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A survey of queries over uncertain data

KNOWLEDGE AND INFORMATION SYSTEMS 2013年第3期37卷 485-530页

作者： Wang, Yijie Li, Xiaoyong Li, Xiaoling Wang, Yuan Natl Univ Def Technol Sch Comp Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

Uncertain data have already widely existed in many practical applications recently, such as sensor networks, RFID networks, location-based services, and mobile object management. Query processing over uncertain data as an important aspect of uncertain data management has received increasing attention in the field of database. Uncertain query processing poses inherent challenges and demands non-traditional techniques, due to the data uncertainty. This paper surveys this interesting and still evolving research area in current database community, so that readers can easily obtain an overview of the state-of-the-art techniques. We first provide an overview of data uncertainty, including uncertainty types, probability representation models, and sources of probabilities. We next outline the current major types of uncertain queries and summarize the main features of uncertain queries. Particularly, we present and analyze several typical uncertain queries in detail, such as skyline queries, top- queries, nearest-neighbor queries, aggregate queries, join queries, range queries, and threshold queries over uncertain data. Finally, we present many interesting research topics on uncertain queries that have not yet been explored.

关键词： Uncertain data Uncertain queries Skyline query Top-k query Nearest-neighbor query Aggregate query

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QR decomposition architecture using the iteration look-ahead modified Gram-Schmidt algorithm

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IET CIRCUITS DEVICES & SYSTEMS 2016年第5期10卷 402-409页

作者： Liu, Cang Tang, Chuan Yuan, Luechao Xing, Zuocheng Zhang, Yang Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

QR decomposition is extensively adopted in multiple-input-multiple-output orthogonal frequency-division multiplexing wireless communication systems, and is one of the performance bottlenecks in lots of high-performance wireless communication algorithms. To implement low processing latency QR decomposition with hardware, the authors propose a novel iterative look-ahead modified Gram-Schmidt (ILMGS) algorithm based on the traditional modified Gram-Schmidt (MGS) algorithm. They also design the corresponding triangular systolic array (TSA) architecture with the proposed ILMGS algorithm, which only needs n time slots for a n x n real matrix. For reducing the hardware overhead, they modify the TSA architecture into an iterative architecture. They also design a modified iterative architecture to further reduce the hardware overhead. The implementation results show that the normalised processing latency of the modified iterative architecture based on the proposed ILMGS algorithm is 1.36 times lower than the one based on the MGS algorithm. To the best of the authors' knowledge, the designed architecture achieves the superior latency performance than the existing works.

关键词： MIMO communication wireless channels iterative methods QR decomposition architecture wireless communication algorithms multiple-input-multiple-output orthogonal frequency-division multiplexing iterative look-ahead modified Gram-Schmidt algorithm modified Gram-Schmidt algorithm triangular systolic array

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Repairing multiple failures adaptively with erasure codes in distributed storage systems

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2016年第5期28卷 1437-1461页

作者： Pei, Xiaoqiang Wang, Yijie Ma, Xingkong Xu, Fangliang Natl Univ Def Technol Coll Comp Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

Repairs of multiple failures in distributed storage systems have posed the challenges for erasure coding: how to minimize the repair time with the least extra repair network traffic cost. However, existing repair schemes designed for single failure suffer from the high network traffic cost due to the serial repairs for multiple failures. Repair schemes designed for multiple failures suffer from long repair time due to the centralized repair structure. In this paper, we propose a decentralized adaptive repair scheme, called DARS, to minimize the repair time with the least extra network traffic cost. Specially, we propose a three-layer repair model to support the repairs for both the single and multiple failures. For low repair time, a bandwidth-aware node selection technique is proposed to guide the selection of nodes, and a line-structured data transmission technique is proposed to organize the data transmission between the providers and the newcomer. For the least extra network traffic cost, a core-based data distribution technique is proposed to organize the data transmission between the coordinator and other newcomers, and an intersection provider adjustment technique is proposed to adaptively adjust the number of intersection providers. Moreover, we adopt the lazy repair' within a stripe to further reduce the repair network traffic cost. We implement and evaluate DARS on our raid distributed storage system under various parameter settings with 30 physical machines and 200 virtual machines. Experimental results confirm that DARS reduces the repair time by 29% and 55% on average compared with tree-structured repair and CORE, respectively. Copyright (c) 2015 John Wiley & Sons, Ltd.

