Cloud-IoT Resource Management Based on Artificial Intelligence for Energy Reduction

Abstract

The rapid growth in demand for cloud services has led to the creation of large-scale data centers, which allows application service providers to lease data center capacity for application deployment as per user requirement in terms of quality of services (QoS). These data centers consume a lot of electrical power which contributes to increased operating costs and carbon dioxide emissions. In addition, modern cloud computing environments must provide QoS for their customers which leads them to a need to make a power-performance compromise that is to say in terms of energy consumption and service-level agreement (SLA) compliance. That is why, we introduce, in this paper, an intelligent resource management policy for cloud data centers. The goal is to dynamically allocate and continuously consolidate virtual machines taking advantage of live migration and disengage inactive nodes to minimize power feeding in this cloud environment while maintaining the quality of service. We integrate some artificial intelligence concepts to ensure a dynamic resource management and a better power-performance compromise and significantly reduce the consumed energy.

BluBSIoT: Advancing Sustainability through Peer-to-Peer Cross-Ledgering in Social Internet of Things

“…Internet of Things (IoT) sensors and devices have been used for remote monitoring. These methods generate considerable interest in resource management that reaches an optimum stature with minimal resource cost and maximal profits by monitoring diverse environmental parameters of blue and green resources (Daoud et al, 2022). The data acquired from IoT sensors and devices can be used for immediate notification for action and long-term observation, and analysis with generalization (Zahoor, Mir, 2018).…”