A Three-level Scheduler to Execute Scientific Experiments on Federated Clouds

Authors
Pacini Naumovich, Elina Rocío; Mateos Diaz, Cristian Maximiliano; Garcia Garino, Carlos Gabriel
Publication Year
2015
Language
Spanish
Format
article
Status
Published version
Description
For executing current simulated scientific experiments it is necessary to have huge amounts of computing power. A solution path to this problem is the federated Cloud model, where custom virtual machines (VM) are scheduled in appropriate hosts belonging to different providers to execute such experiments, minimizing response time. In this paper, we study schedulers for federated Clouds. Scheduling is performed at three levels. First, at the broker level, datacenters are selected by their network latencies via three policies ?Lowest-Latency-Time-First, First-Latency-Time-First, and Latency-Time-In-Round?. Second, at the infrastructure level, two Cloud VM schedulers based on Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are implemented. At this level the scheduler is responsible for mapping VMs to datacenter hosts. Finally, at the VM level, jobs are assigned for execution into the pre-allocated VMs. We evaluate, through simulated experiments, how the proposed three-level scheduler performs w.r.t. the response time delivered to the user as the number of Cloud machines increases, a property known as horizontal scalability.
Fil: Pacini Naumovich, Elina Rocío. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina
Fil: Garcia Garino, Carlos Gabriel. Universidad Nacional de Cuyo. Instituto para las Tecnologías de la Informacion y las Comunicaciones; Argentina
Subject
SCIENTIFIC EXPERIMENTS
FEDERATED CLOUDS
SCHEDULING
ANT COLONY OPTIMIZATION
PARTICLE SWARM OPTIMIZATION
Ciencias de la Computación
Ciencias de la Computación e Información
CIENCIAS NATURALES Y EXACTAS
Access level
Restricted access
License
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repository
CONICET Digital (CONICET)
Institution
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identifier
oai:ri.conicet.gov.ar:11336/6825