Telecommunications Science ›› 2022, Vol. 38 ›› Issue (3): 113-132.doi: 10.11959/j.issn.1000-0801.2022022
Special Issue: 边缘计算
• Research and Development • Previous Articles Next Articles
Lushan ZOU1,2, Xiaowen HUANG1,3, Jingmin YANG1,4, Yifeng ZHENG1,2, Guanglin ZHANG3, Wenjie ZHANG1,2
Revised:
2022-01-26
Online:
2022-03-20
Published:
2022-03-01
Supported by:
CLC Number:
Lushan ZOU, Xiaowen HUANG, Jingmin YANG, Yifeng ZHENG, Guanglin ZHANG, Wenjie ZHANG. Review on resources allocation and pricing methods in mobile edge computing[J]. Telecommunications Science, 2022, 38(3): 113-132.
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MEC场景 | 优化目标 | 参考文献 | 卸载方式 | 计算卸载方案 |
单用户 | 能耗 | 文献[ | 完全卸载 | 基于马尔可夫决策过程的能耗优化模型 |
文献[ | 完全卸载 | 最优码本速率设计和计算任务分配方案 | ||
时延 | 文献[ | 部分卸载 | 马尔可夫决策 | |
文献[ | 部分卸载 | 不等式分析法 | ||
成本 | 文献[ | 部分卸载 | 基于李雅普诺夫优化的动态计算卸载算法(LODCO) | |
QoE | 文献[ | 完全卸载 | 基于自调整参数化技术的贪婪算法 | |
多用户 | 能耗 | 文献[ | 部分卸载 | 基于李雅普诺夫优化技术在线卸载算法设计了任务卸载分配策略 |
时延 | 文献[ | 部分卸载 | 云计算和边缘计算结合(CENAM)模型 | |
文献[ | 部分卸载 | 遗传算法和基于分割时间槽的资源分配算法 | ||
时延和能耗 | 文献[ | 部分卸载 | 运用DDPG和ECOO算法的新型学习算法 | |
文献[ | 部分卸载 | 线性规划与交替优化技术结合的迭代算法 | ||
QoE | 文献[ | 部分卸载 | 多CDN视频分发和本地存储的网络代理方案 | |
多服务器 | 时延 | 文献[ | 完全卸载 | 基于网联车多跳传输的移动边缘计算卸载策略 |
文献[ | 完全卸载 | 最佳停止理论方法 | ||
文献[ | 完全卸载 | 改进min-min算法(TPMM) | ||
时延和能耗 | 文献[ | 部分卸载 | 基于深度强化学习的CAP辅助计算 | |
QoE | 文献[ | 部分卸载 | 基于块坐标下降算法的迭代算法 | |
文献[ | 完全卸载 | 机器学习模型 | ||
能耗 | 文献[ | 完全卸载 | 遗传学与生物地理学集成的算法 |
"
经济和定价模型 | 定价策略 | 参考文献 | 具体方案 | 适用场景和局限性 |
基于市场的定价 | 基于成本的定价 | 文献[ | 低梯度迭代算法 | 适用于比较简单的市场结构,缺乏 |
文献[ | 低复杂度梯度算法 | 考虑供应商策略、卖家价格感知和 | ||
文献[ | 动态递推 | 支付意愿等市场外部因素 | ||
文献[ | SARASA算法 | |||
歧视定价 | 文献[ | 低梯度迭代算法 | 适用于大部分市场结构,但是缺乏 | |
文献[ | 低复杂度梯度算法 | 公平性 | ||
文献[ | 动态递推 | |||
文献[ | SARASA算法 | |||
利润最大 | 文献[ | 引入几种分布式算法得出市场需求曲线 | 适用于大部分市场结构,但忽略市场竞争问题 | |
拉姆齐定 | 文献[ | 任务卸载效用函数 | 适用于大部分市场结构,但未考虑 | |
文献[ | AP诱导自利用户选择正确的优先级别 | 弹性需求市场 | ||
基于博弈理论的定价 | 非合作博 | 文献[ | 基于有限改进性质的分布式博弈方法 | 适用于每个参与者都是自主决策与 |
文献[ | 利用潜在博弈模型解决分布式任务卸载的问题 | 其他参与者无关的场景,但是参与 | ||
文献[ | 基于博弈的云资源和计算资源联合分配方案 | 者同时公布自身定价策略在实际中 | ||
文献[ | 两阶段任务迁移算法 | 很难成立 | ||
文献[ | 拉格朗日乘子法以及迭代法 | |||
主从博弈 | 文献[ | 迭代算法 | 适用于某一方具有优先权可抢占先 | |
文献[ | 分布式迭代算法 | 机的场景,但是要求参与者完全理性 | ||
文献[ | ODCA算法 | |||
演化博弈 | 文献[ | 迭代算法 | 适用于参与者具有各自的计算卸载 | |
文献[ | 基于强化学习的进化博弈卸载策略(EGT-QL) | 任务并且不了解其他参与者的卸载 | ||
文献[ | 基于演化博弈论的分散迭代算法 | 策略 | ||
文献[ | 人口进化集中算法 | |||
文献[ | 基于概率演化博弈论框架的动态卸载策略 | |||
文献[ | 均值场进化方法 | |||
基于拍卖理论的定价 | 双重拍卖 | 文献[ | McAfee拍卖算法 | 适用于拍卖双方如实提供定价及要 |
文献[ | 盈亏平衡双重拍卖(BDA)和动态定价双重拍卖(DPDA) | 价的场景 | ||
文献[ | 基于时延保证的资源双重拍卖算法(LGRDA) | |||
文献[ | 经验加权吸引力(EWA)算法 | |||
最优拍卖 | 文献[ | 运用深度神经网络控制终端设备参与拍卖活动 | 适用于买家都有拍卖意愿并且买家 | |
文献[ | 基于深度学习的最佳拍卖方案 | 会依据真实的价值估价进行出价 | ||
文献[ | 基于最优拍卖的任务缓存机制 | |||
组合拍卖 | 文献[ | 多轮顺序组合拍卖机制 | 适用于分配多种商品的场景,但是 | |
拍卖最终中标者的确定是一大难点 |
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