A Resources Representation For Resource Allocation In Fog Computing Networks

TL;DR

This paper introduces a resource representation scheme for fog computing devices, enabling efficient resource allocation through MEC APIs, which reduces latency and enhances system performance.

Contribution

It proposes a novel resource representation method for heterogeneous fog devices and formulates resource allocation as a Lyapunov optimization problem.

Findings

Minimizes latency in fog networks

Improves resource utilization efficiency

Enhances overall system performance

Abstract

Fog computing is emerging as a new paradigm to deal with latency-sensitive applications, by making data processing and analysis close to their source. Due to the heterogeneity of devices in the fog, it is important to devise novel solutions which take into account the diverse physical resources available in each device to efficiently and dynamically distribute the processing. In this paper, we propose a resource representation scheme which allows exposing the resources of each device through Mobile Edge Computing Application Programming Interfaces (MEC APIs) in order to optimize resource allocation by the supervising entity in the fog. Then, we formulate the resource allocation problem as a Lyapunov optimization and we discuss the impact of our proposed approach on latency. Simulation results show that our proposed approach can minimize latency and improve the performance of the system.