In this paper, we introduce a generalization of the vector bin packing problem, where the bins have variable sizes. This generalization can be used to model virtual machine placement problems. In particular, we study the machine reassignment problem. We propose several greedy heuristics for the variable size vector bin packing problem and show that they are flexible and can be adapted to handle additional constraints. We highlight some structural properties of the machine reassignment problem and use them to adapt our heuristics. We present numerical results on both randomly generated instances and Google realistic instances for the machine reassignment problem
Due to copyright restrictions, the access to the full text of this article is only available via sub...
AbstractThe Bin Packing Problem's purpose (BPP) is to find the minimum number of bins needed to pack...
International audienceA datacenter can be viewed as a dynamic bin packing system where servers host ...
International audienceIn this paper, we introduce a generalization of the vector bin packing problem...
In this paper, we introduce a generalization of the vector bin packing problem, where the bins have ...
Details our solution (team J19, qualified) to the EURO/ROADEF Challenge 2012, proposed by Google.Int...
International audienceThis paper proposes an efficient Multi-Start Iterated Local Search for Packing...
Fundamental problems in operational research are vector scheduling and vector bin packing where a se...
This paper proposes an efficient Multi-Start Iterated Local Search for Packing Problems (MS-ILS-PPs)...
VM Placement algorithms play a crucial role in determining data center utilisation and power consump...
Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer line...
pages 19-35 - Chapter 2International audienceResource management in datacenters involves assigning v...
To date, virtual machine (VM) placement has traditionally been viewed as a bin packing problem where...
The variable sized bin packing problem is a generalisation of the one-dimensional bin packing proble...
International audienceThis paper proposes a new method for solving the Machine Reassignment Problem ...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
AbstractThe Bin Packing Problem's purpose (BPP) is to find the minimum number of bins needed to pack...
International audienceA datacenter can be viewed as a dynamic bin packing system where servers host ...
International audienceIn this paper, we introduce a generalization of the vector bin packing problem...
In this paper, we introduce a generalization of the vector bin packing problem, where the bins have ...
Details our solution (team J19, qualified) to the EURO/ROADEF Challenge 2012, proposed by Google.Int...
International audienceThis paper proposes an efficient Multi-Start Iterated Local Search for Packing...
Fundamental problems in operational research are vector scheduling and vector bin packing where a se...
This paper proposes an efficient Multi-Start Iterated Local Search for Packing Problems (MS-ILS-PPs)...
VM Placement algorithms play a crucial role in determining data center utilisation and power consump...
Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer line...
pages 19-35 - Chapter 2International audienceResource management in datacenters involves assigning v...
To date, virtual machine (VM) placement has traditionally been viewed as a bin packing problem where...
The variable sized bin packing problem is a generalisation of the one-dimensional bin packing proble...
International audienceThis paper proposes a new method for solving the Machine Reassignment Problem ...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
AbstractThe Bin Packing Problem's purpose (BPP) is to find the minimum number of bins needed to pack...
International audienceA datacenter can be viewed as a dynamic bin packing system where servers host ...