… machine learning methods [39]–[41] to solve task scheduling and load balancing problems in
the cloud computing environment… a cloud computing environment. For example, A Max-Min …

… challenges as load balancing (LB) and adaptation to failure. Many LB strategies have been
proposed in cloud computing, but … Machine learning algorithms are classified as supervised …

… Section 4 discusses in detail LB challenges, parameters, policies, and classification of
process state-based LB approaches in the cloud. Section 5 Machine learning for load balancing. …

… Cloud Computing field to improve cloud-based applications’ performance in terms of Load
Balancing … Section III covers the related work whereby the Load Balancing and Tasks …

… various Load Balancing techniques in a static, dynamic, and nature-inspired cloud environment
… by using dual Load Balancers and machine learning tools to predict failures in the active …

… Q-learning algorithm for improving the load balancing in the cloud environment by integrating
improved Q-learning … algorithm in the area of machine learning which allows the agent to …

… In this paper, a strategy is presented based on machine learning for VM replacement which
… Load balancing in data centers is significant for scalable and available cloud computing …

… global load balancing, optimizing … of machine learning in optimizing cloud load balancing
operations, and improving scalability, efficiency, and resilience in modern cloud environments. …

… In this work, we present a machine learning based intrusion detection system for Cloud
environments. We propose an intelligent approach to build automatically a network intrusion …

… [28] have proposed power consumption to balance power consumption and load delay, ie, …
to the basic method based on XCS. Load distribution between cloud and fog nodes is a …