Matchmaking of IaaS cloud computing offers leveraging linked data

Authors:
Maciej Zaremba;Sami Bhiri;Tomas Vitvar;Manfred Hauswirth
Affiliations:
National University of Ireland, Galway, Ireland;National University of Ireland, Galway, Ireland;Czech Technical University in Prague;National University of Ireland, Galway, Ireland
Venue:
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Year:
2013

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Abstract

Cloud Computing is an elastic execution environment becoming the dominating solution for scalable and on-demand computing, and a large market of cloud providers has recently emerged. IaaS is a realisation of the Cloud Computing at the level of processing, storage and networking resources. Currently, users lack a consolidated view of the IaaS market and it is time-consuming and cumbersome to identify the most suitable IaaS offers. IaaS services are highly configurable and their properties are often request-dependent and change dynamically. In this paper we introduce a service matchmaking approach for IaaS. We present models to define expressive search requests and IaaS descriptions which are grounded in lightweight semantic formalisms of RDF and SPARQL, and use Linked Data. Our approach supports dynamic generation of IaaS offers, and their filtering and ranking. We provide a proof-of-concept matchmaker operating on expressive search requests and descriptions of nineteen IaaS services including: Amazon EC2, Google Compute Engine, ElasticHosts, CloudSigma, and Joyent-Cloud.