Flexible and Efficient Deployment of Data Processing Pipelines on Wireless IoT Systems

There is an increasing number of IoT devices that do not merely act as sensor nodes but are also sufficiently powerful to perform some local data processing before data is sent upstream to more powerful servers or the cloud. In this paper, we present a framework for the flexible deployment and execution of sensing and data processing application components on embedded, industrial-strength nodes that can be connected to a wide variety of sensors. This is done using textual, declarative descriptions instead of actual code, in conjunction with a pub/sub approach for data exchange between such components. As a result, it becomes possible to build and deploy in-network data processing pipelines in efficient way, even on top of low-bandwidth wireless links. Our evaluation shows that the proposed approach can reduce the size of application logic by 95.3% and the deployment time by up to 91.1% compared to a more conventional deployment of binaries. Also, the ability to process data near or even directly on the nodes that are connected to the sensors proving the raw measurements, can reduce the number of messages by 97.7% and improve message latency by up to 44.3% vs sending all data and processing it on a server.