A Dynamic Application-Partitioning Algorithm with Improved Offloading Mechanism for Fog Cloud Networks

Abstract

This paper aims to propose a new fog cloud architecture that performs a joint energy-efficient task assignment (JEETA). The proposed JEETA architecture utilizes the dynamic application-partitioning algorithm (DAPTS), a novel algorithm that efficiently decides and switches the task to be offloaded or not in heterogeneous environments with minimal energy consumption. The proposed scheme outperforms baseline approaches such as MAUI, Think Air and Clone Cloud in many performance aspects. Results show that for the execution of 1000 Tasks on fog, mobile offloaded nodes, JEETA consumes the leas, i.e., 23% of the total energy whereas other baseline approaches consume in between 50−100% of the total energy. Results are validated via real test-bed experiments and trice are driven efficient simulations.

Keywords

• MECA
• offloading system
• augmented reality
• application partitioning
• dynamic applications