Optimization of Function Chaining on the Edge for IoT applications

With the rapid deployment of Internet of Things (IoT) applications, video processing and streaming requirements are increasing, and edge computing is a good candidate to cope with strong latency and throughput expectations. In this paper, we consider the optimal routing, placement and scaling of IoT-based service function chains for object detection. We propose an edge networking approach dealing with limited CPU and network bandwidth resources in a joint optimization based on Integer Linear Programming for small problem instances, and a graph-based approximation to cope with scalability issues. We evaluate the efficiency of our algorithms through simulations and show that the graph-based approach converges towards a near-optimal solution in negligible time and is thus suitable for real-time function chain placement.