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Due to the complexity of managing virtual machines arrival and departure in a geographic distributed Cloud, we tackle the dynamic placement and migrations of VMs with simulation techniques. In this work, we present the study of VMs placement policies in geographically distributed data centers (DCs) using the cloud simulator Cloud Sim. We have extended the simulator to take into consideration the inter-DCs...
In this paper, the problem of resource allocation in cloud datacenters, that own highly complex and heterogeneous tasks and servers, is considered. To address this problem, a novel framework, dubbed joint operation cost and network traffic cost (JOT) framework, is proposed. This framework combines notions from Gibbs sampling and matching theory to find an efficient solution addressing the NP-hard...
Over the past few decades, computing environments have progressed from single-user milieu to highly parallel supercomputing environments, Network of Workstations (NoWs), distributed systems, to more recently popular systems like grids and clouds. Due to its great advantage of providing large computational capacity at low costs, cloud infrastructures can be employed as a very effective tool. However,...
In this paper, we introduce a pack-centric approach to data center resource management by abstracting a system as a pack of resources and considering the mapping of these packs onto physical data center resource groups, called swads. The assignment of packs/VMs to swads/PMs is formulated as an integer optimization problem that can capture constraints related to the available resources, data center...
The problem of Virtual Machine (VM) placement in a compute cloud infrastructure is well-studied in the literature. However, the majority of the existing works ignore the dynamic nature of the incoming stream of VM deployment requests that continuously arrive to the cloud provider infrastructure. In this paper we provide a practical model of cloud placement management under a stream of requests and...
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