Profiling-Based Energy-Aware Recommendation System for Cloud Platforms

With rise in energy costs, operational costs for managing cloud infrastructures are also increasing. This is an opportunity to present an energy-aware recommendation system for cloud platforms. This paper presents one such system that implements a pure software approach for generating energy efficient recommendations for cloud infrastructures. This system performs offline profiling of cloud nodes to generate energy-aware profiles which are later matched with runtime usage feed. According to the real-time data, energy efficient profile is matched and provided to provisioning for implementation; consequently, achieving an energy efficient cloud platform.