Abstract

Fog computing is an emerging technology for the Internet of Things (IoT) that aims to support processing on resource-constrained distributed nodes in between the sensors and actuators on the ground and compute clusters in the cloud. Fog Computing benefits from low latency, location awareness, mobility, wide-spread deployment and geographical distribution at the edge of the network. However, there is a need to investigate, optimise for and measure the performance, scalability and interoperability of resource-constrained Fog nodes running real-time applications and queries on streaming IoT data before we can realise these benefits. With Eywa, a novel Fog Computing infrastructure, we

1. formally define and implement a means of distribution and control of query workload with an inverse publish-subscribe and push mechanism,
2. show how data can be integrated and made interoperable through organising data as Linked Data in the Resource Description Format (RDF),
3. test if we can improve RDF Stream Processing query performance and scalability over state-of-the-art engines with our approach to query translation and distribution for a published IoT benchmark on resource-constrained nodes and
4. position Fog Computing within the Internet of the Future.

Publication Meta Information

In Proceedings of the 4th International Conference on Internet Science held in Thessaloniki, Greece