Deadlines
Paper submission due: November 24, 2013
Notification of acceptance: December 22, 2013
Final camera-ready papers due: January 17, 2012
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Description
Cloud computing promises unlimited, cost-effective and agile
computing resources for users. However, this new computing paradigm also
poses a unique set of challenges to both cloud providers and users. On
the one hand, cloud providers need to ensure that resources being
provided are highly available and deliver high performance, while
optimizing cloud infrastructure to reduce their operational costs. On
the other hand, cloud users need to ensure that their applications
receive the best performance from the cloud, while maintaining their
budgetary constraints and the terms of any Service Level Agreements
(SLAs) they have with their cloud providers.
Given the scale of cloud deployment, systematic analytical
approaches are critically needed to provide insights to both providers
and users to achieve their respective goals. For instance, cloud
providers need to constantly be aware of the running status and/or
anomalies in functionality from their cloud, to be able to quickly fix
any issues that may arise, to adjust physical resource allocations to
ensure that their customers get best performance, or plan which services
to offer to get the best return on investment. Similarly, cloud users
need to understand the workload to be deployed into the cloud, plan the
deployment in a cost-effective way, or ascertain the flexibility and
service quality provided by different cloud environments and use this to
decide their deployment strategy. Analytics can play a pivotal role in
all these scenarios. By gathering insights from the large amount of data
from the cloud, both cloud providers and consumers can develop
analytical approaches to achieving their respective objectives in spite
of the scale that clouds provide.
The purpose of this workshop is to provide a forum for researchers
in the related fields to exchange ideas, and share their experiences in
developing analytics to better deploy, operate and use the cloud.
Specifically, we seek and wish to foster research contributions that
draw on statistical analysis, analytical modeling, and machine learning
to develop novel solutions in this problem area.
Topics of Interest
Topics of interest include, but are not limited to, the following:
• Cloud workload measurement and analysis
• Workload behavior modeling
• Analytics for application deployment in cloud
• Performance modeling of cloud applications
• Cloud performance benchmarking
• Resource utilization optimization
• Tracing and problem identification in cloud systems
• Log and monitoring data analysis
• Problem diagnosis and troubleshooting
• Security and intrusion detection
• Reliability engineering, fault management, and disaster recovery
• Design and implementation of analytics systems
• Business optimization in cloud operations
Organizers
Co-Chairs:
Shu Tao (IBM T J Watson Research)
Rich Wolski (UCSB)
Publicity Chair:
Rahul Singh (IBM T J Watson Research)
Program Committee (tentative)
Theophilus Benson (Duke University)
Yanpei Chen (Cloudera)
Yuan Chen (HP Labs)
David Irwin (UMass, Amherst)
Thilo Kielmann (VU University, Amsterdam)
Ningfang Mi (Northeastern University)
Lavanya Ramakrishnan (Lawrence Berkeley National Lab)
Prashant Shenoy (UMass, Amherst)
Christopher Charles Stewart (Ohio State University)
Evgenia Smirni (William and Mary)
Chunqiang Tang (Facebook)
Jon Weissman (University of Minnesota)
Timothy Wood (George Washington University)
Lydia Chen (IBM Zurich Research)
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