Energy efficient cloud service pricing: A two-timescale optimization approach

This paper considers the scenario of a cloud service market where several Cloud Service Providers (CSP) are in operation and are competing against each other to attract and serve the demands generated by the customers. The competition arises from the fact that the customers (the individuals or organizations) who generate demand for services in the market rationally choose the CSP which offers good quality of services at a lower price. For pricing the services offered by the CSPs under this framework, we provide an analytical framework by considering the operational cost incurred by the CSP to service the given demand, the quality of service (QoS) offered and the prices other CSPs are charging. The pricing strategy we propose strikes a reasonable balance between charging too little which would result in irrationally low business profit and charging too much which would result in customer loss and thereby eventually loss of market share. In addition, the pricing strategy proposed promotes energy efficiency and renewable energy integration using a bi-level optimization strategy. The first level consisting of a Slow Timescale Optimization Procedure (STOP) addresses the economic efficiency related issues for cloud service pricing. The second level involving a Fast Timescale Optimization Procedure (FTOP) performs energy efficient job scheduling. We carry out numerical simulations to validate the proposed pricing strategy and compare it with an oracle benchmark policy, with fair profit sharing among the CSPs. We compare the proposed energy aware scheduling policy with a baseline scheduling policy. We demonstrate the efficiency and effectiveness of the proposed bi-level strategy and discuss the results.