A Trust-Based Task Offloading Method

Abstract

The invention discloses a trust-based task offloading method, which is divided into two components. 1: Cluster the Internet of Things devices with edge service computing requirements in the network. The Internet of Things devices in the cluster can communicate with drones, and the devices outside the cluster can transmit tasks to the devices in the cluster through multi-hop. Then offload the task to the drone. This clustering approach can reduce the cost of unmanned flights and expand the range of edge services. Since the tasks outside the cluster only need to be transmitted to any device in the cluster, it can avoid the excessive data load of a single cluster head. 2: Propose a trust evaluation mechanism based on retrospective analysis, introduce active trust based on drones, and conduct trust evaluation on IoT devices to ensure the effectiveness of task offloading. Combined with the trust-based task transmission routing protocol, reliable devices are selected for task relay forwarding or task offloading to ensure the smooth completion of computing tasks and reduce the packet loss rate of the network.

Description

technical field [0001] The invention belongs to the field of task offloading of mobile edge computing, in particular to a trust-based task offloading method. Background technique [0002] With the rapid development of the Internet of Things, the number of IoT devices deployed on the edge network is increasing, and a large amount of valuable data is generated. By processing and calculating the data generated in the edge network, valuable information can be extracted from the original perception data, reducing the data size and greatly reducing the load and computing pressure on the cloud. Processing a large amount of data requires high computing power, while the computing power provided by IoT devices is relatively weak and cannot meet the computing needs. The rise of task offloading technologies in edge networks provides an effective solution. A large number of scholars have studied and built edge computing platforms for task offloading. Among them, the most researched is...

AI Technical Summary

Problems solved by technology

In this drone-assisted scenario, since each IoT device needs to offload its tasks to the drone, there are the following disadvantages: (1) The energy consumption and cost of the drone are too high

Obviously, the longer the drone flies, the more energy it consumes and the higher the cost

(2) The reliability of task offloading cannot be guaranteed

There are attacks from malicious devices in the network, and the devices will discard some or all of the data packets during the transmission process, resulting in the task not being successfully transmitted to the UAV for edge computing, making it impossible for the device to receive the calculation results in a timely and effective manner

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