Workload Classification

Abstract

Traditional cloud-only architecture faces the challenge of coexistence with the ever-increasing IoT devices and demands for the need of the hybrid cloud computing and fog/IoT architecture to realize better handling of workload/requests. Determining where the user-workload should be assigned depends on the workload itself, and thereby, the workload classification gains the pivotal role. This location and offloading decision to the right resource affects both users and the providers. This work describes various cloud-fog workloads and relates them to their suitable place of execution in such a hybrid environment. The workloads have been classified based on their different parameters and characteristics with the aim to identify appropriate resources for efficient resource provisioning. The workload classification and characterization promises a significant role in the resource management by efficient capacity planning, future resource requirement predictions, workload offloading and an improvement in the Quality of Service (QoS) leading to an improvement in the system performance.