A Novel Approach for Service Function Chain (SFC) Mapping with Multiple SFC instances in a Fog-To-Cloud Computing System

Abstract

Internet of Things (IoT) has been ever-growing over the last few years. The IoT devices generate a massive amount of data that should be transmitted to the cloud for computing. Cloud consolidation and centralization lead to many network hops between the IoT devices and its associated cloud which makes two critical problems: (i) high latencies (ii) high bandwidth consumption in the IoT domain. Network Function Virtualization (NFV), Software Defined Network (SDN) and fog computing have been emerged to address these problems. In the Fog-to-Cloud (F2C) architecture, Fog and cloud work together to provide computing, storage, and application services in the IoT domain. To build complex services a specific set of virtual network functions can be chained together in a specific order which is known as Service Function Chaining (SFC). The joint VNF placement and traffic routing are called SFC mapping. In this paper, we propose an Integer Linear Program (ILP) model to solve SFC mapping in the fog-to-cloud Computing System in order to minimize the overall end-to-end (e2e) latency of IoT devices. We observe that our approach reduces the overall e2e latency of IoT devices significantly. Moreover, our approach helps us to analyze the effect of a number of instances in the end-to-end latency of IoT devices.