Performance estimation of container-based cloud-to-fog ofloading

Abstract

Fog computing oloads latency critical services of a Cloud application onto resources located at the edge of the network that are in close proximity to end-user devices. The research in this paper is motivated towards characterising and estimating the time taken to oload a service using containers, which is investigated in the context of the ‘Save and Load’ container migration technique. To this end, the research addresses questions such as whether fog ofloading can be accurately modelled and which system and network related parameters inluence oloading. These are addressed by exploring a catalogue of 21 diferent metrics both at the system and process levels that is used as input to four estimation techniques using a collective model and individual models to predict the time taken for oloading. The study is pursued by collecting over 1.1 million data points and the preliminary results indicate that oloading can be modelled accurately.