Resource Allocation Based on Reverse Auction Algorithm in Edge Computing Environment

With the exploding growth in the number of devices and data traffic, cloud networks face challenges such as high speeds and low latency. The traditional edge calculation is to send data that can't be processed by the local edge server to the remote cloud for processing. This will put great pressure on the remote cloud server, and the data will have relatively large transmission delay through the intermediate device. For this problem, this paper proposes an edge calculation method based on reverse auction algorithm to process the data nearby, and adopts the idea of reverse auction to distribute the overloaded data to the edge server with less load, reduce the transmission delay, improve the user experience, and balance the server load. The final simulation results show that allocating overloaded data to adjacent edge server for processing can make server load balance and significantly reduce transmission delay compared to sending to remote cloud.