Method for maximizing task completion rate of multiple MEC servers with UAV assistance

By using drone-assisted time-division multiple access protocols and optimized resource allocation for multi-MEC servers, the problems of channel fading and limited computing resources in traditional mobile edge computing networks are solved, achieving stability and energy consumption optimization in environments with high computing workloads.

CN116366127BActive Publication Date: 2026-06-30XIAN UNIV OF POSTS & TELECOMM
0 Cites 0 Cited by

Patent Information

Application Number
CN202310223494.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-03-09
Publication Date
2026-06-30
Estimated Expiration
2043-03-09

AI Technical Summary

Technical Problem

Traditional mobile edge computing networks suffer from severe channel fading and limited computing resources of a single mobile edge computing server, making it difficult to maintain stability and reduce energy consumption in environments with high computing workloads.

Method used

The method of using drones to assist multiple MEC servers is adopted. User tasks are offloaded to drones and ground base stations through time division multiple access protocol, optimizing drone trajectory and computing resource allocation to maximize task completion rate and minimize system energy consumption.

Benefits of technology

It improves the stability of edge computing networks in environments with high computing workloads, reduces energy consumption for drones and users, and increases task completion rates.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

This invention discloses a method for maximizing the task completion rate of a UAV-assisted multi-MEC server, primarily addressing the problems of severe channel fading and limited computing resources of a single MEC server in existing technologies. The method includes: 1) constructing a UAV-assisted multi-MEC server network system model; 2) employing a time-division multiple access (TDMA) protocol, where users offload part of their task input data to the UAV, and the UAV offloads part of its unfinished task input data to multiple ground base stations for computation; 3) finding the optimal task completion rate, CPU computing frequency, transmission power, offloading decision, and UAV trajectory by maximizing user task completion rate and minimizing system energy consumption; and 4) optimizing system operating parameters based on the optimization results. This invention effectively improves network computing resources, achieves stability in environments with high computational workloads, and reduces energy consumption for both UAVs and users, making it applicable to edge computing systems.
Need to check novelty before this filing date? Find Prior Art