Please wait a minute...
FITEE
Front. Inform. Technol. Electron. Eng.  2016, Vol. 17 Issue (8): 766-780    DOI: 10.1631/FITEE.1500487
    
负载均衡的分布式指纹识别系统
Yun-xiang Zhao, Wan-xin Zhang, Dong-sheng LI, Zhen Huang, Min-ne Li, Xi-cheng Lu
National Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410003, China
Pegasus: a distributed and load-balancing fingerprint identification system
Yun-xiang Zhao, Wan-xin Zhang, Dong-sheng LI, Zhen Huang, Min-ne Li, Xi-cheng Lu
National Laboratory for Parallel and Distributed Processing, College of Computer, National University of Defense Technology, Changsha 410003, China
 全文: PDF 
摘要： 概要：指纹的唯一性和不变性使得它在各类生物识别系统中得到了广泛的应用。随着指纹识别技术的发展，大规模的指纹存储和系统高并发的需求给指纹识别系统带来了新的挑战。面对这种挑战，我们设计并实现了一个负载均衡的分布式指纹识别系统，它包括分布式指纹特征提取子系统和分布式指纹特征存储子系统两部分。在指纹特征提取的过程中，特征提取与Hadoop图片处理接口（HIPI）的结合使得特征提取的效率得到大幅度提升；特征存储子系统对MongoDB默认的负载均衡策略进行了优化，使得鲁棒性得到了明显提高。相关的试验和模拟表明，相比于Hadoop默认的小文件处理机制，我们的系统可以在指纹特征提取的过程中减少约70%的处理时间；优化后的MongoDB负载均衡策略可以将分布式MongoDB系统的前端mongos负载差距控制在5%以下，基于操作负载（增、删、改、查）的后端数据存储负载均衡策略将由数据迁移带来的时间开销降低了约40%。
关键词： 分布式指纹识别系统;  分布式MongoDB;  负载均衡    
Abstract: Fingerprint has been widely used in a variety of biometric identification systems in the past several years due to its uniqueness and immutability. With the rapid development of fingerprint identification techniques, many fingerprint identification systems are in urgent need to deal with large-scale fingerprint storage and high concurrent recognition queries, which bring huge challenges to the system. In this circumstance, we design and implement a distributed and load-balancing fingerprint identification system named Pegasus, which includes a distributed feature extraction subsystem and a distributed feature storage subsystem. The feature extraction procedure combines the Hadoop Image Processing Interface (HIPI) library to enhance its overall processing speed; the feature storage subsystem optimizes MongoDB’s default load balance strategy to improve the efficiency and robustness of Pegasus. Experiments and simulations are carried out, and results show that Pegasus can reduce the time cost by 70% during the feature extraction procedure. Pegasus also balances the difference of access load among front-end mongos nodes to less than 5%. Additionally, Pegasus reduces over 40% of data migration among back-end data shards to obtain a more reasonable data distribution based on the operation load (insertion, deletion, update, and query) of each shard.
Key words: Distributed fingerprint identification    Distributed MongoDB    Load balancing
收稿日期: 2015-12-29 出版日期: 2016-08-05
CLC:  TP316.4  
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
Yun-xiang Zhao
Wan-xin Zhang
Dong-sheng LI
Zhen Huang
Min-ne Li
Xi-cheng Lu

引用本文:

Yun-xiang Zhao, Wan-xin Zhang, Dong-sheng LI, Zhen Huang, Min-ne Li, Xi-cheng Lu. Pegasus: a distributed and load-balancing fingerprint identification system. Front. Inform. Technol. Electron. Eng., 2016, 17(8): 766-780.

链接本文:

http://www.zjujournals.com/xueshu/fitee/CN/10.1631/FITEE.1500487    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2016/V17/I8/766

[1] Nan-nan Zhao, Ji-guang Wan, Jun Wang, Chang-sheng Xie. 一种针对基于一致性哈希的键值存储系统的低能耗副本布局策略[J]. Front. Inform. Technol. Electron. Eng., 2016, 17(10): 994-1007.