Abstract
Fog computing, which provides low-latency computing services at the network edge, is an enabler for the emerging Internet of Things (IoT) systems. Offloading tasks to the fog that is closer to IoT users for processing has become a means to ensure that tasks are completed quickly. Fog computing cannot only reduce the congestion of the backbone network but also ensure that the task is completed within the specified time. Since fog resources are limited, there will be resource competition among IoT devices. How to quickly and efficiently make an optimal computation offloading decision for individual selfish IoT devices is a fundamental research issue. This article regards the process of multiple IoT devices competing for fog devices as a game and proposes a distributed computation offloading algorithm. The goal is to optimize the balance of computation delay, energy consumption, and cost for fog nodes. The competition between IoT nodes eventually reaches an equilibrium point, that is the Nash equilibrium point. We prove the existence of Nash equilibrium by Weighted Potential Game. In addition, if a large number of IoT devices select the same node for offloading, which will cause the fog node to run out of power and make some networks unable to work normally. Further, causing part of the network to be paralyzed. Therefore, the paper considers the fairness of offloading to extend the network life cycle. A calculation rate adjustment algorithm is designed for the fairness of offloading to ensure that fog nodes do not run out of power and fail. This paper not only fully considers the performance of the IoT device, but also considers the fairness of the fog. Numerous experiments proved the effectiveness of the proposed algorithm.
Highlights
I NTERNATIONALData Corporation (IDC) predicts that the number of sensors connected to the network will increase to 30 billion, and the number of connected devices will increase from 50 billion to 1 trillion by 2022
All these devices are connected to the network and construct the Internet of Things (IoT) systems [1]
Offloading tasks to the fog node can save energy, but because the operation and calculation of the fog node require costs, the fog node will charge a certain amount of waste from the IoT device
Summary
Data Corporation (IDC) predicts that the number of sensors connected to the network will increase to 30 billion, and the number of connected devices will increase from 50 billion to 1 trillion by 2022. This paper we design a distributed computation offloading method for delay-sensitive tasks. Each device makes the most beneficial computing offloading decision based on the choices of other devices Prove that this game will eventually reach a Nash equilibrium point. Task offloading schemes focusing on minimizing the computation delay or total energy consumption in existing literature may lead to extremely heavy burdens on the fog nodes that are close to the fog nodes or have high processing capabilities, which will result in the death of some important fog nodes and even serious network problems. A large number of IoT devices select the same node for offloading, which will cause the fog node to run out of power and make some networks unable to work normally. This paper proposed a computation rate adjustment(CRD) algorithm to reduce the unfairness of offloading
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