School of Information Sciences

Wang authors book on social edge computing

Dong Wang
Dong Wang, Professor and Associate Dean for Research

Associate Professor Dong Wang is the lead author of a book that introduces a new paradigm integrating edge computing, humans, and artificial intelligence (AI). Social Edge Computing: Empowering Human-Centric Edge Computing, Learning and Intelligence (Springer) is coauthored by Daniel "Yue" Zhang, research scientist at Amazon Alexa AI. 

With the rise in smart devices and advances in AI, data is increasingly being captured, processed, and analyzed near where it is created. This practice, edge computing, is different from cloud computing, where data is processed in a data center or public cloud. Advantages of computing at the edge include reduced bandwidth cost, improved responsiveness, and better privacy protection. In their book, Wang and Zhang define a new paradigm, social edge computing (SEC), that generalizes the current machine-to-machine interactions in edge computing and machine-to-AI interactions into a "holistic human-machine-AI ecosystem."

The SEC paradigm introduces a set of critical research challenges such as the rational nature of device owners, pronounced heterogeneity of the edge devices, real-time AI at the edge, human and AI interaction, and the privacy concern of the human users. This book addresses these challenges by presenting a series of principled models and system designs that enable the confluence of the computing capabilities of devices and the intelligence of the people, while explicitly addressing the unique concerns of humans.

"SEC enables 'social interactions' between machines and humans at the edge by allowing the devices to obtain the unique domain knowledge and expertise from humans to improve the performance and transparency of the application," said Wang. "It also motivates novel AI for social good applications such as privacy-aware health monitoring, disaster damage assessment, crowd abnormal event detection, and vehicle-based criminal tracking."

According to the authors, the techniques introduced in Social Edge Computing can help fully harness the power of devices, algorithms, and humans in the next generation of computing, intelligence, and learning applications at the edge.

Wang's research interests lie in the areas of human-centered AI, social sensing and intelligence, big data analytics, misinformation detection, and human cyber-physical systems. He holds a PhD in computer science from the University of Illinois Urbana-Champaign.

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