Cloud computing platform for GIS image processing in U-city

Ubiquitous city (U-city) is a city with ubiquitous information technology that enables citizens to access the converged information anywhere and anytime. A lot of compute power are required in U-city, because large amount of data should be processed in real-time. Cloud computing enables users to use the abstracted and virtualized computing resources and to process huge amount of information without having their own computing power. This paper presents a GIS image processing platform that uses cloud computing. It finds and selects optimal computing resources for applications and run virtual machines to execute the applications. In this paper, we explain the parallel air pollution map generation as a use case for the suggested platform and show how efficiently it processes the massive data.

[1]  Irfan Habib,et al.  Virtualization with KVM , 2008 .

[2]  Yongwoo Lee,et al.  A Job Management System for a Large Scale Grid System , 2007, 7th IEEE International Conference on Computer and Information Technology (CIT 2007).

[3]  Borja Sotomayor,et al.  Combining batch execution and leasing using virtual machines , 2008, HPDC '08.

[4]  Sang Ho Lee,et al.  Towards ubiquitous city: concept, planning, and experiences in the Republic of Korea , 2008 .

[5]  Andrew Warfield,et al.  Live migration of virtual machines , 2005, NSDI.

[6]  Warren Smith,et al.  Scheduling with advanced reservations , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[7]  Rajkumar Buyya,et al.  Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities , 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

[8]  Ming Q. Xu Effective metacomputing using LSF Multicluster , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[9]  Klara Nahrstedt,et al.  A distributed resource management architecture that supports advance reservations and co-allocation , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[10]  Chang-Sung Jeong,et al.  Unified Ubiquitous Middleware for U-City , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[11]  Ian T. Foster,et al.  Condor-G: A Computation Management Agent for Multi-Institutional Grids , 2004, Cluster Computing.

[12]  David Abramson,et al.  High performance parametric modeling with Nimrod/G: killer application for the global grid? , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[13]  Elias N. Houstis,et al.  Towards a Pervasive Grid , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[14]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[15]  Borja Sotomayor,et al.  Virtual Infrastructure Management in Private and Hybrid Clouds , 2009, IEEE Internet Computing.

[16]  M. Weiser The Computer for the Twenty-First Century , 1991 .