Pervasive Cloud Controller for Geotemporal Inputs

TL;DR

This paper introduces a flexible cloud controller that dynamically manages resources across geographically distributed data centers, optimizing energy costs by considering regional electricity prices and temperatures, and demonstrating significant savings.

Contribution

It presents a novel, extensible cloud control system that accounts for geotemporal factors and workload QoS, outperforming traditional VM consolidation methods.

Findings

Achieved 28.6% energy cost savings in simulations.

Validated the controller's extensibility and adaptability.

Provided guidelines for environment conditions for cost savings.

Abstract

The rapid cloud computing growth has turned data center energy consumption into a global problem. At the same time, modern cloud providers operate multiple geographically-distributed data centers. Distributed data center infrastructure changes the rules of cloud control, as energy costs depend on current regional electricity prices and temperatures. Furthermore, to account for emerging technologies surrounding the cloud ecosystem, a maintainable control solution needs to be forward-compatible. Existing cloud controllers are focused on VM consolidation methods suitable only for a single data center or consider migration just in case of workload peaks, not accounting for all the aspects of geographically distributed data centers. In this paper, we propose a pervasive cloud controller for dynamic resource reallocation adapting to volatile time- and location-dependent factors, while considering the QoS impact of too frequent migrations and the data quality limits of time series forecasting methods. The controller is designed with extensible decision support components. We evaluate it in a simulation using historical traces of electricity prices and temperatures. By optimising for these additional factors, we estimate 28.6% energy cost savings compared to baseline dynamic VM consolidation. We provide a range of guidelines for cloud providers, showing the environment conditions necessary to achieve significant cost savings and we validate the controller's extensibility.