Research and Prediction on Time-Sequence Characteristics of Group-User Access Behavior in Public Map Service

WU Huayi; LI Rui; ZHOU Zhen; JIANG Jie; GUI Zhipeng

doi:10.13203/j.whugis20150283

Volume 40 Issue 10

Oct. 2015

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2015 > 40(10): 1279-1286,1316. > DOI: 10.13203/j.whugis20150283

WU Huayi, LI Rui, ZHOU Zhen, JIANG Jie, GUI Zhipeng. Research and Prediction on Time-Sequence Characteristics of Group-User Access Behavior in Public Map Service[J]. Geomatics and Information Science of Wuhan University, 2015, 40(10): 1279-1286,1316. DOI: 10.13203/j.whugis20150283

Citation:

PDF (2756 KB)

Research and Prediction on Time-Sequence Characteristics of Group-User Access Behavior in Public Map Service

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
2.
Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China;
3.
National Geomatics Center of China, Beijing 100830, China;
4.
School of Remote Sensing and Information Science, Wuhan University, Wuhan 430079, China

Funds: The National Natural Science Foundation of China, No. 41371370; the National Key Basic Research and Development Program (973 Program) of China, No. 2012CB719906.

More Information

Received Date: May 05, 2015
Published Date: October 04, 2015

Graphical Abstract

Abstract

Abstract

Group-user access behavior in public map service has a social nature and there is a certain group-user access pattern, which has a high access aggregative and outburst feature. However, the feature has a great influence on the demands for cloud computing resources for public map service. Thus, how to effectively express and capture the access aggregative feature and the changes of access intensity over time, and predict the access load of public map service accurately, is the important key for selecting and scheduling cloud computing resources on demand, that can address the challenge of concurrent service for massive users. Based on the volume user access logs from public map service and the time-sequence clustering method, this paper first builds a time-sequence distribution model for group-user access arriving behavior; then using the features of multi-peak, variable and periodicity in access intensity, this paper optimally partitions the time-sequence of access arrival rate in a period into different temporal patterns; as there are different probability density distribution of access arrival rate in different temporal patterns, this paper proposes a method of service load forecasting method based on a smoothing time-sequence of cumulative probability distribution. This method has a low complexity and needs few priori data. Experimental results and method application prove that the optimal partition and prediction for the access arrival rate of group-user access based on a time-sequence have a good service response performance for massive users concurrent access, improve the utilization of cloud computing resource, and balance the service quality and cost in public map service.
- public map service,
- access arrival rate,
- time series clustering,
- Fisher optimum split method,
- resource scheduling

FullText(HTML)

References (20)

