This article addresses the decentralized optimization problem where a group of agents with coupled private objective functions work together to exactly optimize summation local interests. Upon modeling as an equality-constrained centralized one, we leverage linearized augmented Lagrangian method design event-triggered algorithm that only requires light computation at generic time instants and p...

In resource-constrained devices, adaptation of data stream processing to variations of data rates, availability of resources and environment changes is crucial for consistency and continuity of running applications. Context-aware and resource-aware adaptation, as a new dimension of research in data stream mining, enhances and improves distributed data stream processing tasks. Context-awareness ...

Compressing sensor data benefits sensor network applications because compression saves both transmission energy and storage space. This paper presents a novel lossless compression algorithm for sensor networks that is both dataaware and resource-aware. The DARA algorithm provides high compression ratios and also has a small memory footprint and efficient execution well within the range of senso...