DocumentCode
172816
Title
Exact and Heuristic Graph-Coloring for Energy Efficient Advance Cloud Resource Reservation
Author
Ghribi, Chaima ; Zeghlache, Djamal
Author_Institution
Inst. Mines-Telecom, Telecom SudParis, Evry, France
fYear
2014
fDate
June 27 2014-July 2 2014
Firstpage
112
Lastpage
119
Abstract
This paper presents a new graph-coloring model for advance resource reservation with minimum energy consumption in heterogeneous IaaS cloud data centers. We start with an exact integer linear programming (ILP) formulation which generalizes the graph coloring problem and follow with a fast Energy Efficient Graph Pre-coloring (EEGP) heuristic to address the scalability and to reduce convergence times. The results of performance evaluation and comparisons of EEGP with our exact algorithm and the Haizea advance reservation (AR) algorithm demonstrate the efficiency of EEGP for the energy efficient advance resource reservation problem. Our proposed EEGP heuristic is shown to perform very close to optimal, to scale well with problem size and to achieve convergence times close to the simple and fast AR algorithm that is however suboptimal.
Keywords
cloud computing; computer centres; graph colouring; integer programming; linear programming; power aware computing; EEGP heuristic; Haizea AR algorithm; Haizea advance reservation algorithm; ILP formulation; convergence time reduction; energy efficient advance cloud resource reservation problem; energy efficient graph precoloring heuristic; exact heuristic graph-coloring model; heterogeneous IaaS cloud data centers; integer linear programming formulation; minimum energy consumption; performance evaluation; scalability issue; Brain modeling; Color; Computational modeling; Heuristic algorithms; Image color analysis; Measurement; Servers; Advance Resource reservation; Energy efficiency; Graph-coloring; Heterogeneous Cloud Data Centers;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
Conference_Location
Anchorage, AK
Print_ISBN
978-1-4799-5062-1
Type
conf
DOI
10.1109/CLOUD.2014.25
Filename
6973731
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