Signal Processing and Networking for Big Data Applications

Zhu Han is a Professor in the Department of Electrical and Computer Engineering, University of Houston, and a Fellow of the Institute of Electrical and Electronics Engineers (IEEE). He has co-authored several books, including Wireless Device-to-Device Communications and Networks (with Lingyang Song, Dusit Niyato and Ekram Hossain, Cambridge, 2015) and Game Theory in Wireless and Communication Networks (with Dusit Niyato, Walid Saad, Tamer Baser and Are Hjorungnes, Cambridge, 2011). Mingyi Hong is an Assistant Professor and a Black and Veatch Faculty Fellow in the Department of Industrial and Manufacturing Systems Engineering, Iowa State University. Dan Wang is an Associate Professor in the Department of Computing, Hong Kong Polytechnic University, and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

'A very nice balanced treatment over two large-scale signal processing aspects: mathematical backgrounds versus big data applications, with a strong flavor of distributed optimization and computation.' Shuguang Cui, University of California, Davis

• Part I. Overview of Big Data Applications: 1. Introduction; 2. Data parallelism: the supporting architecture; Part II. Methodology and Mathematical Background: 3. First order methods; 4. Sparse optimization; 5. Sublinear algorithms; 6. Tensor for big data; 7. Deep learning and applications; Part III. Big Data Applications: 8. Compressive sensing based big data analysis; 9. Distributed large-scale optimization; 10. Optimization of finite sums; 11. Big data optimization for communication networks; 12. Big data optimization for smart grid systems; 13. Processing large data set in MapReduce; 14. Massive data collection using wireless sensor networks.