BEAUMONT, Olivier; EYRAUD-DUBOIS, Lionel; REJEB, Hejer; THRAVES-CARO, Christopher

doi:10.1109/TPDS.2012.175

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Licence d’utilisation du document

BEAUMONT, Olivier
Algorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]

EYRAUD-DUBOIS, Lionel
Algorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]

REJEB, Hejer
Algorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
Laboratoire Bordelais de Recherche en Informatique [LaBRI]

Langue

Article de revue

Ce document a été publié dans

IEEE Transactions on Parallel and Distributed Systems. 2012

Institute of Electrical and Electronics Engineers

Résumé en anglais

In this paper, we consider the problem of assigning a set of clients with demands to a set of servers with capacities and degree constraints. The goal is to find an allocation such that the number of clients assigned to a server is smaller than the server's degree and their overall demand is smaller than the server's capacity, while maximizing the overall throughput. This problem has several natural applications in the context of independent tasks scheduling or virtual machines allocation. We consider both the \emph{offline} (when clients are known beforehand) and the \emph{online} (when clients can join and leave the system at any time) versions of the problem. We first show that the degree constraint on the maximal number of clients that a server can handle is realistic in many contexts. Then, our main contribution is to prove that even if it makes the allocation problem more difficult (NP-Complete), a very small additive resource augmentation on the servers degree is enough to find in polynomial time a solution that achieves at least the optimal throughput. After a set of theoretical results on the complexity of the offline and online versions of the problem, we propose several other greedy heuristics to solve the online problem and we compare the \emph{performance} (in terms of throughput) and the \emph{cost} (in terms of disconnections and reconnections) of all proposed algorithms through a set of extensive simulation results.< Réduire

Mots clés en anglais

Online computation

Approximation algorithms

Resource Augmentation

Divisible Scheduling

Bin Packing

Cloud Computing

URI

https://oskar-bordeaux.fr/handle/20.500.12278/197829

DOI

http://dx.doi.org/10.1109/TPDS.2012.175

Project ANR

Simulation de systèmes de prochaine génération - ANR-11-INFR-0013

Origine

Importé de hal

Unités de recherche

Laboratoire Bordelais de Recherche en Informatique (LaBRI) - UMR 5800