A Platform for Collaborative Acoustic Signal Processing
- Author(s): Hanbiao Wang
- Lewis Girod
- Nithya Ramanathan
- et al.
In this paper, we present a platform for collaborative acoustic signal processing, and demonstrate its use with an example application. Our platform is built upon the Stargate Linux-based microserver, and supports synchronized multi-channel acoustic data acquisition. We implement a dataflow-like staged event-driven programming model within the Emstar software framework that simplifies the development of collaborative processing applications. Unlike previous dataflow systems that emphasize real-time constraints, our framework emphasizes collaborative processing across nodes in a distributed system connected by an energy-conserving wireless network with non-deterministic message latency. In our model, an application is constructed by wiring together multiple stages, where each stage is implemented by an EmStar module. The modular approach simplifies development by isolating errors to specific stages, and enables run-time systemreconfigurability by allowing users to swap out implementations of individual stages, and to reconfigure the dataflow at run time.