A Decision Framework for Carbon-aware Storage Service Selection in Multi-Cloud Environment

Data placement and service selection in Cloud has become challenging for enterprises. As they need to select data placement strategy such that their carbon footprint is minimal, users are data regulatory compliant, latency is low for better quality of service and overall operational cost is minimal. In this paper, we propose a decision framework for carbon-aware storage service selection in multi-cloud environment. We propose a mathematical model to repair non-compliant data placement such that the new placement reduces carbon footprint and minimizes operational costs. A Greedy randomized adaptive search (GRASP) based search heuristic is proposed to obtain multiple non-dominating solutions. Extensive experiments are carried out considering multiple tradeoffs to demonstrate their impact on data placement.