CHAVE Project
Consolidation and High Availability on Virtualized Environments — reducing energy consumption in cloud infrastructure without sacrificing service availability.
Project overview
CHAVE is a research project that proposes an innovative approach to virtual machine management, balancing energy efficiency with high availability in cloud computing environments.
The project addresses a fundamental challenge in cloud infrastructure: how to reduce energy consumption through virtual machine consolidation while maintaining sufficient service availability. By developing new algorithms and metrics, CHAVE provides a framework for optimizing resource allocation in virtualized environments.
Key innovations
- Energy-aware VM placement algorithm — placement strategies that consider both power consumption and performance metrics.
- Availability risk assessment — mathematical models to quantify the risk of service unavailability during VM consolidation.
- Dynamic workload analysis — real-time monitoring and prediction of VM resource demands to optimize placement decisions.
- Multi-objective optimization — balancing the conflicting goals of energy efficiency, performance, and availability.
- Migration cost modeling — assessment of the overhead and impact of VM migrations on system performance.
Technical architecture
The CHAVE framework consists of several interconnected components:
Core components
- Resource Monitor — collects and analyzes VM and host metrics
- Consolidation Engine — implements VM placement algorithms
- Risk Analyzer — evaluates availability risks
- Decision Manager — orchestrates VM migrations
- Performance Validator — ensures SLA compliance
Integration points
- OpenStack and VMware adapters
- Power measurement interfaces
- Workload prediction engine
- Historical data analytics
- Event notification system
Research outcomes
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CHAVE: Consolidation with High Availability on Virtualized Environments
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Uma Proposta de Orquestração de Nuvem Computacional Baseada em Consolidação, Elasticidade e Disponibilidade
A cloud orchestration proposal based on consolidation, elasticity and availability
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MeHarCEn: A Method of Harmonizing Energy Consumption in Data Centers
Experimental results
Measured on OpenStack cloud environments
Related publications
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Uma ferramenta para análise do impacto da migração de máquinas virtuais
A tool for analysing the impact of virtual machine migration
Analysis of the impact of virtual machine migration on network and system performance, considering different hypervisors and VM configurations.
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Consolidação de máquinas virtuais com alta disponibilidade: uma revisão bibliográfica sistemática
Virtual machine consolidation with high availability: a systematic literature review
Systematic literature review on virtual machine consolidation strategies that maintain high availability in cloud environments.
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Análise da consolidação de máquinas virtuais nos equipamentos de rede
Analysis of virtual machine consolidation on network equipment
Analysis of the impact of virtual machine consolidation on network equipment and traffic patterns in data center networks.
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Problema Bin Packing com Abordagem Heurística First Fit Decreasing
The bin packing problem with a first fit decreasing heuristic
Implementation and analysis of the First Fit Decreasing heuristic for the Bin Packing problem, applied to virtual machine placement.
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