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• W2619308171 abstract "The geographically distributed data centres problem (GDDC) is a naturally distributed resource allocation problem. The problem involves allocating a set of virtual machines (VM) amongst the data centres (DC) in each time period of an operating horizon. The goal is to optimize the allocation of workload across a set of DCs such that the energy cost is minimized, while respecting limitations on data centre capacities, migrations of VMs, etc. In this paper, we propose a distributed optimization method for GDDC using the distributed constraint optimization (DCOP) framework. First, we develop a new model of the GDDC as a DCOP where each DC operator is represented by an agent. Secondly, since traditional DCOP approaches are unsuited to these types of large-scale problem with multiple variables per agent and global constraints, we introduce a novel semi-asynchronous distributed algorithm for solving such DCOPs. Preliminary results illustrate the benefits of the new method." @default.
• W2619308171 created "2017-06-05" @default.
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• W2619308171 date "2017-01-01" @default.
• W2619308171 modified "2023-09-27" @default.
• W2619308171 title "A Distributed Optimization Method for the Geographically Distributed Data Centres Problem" @default.
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• W2619308171 doi "https://doi.org/10.1007/978-3-319-59776-8_12" @default.
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