基于边-端协同的任务卸载资源分配联合优化算法

吴柳青; 朱晓荣

doi:10.11959/j.issn.1000-0801.2020044

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基于边-端协同的任务卸载资源分配联合优化算法

研究与开发 | 更新时间：2024-06-05

- 基于边-端协同的任务卸载资源分配联合优化算法
- Joint optimization algorithm for task offloading resource allocation based on edge-end collaboration
- 电信科学 2020年36卷第3期页码：42-52
- 作者机构：
- 作者简介：
  
  [ "吴柳青（1995- ），女，南京邮电大学通信与信息工程学院硕士生，主要研究方向为移动边缘计算" ]
  [ "朱晓荣（1977- ），女，博士，南京邮电大学通信与信息工程学院教授、博士生导师，主要研究方向为下一代无线网络、异构网络" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020044
  中图分类号： TN929.5
- 网络出版日期：2020-03，
  
  纸质出版日期：2020-03-20
- 稿件说明：
移动端阅览
吴柳青, 朱晓荣. 基于边-端协同的任务卸载资源分配联合优化算法[J]. 电信科学, 2020,36(3):42-52.

Liuqing WU, Xiaorong ZHU. Joint optimization algorithm for task offloading resource allocation based on edge-end collaboration[J]. Telecommunications science, 2020, 36(3): 42-52.
吴柳青, 朱晓荣. 基于边-端协同的任务卸载资源分配联合优化算法[J]. 电信科学, 2020,36(3):42-52. DOI： 10.11959/j.issn.1000-0801.2020044.

Liuqing WU, Xiaorong ZHU. Joint optimization algorithm for task offloading resource allocation based on edge-end collaboration[J]. Telecommunications science, 2020, 36(3): 42-52. DOI： 10.11959/j.issn.1000-0801.2020044.

摘要

为了解决移动终端资源有限的问题，提升任务处理效率，提出了基于边-端协同的任务卸载与资源分配算法，以任务完成总效益最大化为目标，以业务QoS保证和资源受限为约束，形成了基于李雅普诺夫理论的最优任务卸载资源分配问题，由于该问题是NP难问题，因此提出了解将其耦为采用KKT条件求解的信道资源分配问题和关于任务分配的0-1整数规划问题。与传统算法相比，所提算法的复杂度是O(mn)，并提高了约20%的效益，降低了15%以上的时延。

Abstract

In order to solve the problem of limited mobile terminal resources and improve task processing efficiency

a task offloading resource allocation algorithm based on edge-end collaboration was proposed.With the goal of maximizing the total benefit of tasks

the optimal task offloading resource allocation problem based on Lyapunov theory was formed by the constraint of service QoS guarantee and resource limitation.Since the problem is NP-hard

it was decoupled into a channel resource allocation problem solved by KKT condition and a 0-1 integer programming problem about task assignment.Compared with the traditional algorithm

the complexity of the proposed algorithm was O(mn)

the efficiency was improved by about 20%

and the delay was reduced more than 15%.

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references

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