CLOUDLIGHTNING
A framework for a self-organising and self-managing heterogeneous cloud
Theo Lynn (DCU)
Huanhuan Xiong (University College Cork)
Dapeng Dong (University College Cork)
Bilal Momani (University College Cork)
George Gravvanis (Democritus University of Thrace)
Christos Filelis-Papadopoulos (Democritus University of Thrace)
Anne Elster (Norwegian University of Science and Technology (NTNU))
Malik Muhammad Zaki Murtaza Khan (Norwegian University of Science and Technology (NTNU))
Dimitrios Tzovaras (Centre for Research and Technology)
Konstantinos Giannoutakis (Centre for Research and Technology)
Dana Petcu (West University of Timisoara (UVT))
Marian Neagul (West University of Timisoara (UVT))
Ioan Dragon (West University of Timisoara (UVT))
Perumal Kuppudayar (Intel Ireland Ltd.)
Suryanarayanan Natarajan (Intel Ireland Ltd.)
Michael McGrath (Intel Ireland Ltd.)
Georgi Gaydadjiev (Maxeler)
Tobias Becker (Maxeler)
Anna Gourinovitch (DCU)
David Kenny (DCU)
John Morrison (University College Cork)
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Abstract
As clouds increase in size and as machines of different types are added to the infrastructure in order to maximize performance and power efficiency, heterogeneous clouds are being created. However, exploiting different architectures poses significant challenges. To efficiently access heterogeneous resources and, at the same time, to exploit these resources to reduce application development effort, to make optimisations easier and to simplify service deployment, requires a re-evaluation of our approach to service delivery. We propose a novel cloud management and delivery architecture based on the principles of self-organisation and self-management that shifts the deployment and optimisation effort from the consumer to the software stack running on the cloud infrastructure. Our goal is to address inefficient use of resources and consequently to deliver savings to the cloud provider and consumer in terms of reduced power consumption and improved service delivery, with hyperscale systems particularly in mind. The framework is general but also endeavours to enable cloud services for high performance computing. Infrastructure-as-a-Service provision is the primary use case, however, we posit that genomics, oil and gas exploration, and ray tracing are three downstream use cases that will benefit from the proposed architecture.
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