电讯技术2023，Vol.63Issue(12)：1894-1901,8.DOI:10.20079/j.issn.1001-893x.220728002
协同边缘网络中智能计算卸载与资源优化算法
Intelligent Computation Offloading and Resource Optimization Algorithm in Collaborative Edge Networks
摘要
Abstract
In order to solve the problem of offloading decision for computation-intensive tasks in dependency-aware edge networks,a depth-first search scheduling strategy based on task priority is proposed.By taking into account the limited energy and high mobility of users,the network model of joint downlink energy harvesting and uplink computing task offloading is built.Furthermore,the device-to-device optimization objective function is formulated under the constraints of the latency and the task priority and the task offloading problem is modeled as a Markov decision process.By exploiting the advantage of self-learning of deep reinforcement learning,the Dueling Double DQN(D3QN)algorithm based on task dependency is designed to tackle it.Numerical results show that the proposed method can meet the delay requirements of more users and reduce the completion delay up to 9% ～10% against other existing schemes.关键词
协同边缘网络/移动边缘计算/计算卸载/深度强化学习Key words
collaborative edge network/mobile edge computing/computation offloading/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
李斌,徐天成..协同边缘网络中智能计算卸载与资源优化算法[J].电讯技术,2023,63(12):1894-1901,8.基金项目
国家自然科学基金资助项目(62101277) （62101277）
江苏省自然科学基金(BK20200822) （BK20200822）
