Performance Analysis of Task Offloading With Opportunistic Fog Nodes

Yeunwoong Kyung

doi:10.1109/access.2022.3141199

Abstract

In the fog computing architecture, the offloading of computing tasks can be conducted by the Internet of Things (IoT) devices to the fog nodes (FNs) that are co-located with base stations (BSs). However, as the IoT devices within the same coverage of the BS can offload lots of tasks simultaneously, the FN can be overloaded, resulting in scalability issues due to limited computing resources. As a promising solution to this problem, opportunistic FNs (OFNs) which denote FNs with mobility such as smart phones and vehicles have been considered as they opportunistically reduce the load of static FNs. IoT devices can offload a task and receive the result to/from the OFN directly when OFN is close to the device. In addition, the offloading can be conducted indirectly through the BS when the OFN is not in the vicinity of the IoT devices while it is within the coverage of the BS. To assess the offloading performance according to the mobility of the OFN considering the direct and indirect offloading scenarios, we developed an analytic model for the opportunistic offloading probability that the task can be offloaded to the OFN, which can also be interpreted as the load distribution effect. Extensive simulation results are given to validate the analytic model and to demonstrate the performance of the opportunistic offloading probability.

Highlights

With the growing popularity of smart devices, such as smart phones, wearable devices, and vehicles that are equipped with various sensors, Internet of Things (IoT) networks where data is shared between the connected devices and IoT services such as smart home, smart city, and smart factory have attracted increased attention [1], [2]
2) Eb: When τ1 ≤ τk < τ2 ≤ τr ≤ τ3, after the IoT device offloads the task to the opportunistic fog node (FN) (OFNs) through the base stations (BSs), it can receive the result of the task directly from the OFN because the task is completed within the IoT contact time (i.e., τ2 − τk ≤ tp ≤ τ2 + tI − τk )
Since we assume that the BS contact time is twice of the IoT contact time, the probability that either τk or τr exists within the IoT contact time is higher than the probability that both do not exist within the IoT contact time

Summary

INTRODUCTION

With the growing popularity of smart devices, such as smart phones, wearable devices, and vehicles that are equipped with various sensors, Internet of Things (IoT) networks where data is shared between the connected devices and IoT services such as smart home, smart city, and smart factory have attracted increased attention [1], [2]. The remote location of the cloud servers typically leads to high latency and requires high network bandwidth usage for the core network To mitigate this problem, the concept of fog computing, which brings computing resources closer to the IoT devices, has been introduced [4], [5]. The key contribution of this paper is two-fold: 1) we develop an analytic model for the opportunistic offloading probability that a task can be offloaded to the OFN for each offloading scenario, which can be interpreted as the load distribution effect; and 2) based on the simulation works, we evaluate the performance of the opportunistic offloading probability under various environments, which can provide valuable design guidelines for the OFN-based offloading architectures.

RELATED WORKS

SYSTEM MODEL

PERFORMANCE ANALYSIS

SIMULATION RESULTS

CONCLUSION