Towards QoS-Aware Fog Service Placement

TLDR

Fog computing decentralizes data processing and resource provisioning for IoT, but faces challenges of geographic distribution, delay sensitivity, and large data volumes, and research is still nascent. The study seeks to exploit the ubiquitous presence of small, inexpensive edge devices to successfully execute IoT services. We investigate IoT service placement on fog resources while accounting for QoS requirements. Our optimization model prevents QoS violations and reduces execution cost by 35 % compared to a purely cloud-based approach.

Abstract

Fog computing provides a decentralized approach to data processing and resource provisioning in the Internet of Things (IoT). Particular challenges of adopting fog-based computational resources are the adherence to geographical distribution of IoT data sources, the delay sensitivity of IoT services, and the potentially very large amounts of data emitted and consumed by IoT devices. Despite existing foundations, research on fog computing is still at its very beginning. A major research question is how to exploit the ubiquitous presence of small and cheap computing devices at the edge of the network in order to successfully execute IoT services. Therefore, in this paper, we study the placement of IoT services on fog resources, taking into account their QoS requirements. We show that our optimization model prevents QoS violations and leads to 35% less cost of execution if compared to a purely cloud-based approach.