Reliable Service Allocation in Clouds with Memory and Capacity Constraints

Olivier Beaumont (1, 2) , Lionel Eyraud-Dubois (1, 2) , Pierre Pesneau (3) , Paul Renaud-Goud (1, 2)

1 LaBRI - Laboratoire Bordelais de Recherche en Informatique
2 CEPAGE - Algorithmics for computationally intensive applications over wide scale distributed platforms
3 Realopt - Reformulations based algorithms for Combinatorial Optimization

We consider allocation problems that arise in the context of service allocation in Clouds. More specifically, on the one part we assume that each Physical Machine (denoted as PM) is offering resources (memory, CPU, disk, network). On the other part, we assume that each application in the IaaS Cloud comes as a set of services running as Virtual Machines (VMs) on top of the set of PMs. In turn, each service requires a given quantity of each resource on each machine where it runs (memory footprint, CPU, disk, network). Moreover, there exists a Service Level Agreement (SLA) between the Cloud provider and the client that can be expressed as follows: the client requires a minimal number of service instances which must be alive at the end of the day, with a given reliability (that can be converted into penalties paid by the provider). In this context, the goal for the Cloud provider is to find an allocation of VMs onto PMs so as to satisfy, at minimal cost, both capacity and reliability constraints for each service. In this paper, we propose a simple model for reliability constraints and we prove that it is possible to derive efficient heuristics.

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Olivier Beaumont, Lionel Eyraud-Dubois, Pierre Pesneau, Paul Renaud-Goud. Reliable Service Allocation in Clouds with Memory and Capacity Constraints. Resilience 2013, in conjunction with EuroPar 2013, Sep 2013, Aachen, Germany. ⟨hal-00850125⟩