Study of Smart Transportation Data Center Virtualization Based on VMware vSphere and Parallel Continuous Query Algorithm over Massive Data Streams

Abstract There are various shortages of the traditional data center in cost, resource utilization, power consumption and operation. This paper studies the development trend of the virtual data center and its technical advantages, proposes a scheme of virtual system of smart transportation data center based on VMware vSphere. At the same time, oriented on requirements of traffic data stream management in city smart transportation system under the environment of cloud computing, aimed at massive, multi-source, real-time, dynamic uncertain data stream sent back from all kinds of cross regional intensive control perception device, this paper analyses the characteristics and correlation of actual city traffic operation and traffic data flow, researches evolution mechanism of uncertain data; construct traffic data flow model based on ontology, core metadata and theory of constraints. And on this basis, this paper uses virtualization and large data sets of parallel processing, considers load balancing and adaptive mechanism, combines fuzzy theory and dynamic multi object, multi constrained decision theory, to seek the efficient query algorithm for dynamic, complex and continuous transportation data stream.

[1]  Jian Tang,et al.  Survivable Virtual Infrastructure Mapping in Virtualized Data Centers , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[2]  Xiang Lian,et al.  Probabilistic ranked queries in uncertain databases , 2008, EDBT '08.

[3]  Xiang Lian,et al.  Top-k dominating queries in uncertain databases , 2009, EDBT '09.

[4]  Lisandro Zambenedetti Granville,et al.  Data Center Network Virtualization: A Survey , 2013, IEEE Communications Surveys & Tutorials.

[5]  Jeffrey Xu Yu,et al.  Sliding-window top-k queries on uncertain streams , 2008, Proc. VLDB Endow..

[6]  Christian Böhm,et al.  Probabilistic skyline queries , 2009, CIKM.

[7]  Mikhail J. Atallah,et al.  Computing all skyline probabilities for uncertain data , 2009, PODS.

[8]  Yonggang Wen,et al.  Energy efficiency and server virtualization in data centers: An empirical investigation , 2012, 2012 Proceedings IEEE INFOCOM Workshops.

[9]  Stefano Giordano,et al.  Virtual machines migration in a cloud data center scenario: An experimental analysis , 2013, 2013 IEEE International Conference on Communications (ICC).

[10]  Mohamed A. Soliman,et al.  Top-k Query Processing in Uncertain Databases , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[11]  Yonggang Wen,et al.  An Empirical Investigation of the Impact of Server Virtualization on Energy Efficiency for Green Data Center , 2013, Comput. J..

[12]  Evgenia Smirni,et al.  State-of-the-practice in data center virtualization: Toward a better understanding of VM usage , 2013, 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN).

[13]  Mohammad Reza Ahmadi,et al.  Performance evaluation of server virtualization in data center applications , 2010, 2010 5th International Symposium on Telecommunications.

[14]  Vijayaraghavan Soundararajan,et al.  The impact of management operations on the virtualized datacenter , 2010, ISCA '10.

[15]  Azizah Abdul Rahman,et al.  Virtualization Implementation Model for Cost Effective & Efficient Data Centers , 2012, ArXiv.

[16]  S. T Widyawan,et al.  Total Cost of Ownership Formulation Analysis forVirtualization Data Center in University , 2013 .

[17]  Feifei Li,et al.  Efficient Processing of Top-k Queries in Uncertain Databases with x-Relations , 2008, IEEE Transactions on Knowledge and Data Engineering.

[18]  Bin Jiang,et al.  Probabilistic Skylines on Uncertain Data , 2007, VLDB.

[19]  Nick McKeown,et al.  Optimizing a virtualized data center , 2011, SIGCOMM 2011.

[20]  Jian Pei,et al.  Efficiently Answering Probabilistic Threshold Top-k Queries on Uncertain Data , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[21]  Ihab F. Ilyas,et al.  A survey of top-k query processing techniques in relational database systems , 2008, CSUR.

[22]  Jeffrey Xu Yu,et al.  Probabilistic Skyline Operator over Sliding Windows , 2009, 2009 IEEE 25th International Conference on Data Engineering.