ABSTRACT
Contents 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 6.2 Low-Carbon Network and Resource Management . . . . . . . . . . . . . . . . . 140 6.3 Virtualized Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 6.4 ICT Energy Consumption Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 6.5 Proposed System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 6.6 Carbon-Aware Resource Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 6.7 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 6.8 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Using smart grids to build low-carbon networks is one of the most challenging topics in the ICT industry. The GreenStar Network is the first worldwide initiative completely powered by renewable energy sources across Canada. Smart grid techniques are deployed to migrate data centers across network nodes according to energy source availabilities, thus reducing CO2 emissions to minimal. Such flexibility requires a scalable resource management support, achieved by virtualization enabling the sharing, aggregation, and dynamic configuration of a large variety of resources. Such a virtualized management is based on an efficient resource description and discovery framework, dealing with a large number of heterogeneous elements and the diversity of architectures and protocols. In this chapter, we present an ontology-based resource description framework, developed particularly for ICT energy management, where the focus is on energy-related semantics of resources and their properties. We propose then a scalable resource discovery method in large and dynamic collections of ICT resources, based on semantics similarity inside a federated index using a Bayesian belief network. The proposed framework allows users to determine the cleanest resources to fulfill their requirements, regarding the energy source availabilities. Experimental results are shown to compare the proposed method with a traditional one in terms of GHG emission reductions.
