Performance Analysis of Task Offloading with Opportunistic Fog Nodes

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.