5G Network Management for Big Data Streaming using Machine Learning

This chapter provides background information regarding the application of Machine Learning (ML) and artificial intelligence (AI) in managing big data streaming in future softwarized and virtualized 5G networks. It discusses the concepts for optimization of data management with ML in softwarized 5G networks. The chapter presents state‐of‐the‐art research work on multimedia big data analytics by providing the current big data 5G frameworks and their applications in multimedia analyses. The learning paradigms in ML that influence the data collection, feature engineering, and the establishment of ground truth are divided into four categories, namely: supervised, unsupervised, semisupervised, and reinforcement learning. Multimedia big data is often multimodal, heterogeneous, and unstructured, attributes that make it difficult to represent and model. The deep learning models for Internet of Things (IoT) big data analytics can be performed at the IoT cloud layer on high‐performance computing systems or cloud platforms.