Data center resource mapping algorithm based on the ant colony optimization

Author

Plakunov, A. ; Kostenko, V.

Author_Institution

Fac. of Comput. Math. & Cybern., Moscow State Univ., Moscow, Russia

fYear

2014

fDate

28-29 Oct. 2014

Firstpage

1

Lastpage

6

Abstract

In this paper we present a data center resource mapping algorithm based on the ant colony optimization approach. The algorithm considers data centers to present IaaS model and can be used in a joint scheduler for all resource types. The algorithm uses ant colony optimization approach to map resource requests to physical computational nodes and data storages. The shortest path algorithm is used to map virtual channels to the data center´s physical network channels and network switches. We then present a comparison of the developed algorithm with an algorithm based on greedy and limited exhaustive search strategies.

Keywords

ant colony optimisation; cloud computing; computer centres; graph theory; greedy algorithms; scheduling; search problems; IaaS model; ant colony optimization; data center resource mapping algorithm; data storages; greedy strategy; joint scheduler; limited exhaustive search strategy; network switches; physical computational nodes; physical network channels; resource request mapping; shortest path algorithm; virtual channel mapping; Algorithm design and analysis; Ant colony optimization; Bandwidth; Heuristic algorithms; Memory; Network topology; Virtual machining; Ant Colony Optimization; Cloud Platforms; Data Centers; Virtualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Science and Technology Conference (Modern Networking Technologies) (MoNeTeC), 2014 International

Conference_Location

Moscow

Print_ISBN

978-1-4799-7593-8

Type

conf

DOI

10.1109/MoNeTeC.2014.6995596

Filename

6995596