In the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) A key barrier to building performant, remotely managed and self-optimizing multi-sensor, distributed stream processing edge applications is high programming complexity. We recently proposed DataX [1], a novel platform that improves programmer productivity by enabling easy exchange, transformations, … Continue reading DataXe: A System for Application Self-optimization in Serverless Edge Computing Environments →

The exponential growth in smart sensors and rapid progress in 5G networks is creating a world awash with data streams. However, a key barrier to building perfor- mant multi-sensor, distributed stream processing applications is high programming complexity. We propose DataX, a novel platform that improves programmer productivity by enabling easy exchange, transformations, and fusion of data streams. DataX abstraction simplifies the application’s specification and exposes parallelism and dependencies among the application functions (microservices). DataX runtime automatically sets up appropriate data communication mechanisms, enables effortless reuse of microservices and data streams across applications, and leverages serverless computing to transform, fuse, and auto-scale microservices. DataX makes it easy to write, deploy and reliably operate distributed applications at scale. Synthesizing these capabilities into a single platform is substantially more transformative than any available stream processing system.