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Technology advancement has pushed computation to the network edge, paving the way for a class of IoT applications that leverage CPU, storage and communications in edge devices. Building these new IoT applications is not an easy task however. Two key challenges include: supporting the dynamic nature of the edge network and the context-dependent characteristics of application logic. In this paper we report our experience in building an edge computing platform that uses a distributed data flow programming model based on the popular open source Node-RED tool. We describe some of the challenges we faced as well as some novel solutions that were implemented in our platform. A new approach in applying the concept of exogenous coordination is also presented and shown to be necessary in building large scale IoT applications across the edge, fog and cloud.

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Summary In recent years, fog computing has emerged as a new distributed system model for a large class of applications that are data‐intensive or delay‐sensitive. By exploiting widely distributed computing infrastructure that is located closer to the network edge, communication cost and service response time can be significantly reduced. However, developing this class of applications is not straightforward and requires addressing three key challenges, ie, supporting the dynamic nature of the edge network, managing the context‐dependent characteristics of application logic, and dealing with the large scale of the system. In this paper, we present a case study in building fog computing applications using our open source platform Distributed Node‐RED (DNR). In particular, we show how applications can be decomposed and deployed to a geographically distributed infrastructure using DNR, and how existing software components can be adapted and reused to participate in fog applications. We present a lab‐based implementation of a fog application built using DNR that addresses the first two of the issues highlighted earlier. To validate that our approach also deals with large scale, we augment our live trial with a large scale simulation of the application model, conducted in Omnet++, which shows the scalability of the model and how it supports the dynamic nature of fog applications.

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