Pricing tradeoffs for data analytics in fog-cloud scenarios
Fog computing represents a generalization of traditional cloud computing, in which application functionality resides at a local device and a remote cloud server. This chapter presents an initial survey of fogonomics, using a case study of distributed data processing to illustrate its research challenges. In particular, it demonstrates the trade-off between balancing quality-of-service and service cost when distributing application tasks between cloud and edge devices, given a set of service prices. Applications utilizing fog architectures will require access to both computing devices at different levels of the cloud-to-things continuum and network bandwidth to connect these devices together. The chapter discusses the economics faced by fog applications today. It provides an overview of typical fog application architectures on which economic markets are constructed. The chapter also illustrates how price schemes impact the design of fog applications through the case study.