@inproceedings{b050d7a6226141d5846d1ef12e781959,
title = "Evolutionary multiobjective optimization for Green clouds",
abstract = "As Internet data centers (IDCs) have been increasing in scale and complexity, they are currently a significant source of energy consumption and CO2 emission. This paper proposes and evaluates a new framework to operate a federation of IDCs in a {"}green{"} way. The proposed framework, called Green Monster, dynamically moves services (i.e., workload) across IDCs for increasing renewable energy consumption while maintaining their performance. It makes decisions of service migration and placement with an evolutionary multi-objective optimization algorithm (EMOA) that evolves a set of solution candidates through global and local search processes. The proposed EMOA seeks the Pareto-optimal solutions by balancing the trade-offs among conicting optimization objectives such as renewable energy consumption, cooling energy consumption and response time performance.",
keywords = "Cloud computing, Evolutionary multiobjective optimization, Internet data centers, Renewable energy, Sustainability",
author = "Phan, {Dung H.} and Junichi Suzuki and Raymond Carroll and Sasitharan Balasubramaniam and William Donnelly and Dmitri Botvich",
year = "2012",
doi = "10.1145/2330784.2330788",
language = "English",
isbn = "9781450311786",
series = "GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion",
publisher = "Association for Computing Machinery (ACM)",
pages = "19--26",
booktitle = "GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion",
address = "United States",
note = "null ; Conference date: 07-07-2012 Through 11-07-2012",
}
