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Usage Report india

  • Period: October 01 – December 23, 2013
  • 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)

Average Monthly Usage Data (Wall time, Launched VMs, Users)
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: October 01 – December 23, 2013

  • 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)

Users count (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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
VMs count (daily)
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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
Wall time (hours, daily)
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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india

Distribution

VM count by wall time
Figure 5: VM count by wall time
This chart illustrates usage patterns of VM instances in terms of running wall time.
  • Period: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
VMs count by project
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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
VMs count by project
Project Value
fg-172:Cloud-TM 685
fg-82:FG General Software Development 222
Others 209
fg-316:Course: Cloud Computing Class - third edition 108
fg-143:Course: Cloud Computing for Data Intensive Science Class 47
fg-213:Course: Cloud Computing class - second edition 41
fg-54:Investigating cloud computing as a solution for analyzing particle physics data 22
fg-179:GPCloud: Cloud-based Automatic Repair of Real-World Software Bugs 17
fg-3:Survey of Open-Source Cloud Infrastructure using FutureGrid Testbed 16
fg-233:CINET - A Cyber-Infrastructure for Network Science 5
fg-42:SAGA 4
fg-253:Characterizing Performance of Infrastructure Clouds 4
fg-201:ExTENCI Testing, Validation, and Performance 3
fg-1:Peer-to-peer overlay networks and applications in virtual networks and virtual clusters 3
fg-136:JGC-DataCloud-2012 paper experiments 3
fg-60:Wide area distributed file system for MapReduce applications on FutureGrid platform 3
fg-149:Metagenome analysis of benthic marine invertebrates 2
fg-189:Pegasus development and improvement platform 1
fg-20:Development of an information service for FutureGrid 1
VMs count by project leader
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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
VMs count by project leader
Projectleader Value
Paolo Romano 685
Gregor von Laszewski 222
Others 209
Massimo Canonico 149
Judy Qiu 47
Randall Sobie 22
Claire Le Goues 17
Tak-Lon Wu 16
Keith Bisset 5
Mats Rynge 4
Shantenu Jha 4
Paul Marshall 4
Preston Smith 3
Lizhe Wang 3
Renato Figueiredo 3
Jason Kwan 2
Hyungro Lee 1
VMs count by institution
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: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
VMs count by institution
Institution Value
INESC ID 685
Indiana University 289
Others 209
University of Piemonte Orientale, Computer Science Department 108
University of Piemonte Orientale 41
University of Victoria 22
University of Virginia 17
Virginia Tech 5
USC 4
Louisiana State University 4
University of Colorado at Boulder 4
Purdue University 3
University of Florida 3
University of Utah 2
Wall time (hours) by project leader
Figure 9: Wall time (hours) by project leader
This chart illustrates proportionate total run times by project leader.
  • Period: October 01 – December 23, 2013
  • 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.

VMs count by systems in Cluster (india)
Figure 10: VMs count by systems (compute nodes) in Cluster (india)
This column chart represents VMs count among systems.
  • Period: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india
Wall time (hours) by systems in Cluster (india)
Figure 11: Wall time (hours) by systems (compute nodes) in Cluster (india)
This column chart represents wall time among systems.
  • Period: October 01 – December 23, 2013
  • Cloud(IaaS): openstack, eucalyptus
  • Hostname: india