Grant: Strategic Projects - Group
University of Waterloo
$173,660.00
Cross-layer Resource Management for Cloud Computing Platforms
FY 2013-14
Summary
Cloud computing platforms represent the fastest growing component of the ICT infrastructure, both in terms ofcomputing resources and energy consumption. Clouds are characterized by a hierarchy of parallel computing,starting from networks of data centers to the multi-core server processors within a data center, and by theheterogeneity of applications, job sizes and hardware resources.Adaptive power and resource management are critical for improving the power efficiency of next-generationcloud computing platforms, while providing quality-of-service (QoS) guarantees to each user. Our research willaddress this challenge by adopting a unique cross-layer approach in which the cloud computing hardware andinfrastructure is jointly optimized with data center and network-wide resource allocation and managementpolicies. We will focus specifically on the scalability of the proposed solutions, given the increasinglydistributed and parallel nature of cloud computing services, and on robustness to large variations in client-sideservice requests and changing infrastructure.The complexity of the adaptive power management problem, both at the node-level and at the system-level,scales with the degree of parallelism available on these platforms. Scalability represents an entirely newchallenge that has not been adequately addressed before in the context of power management for parallelcomputing.Our research will involve modelling, analysis, and the development of a simulation infrastructure as well asdesign methodologies. The research will bring together techniques and models from networking, adaptivealgorithms, scheduling techniques for multi-processor systems, and the development of simulators that span alllayers of the system.
Program
Strategic Projects - Group
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
413461-2011
Name nom
Mazumdar, Ravi
Department département
Electrical & Computer Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2013
Competition year année de concours
2011
Award amount
173660
Program id
STPGP
Program name en
Strategic Projects - Group
Program name fr
Projets stratégiques - De groupe
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1567
Committee name en
Strategic Projects Selection Panel - ICT
Committee name fr
Comité de sélection des projets stratégiques - ICT
Area of application code
804
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Communication systems and services (planning, organization, services)
Area of application fr
Systèmes et services de communications (planification, organisation et services)
Research subject code
2710
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information systems design
Research subject fr
Conception de systèmes d'information
Partie
3
Nb partie
3
Application title
Cross-layer Resource Management for Cloud Computing Platforms
Keyword
NSERC
Application summary
Cloud computing platforms represent the fastest growing component of the ICT infrastructure, both in terms ofcomputing resources and energy consumption. Clouds are characterized by a hierarchy of parallel computing,starting from networks of data centers to the multi-core server processors within a data center, and by theheterogeneity of applications, job sizes and hardware resources.Adaptive power and resource management are critical for improving the power efficiency of next-generationcloud computing platforms, while providing quality-of-service (QoS) guarantees to each user. Our research willaddress this challenge by adopting a unique cross-layer approach in which the cloud computing hardware andinfrastructure is jointly optimized with data center and network-wide resource allocation and managementpolicies. We will focus specifically on the scalability of the proposed solutions, given the increasinglydistributed and parallel nature of cloud computing services, and on robustness to large variations in client-sideservice requests and changing infrastructure.The complexity of the adaptive power management problem, both at the node-level and at the system-level,scales with the degree of parallelism available on these platforms. Scalability represents an entirely newchallenge that has not been adequately addressed before in the context of power management for parallelcomputing.Our research will involve modelling, analysis, and the development of a simulation infrastructure as well asdesign methodologies. The research will bring together techniques and models from networking, adaptivealgorithms, scheduling techniques for multi-processor systems, and the development of simulators that span alllayers of the system.