References

[1]	Li Deren, Sui Haigang, Shan Jie, et al. Discussion on Key Technologies of Geographic National Conditions Monitoring[J].Geomatics and Information Science of Wuhan University,2012,37(5):505-512(李德仁,眭海刚,单杰,等.论地理国情监测的技术支撑[J].武汉大学学报·信息科学版,2012,37(5):505-512)
[2]	Wu Huayi, Zhang Hanwu. QoGIS: Concept and Research Framework[J]. Geomatics and Information Science of Wuhan University, 2007, 32(5): 385-388(吴华意,章汉武. 地理信息服务质量(QoGIS):概念和研究框架 [J]. 武汉大学学报·信息科学版, 2007, 32(5): 385-388)
[3]	Zhang Hanwu,Wu Huayi,Hu Yueming,et al. From Quality of Geospatial Data to Quality of Geospatial Information Services[J]. Geomatics and Information Science of Wuhan University, 2010, 35(9): 1 104-1 107(章汉武,吴华意,胡月明,等. 从地理空间数据质量到地理空间信息服务质量[J]. 武汉大学学报·信息科学版, 2010, 35(9): 1 104-1 107)
[4]	Gong J, Wu H, Zhang T, et al. Geospatial Service Web: Towards Integrated Cyberinfrastructure for GIScience[J]. Geo-spatial Information Science, 2012, 15(2): 73-84
[5]	Li Deren. The Geo-spatial Information Science Mission [J]. Geo-spatial Information Science, 2012, 15(1): 1-2
[6]	Gao J, Pattabhiraman P, Bai X, et al. SaaS Performance and Scalability Evaluation in Clouds[C]. 2011 IEEE 6th International Symposium on Service Oriented System Engineering (SOSE), Irvine, CA,2011
[7]	Badger L, Grance T, Patt-Corner R, et al. Cloud Computing Synopsis and Recommendations[S]. U.S. Department of Commerce: NIST Special Publication 800-146, 2012
[8]	Wu Jun, Xu Ming. A Comparative Analysis on the Billing Model of Public Cloud Service[J]. Telecommunications Science, 2012, 28(1): 127-132(吴俊, 徐溟. 公有云服务计费模式比较研究[J]. 电信科学, 2012, 28(1): 127-132)
[9]	Furht B, Escalante A. Handbook of Cloud Computing[M]. New York: Springer, 2010
[10]	Zhang Bo, Wu Lili, Zhou Min. The Analysis of User Behavior Based on Web Usage Mining[J].Computer Science,2006,33(8):213-214(张波, 巫莉莉, 周敏. 基于Web 使用挖掘的用户行为分析[J]. 计算机科学, 2006, 33(8): 213-214)
[11]	Li R, Guo R, Xu Z, et al. A Prefetching Model Based on Access Popularity for Geospatial Data in a Cluster-based Caching System[J]. International Journal of Geographical Information Science, 2012,26 (10): 1 831-1 844
[12]	Fisher D. Hotmap: Looking at Geographic Attention[J]. IEEE Transactions on Visualization & Computer Graphics, 2007, 13(6):1 184-1 191
[13]	Talagala N, Asami S, Patterson D, et al. The Art of Massive Storage: A Web Image Archive[J]. Computer, 2000,33(11):22-28
[14]	Wang Hao, Pan Shaoming, Peng Min, et al. Zipf-like Distribution and Its Application Analysis for Image Data Tile Request in Digital Earth[J]. Geomatics and Information Science of Wuhan University, 2010,35 (3):356-359 (王浩,潘少明,彭敏,等. 数字地球中影像数据的Zipf-like访问分布及应用分析[J]. 武汉大学学报·信息科学版,2010,35(3):356-359)
[15]	Park D J,Kim H J. Prefetch Policies for Large Objects in a Web-enabled GIS Application[J]. Data & Knowledge Engineering, 2001,37(1): 65-84
[16]	Yang Chaowei, Wu Huayi, Huang Qunying, et al. Using Spatial Principles to Optimize Distributed Computing for Enabling the Physical Science Discoveries[J]. Proceedings of the National Academy of Sciences of the United States of America,2011, 108 (14):5 498-5 503
[17]	Wang Binfei. Access Pattern Analysis and Performance Optimization of IP Network Video Service System[D]. Hefei:University of Science and Technology of China, 2010(王炳飞. IP 网络视频服务系统访问模式分析和性能优化[D]. 合肥: 中国科学技术大学, 2010)
[18]	Wu H Y, Li Z L, Zhang H W, et al. Monitoring and Evaluating Web Map Service Resources for Optimizing Map Composition over the Internet to Support Decision Making[J]. Computers and Geosciences, 2011,37(4):485-494
[19]	Li D, Zhang J, Wu H. Spatial Data Quality and Beyond [J]. International Journal of Geographical Information Science, 2012, 26(12): 2 277-2 290
[20]	Zhang Hanwu, Zhu Xinyan, Zhang Songbo. Response Time in WebGIS Based on Vector Data[J]. Journal of Geomatics, 2005, 30(2): 25-27(章汉武, 朱欣焰, 张松波. 基于矢量的 WebGIS 用户响应时间问题的若干研究[J]. 测绘信息与工程, 2005, 30(2): 25-27)

Cited By

Cited by

Periodical cited type(2)

1.	谭冰，高春春，陆洋，卢鹏，李志军. 南极威德尔海西北区域冬季海冰龙骨形态分析. 武汉大学学报(信息科学版). 2021(09): 1386-1394 .
2.	陈俊霖，周春霞，赵秋阳. 2003—2018年Byrd冰川流域冰下湖活动及水文联系——多源卫星测高数据监测结果分析. 测绘学报. 2020(05): 547-556 .

Other cited types(3)

Get Citation

PDF

XML

Article views (1689) PDF downloads (878) Cited by(5)

Research and Prediction on Time-Sequence Characteristics of Group-User Access Behavior in Public Map Service

Abstract

References

Cited by

Periodical cited type(2)

Other cited types(3)

Catalog

Related

Research and Prediction on Time-Sequence Characteristics of Group-User Access Behavior in Public Map Service

Abstract

References

Cited by

Periodical cited type(2)

Other cited types(3)

Catalog

Related

Export File

Citation

Format

Content