A Task Offloading and Reallocation Scheme for Passenger Assistance Using Fog Computing

A Fog computing-based transportation system envisions to reduce energy consumption and communication delay. This paper presents a Fog computing-based scheme for assisting passengers, which involves task offloading and reallocation. We consider a dynamic environment where the passengers frequently change their locations. Additionally, the scheme mitigates the sudden failure of the Fog devices. We employ a game-theoretic approach to determine optimal fractions of a task associated with the passengers to be offloaded among the Fog devices and Cloud. It also supports the reallocation of the allocated fractions of the task. This offloading and reallocation of tasks ensures the execution within a given time constraint and requires minimal execution cost. We also prove the existence of near Nash equilibrium for the allocated fractions of the task on Fog devices. Further, this work covers different possibilities of dependencies among the fractions of the task and corresponding utilities of Fog devices in the dynamic environment. Finally, we present the empirical and real-world evaluations to verify the effectiveness of the proposed scheme in terms of the number of Fog devices, the deadline of the task, and game parameters.

Automated summary

This paper presents a Fog computing-based scheme for assisting passengers by offloading and reallocating tasks, aiming to reduce energy consumption and communication delay. It supports the execution within a given time constraint and minimal execution cost in a dynamic environment.