关键词： Repair Wound Healing traffic network Cache Memory System data transmission TIME TO REPAIR telecommunication traffic DARS gene multiple fault parameter setting

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An Area-Efficient Hybrid Polar Decoder With Pipelined Architecture

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IEEE ACCESS 2020年 8卷 68068-68082页

作者： Wang, Yu Wang, Qinglin Zhang, Yang Qiu, Shikai Xing, Zuocheng Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha 410073 Peoples R China

As the first kind of capacity-achieving forward error correction (FEC) codes, polar codes have attracted much research interest recently. Compared with traditional FEC codes, polar codes show better error correction performance when successive cancellation list (SCL) decoding with cyclic redundancy check is adopted. However, its serial decoding nature and high complexity of list management lead to its low throughput. Though the adaptive SCL decoding and hybrid decoding can improve the throughput, it comes at cost of implementation area. In this paper, we propose a pipelined hybrid decoding procedure and the corresponding hardware architecture to improve the area efficiency. In our design, the idle decoding cores are employed for successive cancellation (SC) decoding when SCL decoding is not working. The SCL decoding will be activated when the SC decoding fails. Different decoding cores work according to their own operation sequences and share one common processing array to improve the utilization ratio of processing elements. Constant receiving interval is supported with the design of input buffer to store all received codewords. A software platform is established to optimize the design parameters for each module of decoder. Moreover, the corresponding architecture is implemented using 65nm technology. Experimental results show that the proposed decoder can achieve a similar error correction performance with the SCL decoding with list size 16. Compared to the state-of-the-art available hybrid decoder, our proposed pipelined hybrid decoder is 3.07 x more area efficient.

关键词： Polar decoder hybrid decoding pipelined architecture area-efficient

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Scalable and elastic event matching for attribute-based publish/subscribe systems

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2014年 36卷 102-119页

作者： Ma, Xingkong Wang, Yijie Qiu, Qing Sun, Weidong Pei, Xiaoqiang Natl Univ Def Technol Sch Comp Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

Due to the sudden change of the arrival live content rate and the skewness of the large-scale subscriptions, the rapid growth of emergency applications presents a new challenge to the current publish/subscribe systems: providing a scalable and elastic event matching service. However, most existing event matching services cannot adapt to the sudden change of the arrival live content rate, and generate a non-uniform distribution of load on the servers because of the skewness of the large-scale subscriptions. To this end, we propose SEMAS, a scalable and elastic event matching service for attribute-based pub/sub systems in the cloud computing environment. SEMAS uses one-hop lookup overlay to reduce the routing latency. Through a hierarchical multi-attribute space partition technique, SEMAS adaptively partitions the skewed subscriptions and maps them into balanced clusters to achieve high matching throughput. The performance-aware detection scheme in SEMAS adaptively adjusts the scale of servers according to the churn of workloads, leading to high performance-price ratio. A prototype system on an OpenStack-based platform demonstrates that SEMAS has a linear increasing matching capacity as the number of servers and the partitioning granularity increase. It is able to elastically adjust the scale of servers and tolerate a large number of server failures with low latency and traffic overhead. Compared with existing cloud based pub/sub systems, SEMAS achieves higher throughput in various workloads. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Publish/subscribe Attribute-based Event matching Content space partitioning Cloud computing

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High performance robust audio event recognition system based on FPGA platform

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COGNITIVE SYSTEMS RESEARCH 2018年 50卷 196-205页

作者： Xu, Jinwei Liu, Zhiqiang Jiang, Jingfei Dou, Yong Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

Audio event recognition is applied in many novel application areas. Opposing the deep CNN, 1-max pooling CNN is a simple, but efficient CNN architecture for robust audio event recognition. This study proposes a parallel architecture to accelerate robust audio event recognition. To implement this in hardware, we evaluate the precision of 1-max pooling CNN model and propose an approximate algorithm to replace the complex calculation in spectral image feature (SIF) extraction. We then propose a scalable parallel structure of SIF extraction and 1-max pooling CNN. The SIF extraction unit has eight parallelisms and the 1-Max Pooling CNN accelerator has 40 processor elements (PEs) in our implementation. The entire system is implemented on the Xilinx VC709 board. The average performance of our FPGA accelerator is 675.7 fps under 100 MHz working frequency, which is about 31.9 x speed-up compare with CPU. We further implement a small-scale FPGA array with four Xilinx FPGA for robust audio event recognition. To communicate between the four FPGA and the host, we design a route protocol based on source route algorithm. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Audio event recognition Convolutional neural networks 1-max pooling Precision evaluation parallel architecture FPGA

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ATTI: Workload-Aware Query Adaptive OcTree Based Trajectory Index

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2013年第3期E96D卷 643-654页

作者： Meng, Xiangxu Wang, Xiaodong Li, Xinye Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

The GPS trajectory databases serve as bases for many intelligent applications that need to extract some trajectories for future processing of mining. When doing such tasks, spatio-temporal range queries based methods, which find all sub-trajectories within the given spatial extent and time interval, are commonly used. However, the history trajectory indexes of such methods suffer from two problems. First, temporal and spatial factors are not considered simutaneously, resulting in low performance when processing spatio-temporal queries. Second, the efficiency of indexes is sensitive to query size. The query performance changes dramatically as the query size changed. This paper proposes workload-aware Adaptive OcTree based Trajectory clustering Index (ATTI) aiming at optimizing trajectory storage and index performance. The contributions are three-folds. First, the distribution and time delay of the trajectory storage are introduced into the cost model of spatio-temporal range query;Second, the distribution of spatial division is dynamically adjusted based on UPS update workload;Third, the query workload adaptive mechanism is proposed based on virtual OcTree forest. A wide range of experiments are carried out over Microsoft GeoLife project dataset, and the results show that query delay of ATTI could be about 50% shorter than that of the nested index.

