data transmission rate unchangeable, and the proposed routing protocol can choose other path to transmit data in order to reduce the number of data missing. Simulation results indicate that the proposed protocol can deal with congestion and improves the network throughput effectively.

关键词： Pipelines

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Mobility-assisted big data collecting in wireless sensor networks

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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS 2016年第8期12卷

作者： Zhu, Jinghua Yin, Xuming Bai, Jingsi Wang, Yake Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Heilongjiang Peoples R China Key Lab Database & Parallel Comp Heilongjiang Pro Harbin Peoples R China

In recent years, the big data emerged as a hot topic because of the rapid growth of the information and wireless communication technology. One of the significant sources of the big data is wireless sensor networks. Due to the power limitation of sensor nodes, energy-efficient big data collecting is a challenging task in wireless sensor networks. Being considered as an effective solution to address this challenge is to utilize sink's mobility to assist data collecting. Although this method can reduce the volume of data transfer between sensor nodes and thus save energy consumption of nodes, the low speed of mobile sink hinders its use in data-intensive sensing applications with time constraint. In this article, we propose a four-phase mobility-assisted data collecting protocol consisting of network clustering, routes planning, routes combination, and data collecting. Two heuristic routes planning algorithms are presented to build a set of trajectories which satisfy the deadline constraint and have the minimum overall movement cost. Numeric results show that our approaches have better performance in terms of energy saving, latency, and movement cost.

关键词： Big data wireless sensor network data collection protocol mobile sinks heuristic routes planning algorithm

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Rogue Access Point Detection in Vehicular Environments 10th

Rogue Access Point Detection in Vehicular Environments

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10th International Conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Qu, Hao Guo, Longjiang Zhang, Weiping Li, Jinbao Ren, Meirui Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Peoples R China Key Lab Database & Parallel Comp Harbin 150080 Peoples R China

ISBN: (纸本)9783319218373;9783319218366

The threat of rogue access points (APs) has attracted significant attentions from both industrial and academic researchers. This paper considers a category of rogue APs that are set up in moving vehicles to lure users. Usually, rogue access points are on the moving vehicles that can keep close distance to the users at all time, thus the adversary has more time to expose private information of users. This paper proposes a practical detecting rogue APs algorithm based on received signal strength (RSS), which calculates the distance between the user and the APs to defend against the rogue APs. The paper also develops a relative position algorithm to find the position of AP. If the position of AP is on the road rather than on the road side, the algorithm suspects that the AP is rogue AP. In this paper, we also have implemented the detection algorithm on real vehicular environments and also have evaluated the performance of the proposed algorithm.

关键词： Rogue access point Vehicular networks RSS

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Research on Neutral Mutation Algorithm in DNA Polymorphism Testing based on OpenMP

Research on Neutral Mutation Algorithm in DNA Polymorphism T...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Li, Jun Lu, Jun Jing, Ruiqing Wang, Qiong Chang, Cheng Heilongjiang Univ Coll Comp Sci & Technol Harbin Peoples R China Key Lab Database & Parallel Comp Heilongjiang Pro Harbin Peoples R China

ISBN: (纸本)9781479919802

Soybean genotypes are adopted as the data source and the Tajima's D statistical method is parallel implemented by OpenMP technology,. This method is used for testing neutral mutation hypothesis of DNA polymorphism. By setting the sliding window size, all chromosomes containing the massive windows with multiple SNP sites are parallel processed, then the number of individual in sample, the number of segregating sites (S) and average number of nucleotide differences (pi) are obtained. After parameters filtering, the Tajima's D values for the effective SNP sites in each sliding window are parallel calculated. According to the experimental data, the serial/parallel algorithms are compared and the conclusion shows that the efficiency of testing neutral mutation can be improved by using the OpenMP technology. It is a realistic significance for processing massive biological information data.

