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Fog computing and edge computing are two of the latest technologies which are offered as solutions to challenges faced in cloud computing. Instead of offloading all the tasks to centralized cloud servers, some of the tasks can be scheduled at intermediate fog servers or edge devices. Though this solves most of the problems faced in cloud, it also encounters other traditional problems due to resource-related constraints like load balancing, scheduling, etc. In order to address task scheduling and load balancing in cloud-fog-edge collaboration among servers, the authors have proposed an improved version of min-min algorithm for workflow scheduling which considers cost, makespan, energy, and load balancing in heterogeneous environment. This algorithm is implemented and tested in different offloading scenarios – cloud only, fog only, cloud-fog, and cloud-fog-edge collaboration. This approach performed better, and the result gives minimum makespan, less energy consumption, along with load balancing and marginally less cost when compared to min-min and ELBMM algorithms.

Load and Cost-Aware Min-Min Workflow Scheduling Algorithm for Heterogeneous Resources in Fog, Cloud, and Edge Scenarios