关键词： spatial-temporal database trajectory workload-aware adaptive

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CaFPGA: An automatic generation model for CNN accelerator

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MICROprocESSORS AND MICROSYSTEMS 2018年第Jul.期60卷 196-206页

作者： Xu, Jinwei Liu, Zhiqiang Jiang, Jingfei Dou, Yong Li, Shijie Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

Convolutional neural networks (CNNs) are gaining considerable popularity in numerous computer-vision applications. A convolutional architecture for fast feature embedding (Caffe) and other general frameworks has been proposed with the development of CNN. The field-programmable gate array (FPGA) as a classical platform is used to accelerate CNNs because CNNs are computationally complex tasks. However, the implementation of CNN on FPGA platforms is difficult. The present study focuses on exploring the performance-resource design space and proposes an automatic generation model to implement the CNN reconfigurable accelerator on the FPGA platform, which uses Caffe description text as its input file. A design-space exploration model is further proposed. This model includes a layer-folding pipeline structure to balance the bandwidth requirements of convolutional and fully connected layers with incremental exploration algorithms to exploit CNN parallelism. The AlexNet, VGG-S, and VGG-16 networks are implemented. The AlexNet accelerator can achieve 593.5 GOPS, and the VGG-16 accelerator can achieve 638.9 GOPS, which is equivalent or even exceeds that of the state-of-the-art CNN accelerator for VGG-16.

关键词： Convolution neural networks FPGA Automatic generation model Layer-folding pipeline structure Design space exploration

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A novel orientation-and location-independent activity recognition method

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PERSONAL AND UBIQUITOUS COMPUTING 2017年第3期21卷 427-441页

作者： Shi, Dianxi Wang, Ran Wu, Yuan Mo, Xiaoyun Wei, Jing Natl Univ Def Technol Natl Lab Parallel & Distributed Proc Changsha Hunan Peoples R China

The orientation and location of a mobile phone pose fundamental challenges to activity recognition (AR) in a device. Given that AR significantly affects recognition accuracy, in this study, we focus on eliminating the influence of orientation and location changes on AR. First, we propose an activity recognition framework, which is independent of orientation and location changes, to uniformly deal with the problem of orientation and location changes on AR. Second, a dynamic coordinate transformation approach on inertial sensor data is proposed. In this method, the data collected in different orientations are dynamically mapped to the reference coordinate system of a mobile phone. The classification on the mapped data can reach significantly higher accuracy than that on the original data. We design four sets of comparative experiments to verify the validity of the proposed method, and the results demonstrate its effectiveness. Third, the influence of the location changes of mobile phones on AR is eliminated through the location-specific AR method. The effectiveness of the proposed method is verified by two groups of contrast tests. Finally, a real-time AR system is implemented on an Android platform. Results demonstrate that the proposed method obtains valid recognition results despite various orientation and location changes.

关键词： Activity recognition Dynamic coordinates Inertial sensor Orientation-independent Location-independent Transformation

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SPGM: an efficient algorithm for mapping MapReduce-like data-intensive applications in data centre network

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INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES 2013年第2期9卷 172-192页

作者： Li, Xiaoling Wang, Huaimin Ding, Bo Li, Xiaoyong Natl Univ Def Technol Sch Comp Sci Natl Key Lab Parallel & Distributed Proc Changsha 410073 Hunan Peoples R China

In traditional data centre network, how to efficiently allocate the virtual data centres (VDCs) on the physical data centre network (PDCN) is a challenging problem, which is denoted as GraphMap. GraphMap refers to map the virtual nodes to the substrate nodes and the virtual links to the substrate paths, respectively. The existing heuristic approaches attempt a two stage solution by solving the node mapping in a first stage and doing the link mapping in a second stage, which results in the mapping time being very large. In this paper, we propose an efficient mapping algorithm based on shortest path graph matching (SPGM) for online MapReduce-like data-intensive applications;the simulations show that SPGM can efficiently allocate the MapReduce-like data intensive applications on the PDCN in a much shorter time compared to the existing heuristic algorithms and maintain good performance.

关键词： data centre networks virtual data centre physical data centre network MapReduce-like data intensive

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