Cloud computing poses many large and complex problems for system management. An increasingly important requirement is the ability to maximize service performance at minimum cost subject to diverse goals and constraints. This necessitates advanced management approaches for reducing costs while maintaining high availability, scalability, elasticity, flexibility, reliability and efficiency. Solutions are sought in the broad area of system management, including resource and application management for cloud providers and users, self-reconfiguration to enable adaptation to changes, management processes and technologies, economically-driven decisions, models for cloud management, disaster recovery and backup etc.

The objective of CCOPT is to bring together researchers and practitioners to address the many facets of optimization in cloud-based computing systems and applications from different perspectives. Researchers will engage in stimulating dialogue regarding the fundamental principles, state of the art, and critical problems and challenges in optimization for cloud computing. A main goal of CCOPT is to bridge the gap between the fields of operations research and service system management.

While not limited to these, we intend to focus on three main thrusts:

Applications of optimization in cloud management: Management of clouds or cloud-based systems requires advanced optimization approaches, including, but not limited to, the following:

  • Machine-jobs scheduling in clouds
  • Capacity planning for the use of clouds
  • Energy management in clouds
  • Service management across clouds
  • Management processes and technologies
  • Cloud-based application, platform, infrastructure management
  • Cloud-based storage systems
  • Network management in clouds
  • Tolerance management for clouds
  • Internet of things

Optimization components and services: The use of optimization for cloud management necessitates changes to the management framework, architecture, and economic models etc.:

  • System frameworks and architectures
  • Economic models and management
  • Self-optimization components and services
  • Optimization for performance, QoS
  • Monitoring, modeling, estimation for optimization of management 

Algorithms and theory of optimization for cloud management

  • Optimization algorithms
  • Optimization models
  • Hierarchical and decentralized optimization
  • Predictive optimization