关键词： genotype Tajima's D OpenMP SNP

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Research on parallel F-statistics estimation algorithm based on OpenMP

Research on Parallel F-statistics estimation algorithm based...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Jing, Rinqing Lu, Jun Li, Jun Wan, Kang Zhang, Haoyu Heilongjiang Univ Coll Comp Sci & Technol Harbin Peoples R China Key Lab Database & Parallel Comp Heilongjiang Pro Harbin Peoples R China

ISBN: (纸本)9781479919802

The genetic variation information file of glycine max is adopted as experimental data in this paper. The genetic variation information of soybean is processed and the corresponding algorithm is paralleled by the OpenMP parallel technology. The experiment extracted the corresponding biologic information of population individuals from genetic variation information, implemented corresponding process and calculation. The relevant serial algorithm and parallel algorithm are compared and analyzed. The experiment results show that the efficiency of the data processing and analysis of F statistic are effectively improved by OpenMP parallel technology[1]. It has actual significance on processing massive bioinformatic data.

关键词： F-statistics OpenMP population differentiation variation site

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Recognizing Human Activities in Real-Time Using Mobile Phone Sensors 8th

Recognizing Human Activities in Real-Time Using Mobile Phone...

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8th China Wireless Sensor Network Conference (CWSN)

作者： Jia, Boxuan Li, Jinbao Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Heilongjiang Peoples R China Key Lab Database & Parallel Comp Heilongjiang Pro Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9783662469811;9783662469804

To overcome the defects that previous research cannot recognize human activities accurately in real-time, we proposed a novel method, which collects data from the accelerator and gyroscope on a mobile phone, and then extracts features of both time domain and frequency domain. These features are used to learn random forest models offline, which make our mobile app can recognize human activities accurately online in real-time. Verified by theoretical analysis and a large number of contrast experiments, the recognition is rapid and accurate on mobile phones with accuracy at 97 %.

关键词： Activity recognition Random forests Mobile sensors Real time

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Mobile Data Gathering with Time-Constraints in Wireless Sensor Networks 10th

Mobile Data Gathering with Time-Constraints in Wireless Sens...

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10th International Conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Yin, Xuming Zhu, Jinghua Li, Yingshu Wu, Zhiqiang Heilongjiang Univ Sch Comp Sci & Technol Harbin 150080 Heilongjiang Peoples R China Key Lab Database & Parallel Comp Heilongjiang Pro Harbin Heilongjiang Peoples R China Georgia State Univ Atlanta GA 30303 USA

ISBN: (纸本)9783319218373;9783319218366

Recent research shows that significant energy can be saved by using mobile elements (ME) for data gathering in wireless sensor networks. The major drawback of this approach is the low movement speed of MEs which limits them to gather data from all sensor nodes with time constraints. This paper presents a data gathering algorithm called Minimum Mobile Elements Routing with Deadline (M2ERD). The goal of M2ERD is to find a set of minimum cost trajectories whilst satisfying deadline constraint. A genetic algorithm is presented to determine the feasible trajectories. The effectiveness and efficiency of M2ERD are verified through extensive simulations. The presented results show that M2ERD not only can provide substantial energy saving compared with traditional data gathering algorithm, but also can reduce the cost of mobile elements compared with ME-based data gathering algorithm.

关键词： Wireless sensor network Data gathering algorithm Mobile elements Genetic algorithm

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Improved Pre-miRNA Classification by Reducing the Effect of Class Imbalance

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BIOMED RESEARCH INTERNATIONAL 2015年第0期2015卷 960108-960108页

作者： Zhong, Yingli Xuan, Ping Han, Ke Zhang, Weiping Li, Jianzhong Heilongjiang Univ Key Lab Database & Parallel Comp Heilongjiang Pro Sch Comp Sci & Technol Harbin 150080 Peoples R China Harbin Univ Commerce Sch Comp & Informat Engn Harbin 150028 Peoples R China

