Titlebook: Artificial Intelligence for Cloud and Edge Computing; Sanjay Misra,Amit Kumar Tyagi,Lalit Garg Book 2022 The Editor(s) (if applicable) and

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Optimization Model of Smartphone and Smart Watch Based on Multi Level of Elitism (OMSPW-MLE),any activities that can be managed by these electronic devices. Therefore, in this study, the authors deal with building a model based on two artificial intelligent techniques: deterministic selection and ant colony optimization. This model is called a multilevel optimization model in order to perfo

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Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems,ve increased in recent years by providing opportunities into new domains for automation and integration of real-world objects. IoT-based cloud systems have been used, and there is a growing interest in IoT-enabled smart devices to generate big volumes of data, as mass production. Hence, there is a n

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Anomaly Detection in IoT Using Machine Learning,icate with each other. However, alongside IoT’s growth, a daunting topic has risen: the security of the IoT. With the numerous devices connected . Therefore, the network security should be able to identify such malignant packets. Therefore, an Intrusion Detection System (IDS) is very much needed. Su

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System Level Knowledge Representation for Edge Intelligence,parency and risks for IoT networks. Novel intelligent capabilities are being pushed towards the edge of the network, contributing novel risk factors such as privacy and limiting the ability of users to interact with the network components... This paper considers the IoT (Internet of Things), edge co

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AI-Based Enhanced Time Cost-Effective Cloud Workflow Scheduling,-sensitive workflows at the lowest cost and versatile time-cost algorithm (VTCA) which consider both time and cost constraints; these algorithms considerably enhance the earlier algorithms. TECA schedules activities to be completed as soon as possible and optimizes the costs in resource provisioning

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AI-JasCon: An Artificial Intelligent Containerization System for Bayesian Fraud Determination in Co at the edge and cloud domains. Most transactional systems from the edge-to-cloud layers lack the robust platform integration (such as application program interface (API) microservices) needed for fraud mitigation in networks and systems. This paper presents an AI containerization API system based o