Usage Report india

• Period: April 01 – June 30, 2014
• Hostname: india.futuregrid.org
• Services: openstack, eucalyptus
• Metrics: VMs count, Users count, Wall time (hours), Distribution by wall time, project, project leader, and institution, and systems

Histogram

Summary (Monthly)

Figure 1: Average monthly usage data (wall time (hour), launched VMs, users)

This mixed chart represents average monthly usage as to wall time (hour), the number of VM instances and active users.

• Period: April 01 – June 30, 2014

• Cloud(IaaS): openstack, eucalyptus

• Hostname: india

• Metric:

  • Runtime (Wall time hours): Sum of time elapsed from launch to termination of VM instances
  • Count (VM count): The number of launched VM instances
  • User count (Active): The number of users who launched VMs

Summary (Daily)

Figure 2: Users count

This time series chart represents daily active user count for cloud services and shows historical changes during the period.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

Figure 3: VMs count

This time series chart represents the number of daily launched VM instances for cloud services and shows historical changes during the period.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

Figure 4: Wall time (hours)

This time series chart represents daily wall time (hours) for cloud services and shows historical changes during the period.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

Distribution

Figure 5: VM count by wall time

This chart illustrates usage patterns of VM instances in terms of running wall time.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

Figure 6: VMs count by project

This chart illustrates the proportion of launched VM instances by project groups. The same data in tabular form follows.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

VMs count by project

Project	Value
fg-405:Spring 2014 CSCI-B649 Cloud Computing MOOC for residential and online students	367
fg-367:Optimize rapid deployment and updating of VM images at the remote compute cluster	151
fg-13:FutureGrid Systems Development and Prototyping	143
fg-418:Course: Cloud Computing Class - fourth edition	129
fg-7:SDCI NMI Improvement: Pegasus: From Concept to Execution- - -Mapping Scientific Workflows onto the National Cyberinfrastructure	69
fg-288:Federating HPC, Cyberinfrastructure and Clouds using CometCloud	42
fg-314:User-friendly tools to play with cloud platforms	38
fg-224:Nimbus Auto Scale	37
fg-168:Next Generation Sequencing in the Cloud	33
fg-384:Graph/network analysis Resource manager	28
fg-136:JGC-DataCloud-2012 paper experiments	24
fg-174:RAIN: FutureGrid Dynamic provisioning Framework	23
fg-368:Course: Fall 2013 P434 Distributed Systems Undergraduate Course	17
fg-333:Intrusion Detection and Prevention for Infrastructure as a Service Cloud Computing System	12
fg-214:Mining Interactions between Network Community Structure and Information Diffusion	12
fg-175:GridProphet, A workflow execution time prediction system for the Grid	11
fg-362:Course: Cloud Computing and Storage (UF)	10
fg-382:Reliability Analysis using Hadoop and MapReduce	7
fg-316:Course: Cloud Computing Class - third edition	5
fg-10:TeraGrid XD TIS(Technology Insertion Service) Technology Evaluation Laboratory	4
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters	3
fg-165:The VIEW Project	3
fg-248:Geophysical fluid dynamics education and research	3
fg-411:ILS-Z604 Big Data Analytics for Web and Text - SP14 Group #2	2
fg-432:2014 Topics in Parallel Computation	2
fg-110:FutureGrid Systems Development	1
fg-20:Development of an information service for FutureGrid	1
fg-42:SAGA	1
fg-45:Experiments in Distributed Computing	1
fg-372:Mobile Device Computation Offloading over SocialVPNs	1

Figure 7: VMs count by project leader

This chart also illustrates the proportion of launched VM instances by project Leader. The same data in tabular form follows.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

VMs count by project leader

Projectleader	Value
Judy Qiu	384
Massimo Canonico	172
Jan Balewski	151
Sharif Islam	143
Mats Rynge	93
Javier Diaz Montes	42
Pierre Riteau	37
Jonathan Klinginsmith	33
Tirtha Bhattacharjee	28
Gregor von Laszewski	23
Jessie Walker	12
Yong-Yeol Ahn	12
Thomas Fahringer	11
Andy Li	10
Carl Walasek	7
Renato Figueiredo	4
John Lockman	4
Glenn Flierl	3
Shiyong Lu	3
Shantenu Jha	2
Heru Suhartanto	2
Trevor Edelblute	2
Gary Miksik	1
Hyungro Lee	1

Figure 8: VMs count by institution

This chart illustrates the proportion of launched VM instances by Institution. The same data in tabular form follows.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

VMs count by institution

Institution	Value
Indiana University, School of Informatics and Computing	384
Indiana University	213
University of Piemonte Orientale, Computer Science Department	172
Massachusetts Institute of Technology, Laboratory for Nuclear Sc	151
USC	93
Rutgers	42
University of Chicago	37
Virginia Bioinformatics Institute, Virginia Polytechnic Institut	28
University of Arkansas at Pine Bluff , Computer Science	12
University of Innsbruck	11
University of Florida, Department of Electrical and Computer Eng	10
University of the Sciences , Mathematics, Physics, and Statistic	7
University of Texas at Austin	4
Massachusetts Institute of Technology	3
Wayne State University	3
University of Florida	3
Louisiana State University	2
Indiana University, Department of Information & Library Science,	2
Universitas Indonesia, Faculty of Computer Science	2
University of Florida, Electrical and Computer Engineering	1

Figure 9: Wall time (hours) by project leader

This chart illustrates proportionate total run times by project leader.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

System information

System information shows utilization distribution as to VMs count and wall time. Each cluster represents a compute node.

Figure 10: VMs count by systems (compute nodes) in Cluster (india)

This column chart represents VMs count among systems.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india

Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (india)

This column chart represents wall time among systems.

• Period: April 01 – June 30, 2014
• Cloud(IaaS): openstack, eucalyptus
• Hostname: india