MicroRNAs (miRNAs) play important roles in the diverse biological processes of animals and plants. Although the prediction methods based on machine learning can identify nonhomologous and species-specific miRNAs, they suffered from severe class imbalance on real and pseudo pre-miRNAs. We propose a pre-miRNA classification method based on cost-sensitive ensemble learning and refer to it as MiRNA Classify. Through a series of iterations, the information of all the positive and negative samples is completely exploited. In each iteration, a new classification instance is trained by the equal number of positive and negative samples. In this way, the negative effect of class imbalance is efficiently relieved. The new instance primarily focuses on those samples that are easy to be misclassified. In addition, the positive samples are assigned higher cost weight than the negative samples. MiRNA Classify is compared with several state-of-the-art methods and some well-known classification models by testing the datasets about human, animal, and plant. The result of cross validation indicates that MiRNA Classify significantly outperforms other methods and models. In addition, the newly added pre-miRNAs are used to further evaluate the ability of these methods to discover novel pre-miRNAs. MiRNA Classify still achieves consistently superior performance and can discover more pre-miRNAs.

关键词： ALGORITHMS PROBABILITY theory RESEARCH -- Evaluation FINANCING of research RNA T-test (Statistics) BIOINFORMATICS COST analysis RECEIVER operating characteristic curves DESCRIPTIVE statistics

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A Spatial Correlation Based Adaptive Missing Data Estimation Algorithm in Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS 2014年第4期21卷 280-289页

作者： Pan, Liqiang Gao, Huijun Gao, Hong Liu, Yong Harbin Inst Technol 92 West Da Zhi St Harbin Peoples R China Heilongjiang Univ Key Lab Database Parallel Comp Heilongjiang Prov Harbin Peoples R China

In wireless sensor networks, the missing of sensor data is inevitable due to the inherent characteristic of wireless sensor networks, and it causes many difficulties in various applications. To solve the problem, the missing data should be estimated as accurately as possible. In this paper, an adaptive missing data estimation algorithm is proposed based on the spatial correlation of sensor data. It adopts multiple regression model to estimate the missing data with the data of multiple neighbor nodes jointly rather than independently, which makes its estimation performance stable and reliable. In addition, for different missing data, it can adjust the estimation equation adaptively to capture the dynamic correlation of sensor data. Thereby, it can estimate the missing data more accurately. Further more, it can also give the confidence interval of each missing data for the given confidence level, which is helpful greatly for users. Experimental results on two real-world datasets show that the proposed algorithm can estimate the missing data accurately.

关键词： Missing data Estimation Spatial correlation Wireless sensor networks

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Implementing the Matrix Inversion by Gauss-Jordan Method with CUDA 9

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9th International Conference on Wireless Algorithms, Systems, and Applications (WASA)

作者： Tian, Ning Guo, Longjiang Ren, Meirui Ai, Chunyu Heilongjiang Univ Sch Comp Sci & Technol Harbin Peoples R China Key Lab Database & Parallel Comp Heilongjiang Peoples R China Univ S Carolina Div Math & Comp Sci Columbia SC 29208 USA

ISBN: (纸本)9783319077826;9783319077819

Solving the matrix inversion is an open problem which is often related to scientific computation. Moreover, matrix inverse also has wide applications in social networks. Individuals in social networks are described as nodes, and the similarity among nodes are significant for link prediction. Usually, the problem of calculating similarities among nodes is converted to the problem of matrix inversion. With the increasing of the orders of matrices, traditional sequential algorithms are unable to meet the needs for the short calculation time. Although cluster systems can solve the inversion of large-scale matrices efficiently, the equipment cost and power consumption are very high. This paper proposes a parallel algorithm PA-Gauss, which is based on the Gauss-Jordan method of selecting the main element. CUDA (computer Unified Device Architecture) of GPU (Graphic Process Unit) is used to implement the proposed algorithm to solve inversions of the real and complex matrices. The experimental results show that the Gauss-Jordan algorithm can save more running time than traditional sequential algorithms and the speedup ratio of PA-Gauss for Real Matrices is 633 similar to 100435, and the speedup ratio of PA-Gauss for complex Matrices is 224 similar to 36508. Therefore, the computing time of solving the matrix inversions is reduced significantly.

关键词： Inverse problems

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