Journal of Management Information Systems

Volume 39 Number 2 2022 pp. 513-541

Greening the Cloud: A Load Balancing Mechanism to Optimize Cloud Computing Networks

Kumar, Chetan, Marston, Sean, Sen, Ravi, and Narisetty, Amar

ABSTRACT:

Approximately 55 percent of the world’s 7.3 billion people access the Internet, creating a significant demand in information technology (IT) services for both organizations and consumers. The number of data centers continue to increase to meet this demand, consuming 2 percent of the energy produced worldwide. Many organizations moving towards cloud computing due to its ability to meet users’ needs on demand. Greening cloud computing technology has become an important aspect of an organization’s design and use of cloud computing. One aspect of greening the cloud is through efficiently using cloud-based resources. In this study, we focus on the resource allocation applications of cloud computing technologies to green an organizations cloud. We design a pricing and allocation mechanism for a private cloud computing service that allows the firm to effectively load balance their cloud computing resources. Our optimal pricing mechanism is a dynamic pricing model, which maximizes the net value of users in a private cloud computing service. Additionally, we create a job allocation algorithm based on our dynamic pricing model to load balance the cloud. We show that balancing the job allocation such that the number of jobs at individual resource servers as close to equal as possible is optimal. Furthermore, simulations were run on the allocation mechanism to examine the effects on the cloud resources while gaining insight to effectively distribution resources to public clouds. Our model can help organizations to efficiently distribute their cloud-based resources, which allows for a greener cloud computing system.

Key words and phrases: Cloud computing, Green IT, load balancing, optimal allocation