Implementation and Usability Evaluation of a Cloud Platform for Scientific Computing as a Service (SCaaS)

Scientific computing requires simulation and visualization involving large data sets among collaborating teams. Cloud platforms offer a promising solution via ScaaS. We report on the architecture, implementation and User Experience (UX) evaluation of one such SCaaS platform implementing TOUGH2V2.0, a numerical simulator for sub-surface fluid and heat flow, offered as a service. Results from example simulations, with virtualization of workloads in a multi-tenant, Virtual Machine (VM)-based cloud platform, are presented. These include fluid production from a geothermal reservoir, diffusive and advective spreading of contaminants, radial flow from a CO2 injection well and gas diffusion of a chemical through porous media. Prepackaged VM pools deployed autonomically ensure that sessions are provisioned elastically on demand. Users can access data-intensive visualizations via a web-browser. Authentication, user state and sessions are managed securely via an Access Gateway, to autonomically redirect and manage the workflows when multiple concurrent users are accessing their own sessions. Usability in the cloud and the traditional desktop are comparatively assessed, using several UX metrics. Simulated network conditions of different quality were imposed using a WAN emulator. Usability was found to be good for all the simulations under even moderately degraded network quality, as long as latency was not well above 100 ms. Hosting of a complex scientific computing application on an actual, global Enterprise cloud platform (as opposed to earlier remoting platforms) and its usability assessment, both presented for the first time, are the essential contributions of this work.

[1]  Robert B. Miller,et al.  Response time in man-computer conversational transactions , 1899, AFIPS Fall Joint Computing Conference.

[2]  K. Pruess,et al.  TOUGH2 User's Guide Version 2 , 1999 .

[3]  Douglas Thain,et al.  Distributed computing in practice: the Condor experience , 2005, Concurr. Pract. Exp..

[4]  F. Gagliardi,et al.  EGEE - providing a production quality grid for e-science , 2005, 2005 IEEE International Symposium on Mass Storage Systems and Technology.

[5]  Charles E. Catlett.  TeraGrid: A Foundation for US Cyberinfrastructure , 2005, NPC.

[6]  Jorge Luis Rodriguez,et al.  The Open Science Grid , 2005 .

[7]  Terrence Fernando,et al.  Dynamism and Data Management in Distributed, Collaborative Working Environments , 2008, COOP.

[8]  Marian Bubak,et al.  ViroLab Virtual Laboratory , 2008 .

[9]  Lizhe Wang,et al.  Scientific Cloud Computing: Early Definition and Experience , 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

[10]  Hajime Yamamoto,et al.  PetraSim: A Graphical User Interface for the TOUGH2 Family of Multiphase Flow and Transport Codes , 2008 .

[11]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[12]  Valerio Pascucci,et al.  Visualization for data-intensive science , 2009, The Fourth Paradigm.

[13]  Rajkumar Buyya,et al.  High-Performance Cloud Computing: A View of Scientific Applications , 2009, 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks.

[14]  Valerio Pascucci,et al.  Scientific Data Management Challenges in High-Performance Visual Data Analysis , 2009, Scientific Data Management.

[15]  Prasad Saripalli,et al.  Load Prediction and Hot Spot Detection Models for Autonomic Cloud Computing , 2011, 2011 Fourth IEEE International Conference on Utility and Cloud Computing.