Networked Signal and Information Processing
This addresses the problem of enabling efficient and secure decision-making in distributed environments for applications like IoT and edge computing, but it is incremental as it reviews existing progress.
The article reviews advances in networked signal and information processing over the last 25 years, showing that distributed agents can match the performance of centralized solutions while offering improved privacy, resilience, and resource savings.
The article reviews significant advances in networked signal and information processing, which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments of distributed agents. As these interacting agents cooperate, new collective behaviors emerge from local decisions and actions. Moreover, and significantly, theory and applications show that networked agents, through cooperation and sharing, are able to match the performance of cloud or federated solutions, while offering the potential for improved privacy, increasing resilience, and saving resources.