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A Distributed Optimization Method for the Geographically Distributed Data Centres Problem


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 semiasynchronous distributed algorithm for solving such DCOPs. Preliminary results illustrate the benefits of the new method.

Speaker Name: 
Diarmuid Grimes
Speaker Bio: 
Senior Post-Doctoral Researcher
Speaker Photo: 
Seminar Date: 
Wednesday, 21 June, 2017 - 15:30 to 16:00
Seminar Location: 
WGB 2.16