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Resource Management in Utility and Cloud ComputingEfficient and Fair Resource Trading Management

Resource Management in Utility and Cloud Computing: Efficient and Fair Resource Trading Management [In this chapter, we investigate the resource trading problem in a utility and cloud computing setting where multiple tenants communicate in a Peer-to-Peer (P2P) fashion. Enabling resource trading in cloud unleashes the untapped cloud resources, thus presents a flexible solution for managing resource allocation. However, finding an efficient and fair resource allocation is challenging mainly due to the heterogeneity of resource valuations. Our work first develops a utility-oriented model to support resource negotiation and trading. Based on this model, we adopt a multiagent-based technique that allows a group of autonomous tenants to reach an efficient and fair resource allocation. Further, we add budget limitation to each tenant and propose a directed hypergraph model to facilitate resource trading amongst heterogeneous tenants. We develop a directed hypergraph model to facilitate trading decision making, and design a class of heuristic-based distributed resource trading protocols in favor of different performance metrics.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Resource Management in Utility and Cloud ComputingEfficient and Fair Resource Trading Management

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Publisher
Springer New York
Copyright
© The Author(s) 2013
ISBN
978-1-4614-8969-6
Pages
37 –56
DOI
10.1007/978-1-4614-8970-2_3
Publisher site
See Chapter on Publisher Site

Abstract

[In this chapter, we investigate the resource trading problem in a utility and cloud computing setting where multiple tenants communicate in a Peer-to-Peer (P2P) fashion. Enabling resource trading in cloud unleashes the untapped cloud resources, thus presents a flexible solution for managing resource allocation. However, finding an efficient and fair resource allocation is challenging mainly due to the heterogeneity of resource valuations. Our work first develops a utility-oriented model to support resource negotiation and trading. Based on this model, we adopt a multiagent-based technique that allows a group of autonomous tenants to reach an efficient and fair resource allocation. Further, we add budget limitation to each tenant and propose a directed hypergraph model to facilitate resource trading amongst heterogeneous tenants. We develop a directed hypergraph model to facilitate trading decision making, and design a class of heuristic-based distributed resource trading protocols in favor of different performance metrics.]

Published: Sep 19, 2013

Keywords: Resource Trading; Hypernode; Envy Relations; Neighbor Peers; Payments Range

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