Journal on Communications ›› 2021, Vol. 42 ›› Issue (4): 44-61.doi: 10.11959/j.issn.1000-436x.2021096
Special Issue: 边缘计算
• Topics: Strategic Technologies to Massive Connecting for the Future Mobile Networks • Previous Articles Next Articles
Yongming HUANG1,2, Chong ZHENG1, Zhengming ZHANG1, Xiaohu YOU1,2
Revised:
2021-03-31
Online:
2021-04-25
Published:
2021-04-01
Supported by:
CLC Number:
Yongming HUANG, Chong ZHENG, Zhengming ZHANG, Xiaohu YOU. Research on mobile edge computing and caching in massive wireless communication network[J]. Journal on Communications, 2021, 42(4): 44-61.
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关键问题 | 关键研究点 | 相关文献 | 方法论 |
能耗敏感型计算卸载 | 文献[15-16] | 整体卸载,基于SCA的迭代优化的卸载 | |
计算卸载问题 | 部分卸载,基于阈值优先级的计算卸载 | ||
时延敏感型计算卸载 | 文献[17] | 基于Lyapunov的低复杂度在线动态计算卸载 | |
时延-能耗敏感型计算卸载 | 文献[18-19] | 基于惩罚函数和D.C.规划的迭代搜索计算卸载 | |
基于交替凸搜索的计算卸载 | |||
基于统计用户请求的历史数据 | |||
非编码缓存 | 文献[21-26] | 基于优化算法 | |
边缘缓存问题 | 基于动态规划和强化学习 | ||
基于深度神经网的PDA设计 | |||
编码缓存 | 文献[20,27-30] | 基于强化学习的缓存更新和多播调度 | |
基于优化算法 | |||
计算资源分配 | 文献[31-32] | 时间维度的资源分配,基于Lyapunov的最优计算资源分配 | |
空间维度的资源分配,基于势博弈论的计算资源分配 | |||
缓存资源分配 | 文献[33-34] | 基于用户社交关系的静态缓存资源配置 | |
多维资源分配问题 | 基于用户时变内容请求的在线响应式动态缓存资源分配 | ||
能量资源分配 | 文献[35-36] | CSI和TSI知识完备时,基于凸优化的离线传输功率分配算法实;CSI和TSI知识仅因果已知,基于启发式的在线传输功率分配 | |
基于拉格朗日对偶法的离线能耗优化算法;基于滑动窗口以及序列优化的在线传输功率分配算法 | |||
通信资源分配 | 文献[37] | 基于回声状态网络和迁移学习的上下行传输资源块动态分配 | |
混合资源分配 | 文献[38-39] | 基于深度强化学习的通信与计算资源联合分配 | |
基于自适应优化算法、粒子群算法与Pareto一对一匹配算法相结合的计算、能量和通信资源混合资源分配 | |||
用户关联问题 | 基于时延最小化用户关联 | 文献[40] | 基于深度强化学习的自适应用户关联算法,实现任务总计算时延最小化 |
基于能耗最小化用户关联 | 文献[41] | 基于最短路径优化的用户关联算法,实现时延约束下的能效最大化 | |
基于粒子群的用户关联,实现时延能耗联合代价最小化 | |||
基于能耗?时延权衡用户关联 | 文献[42-44] | 基于0-1整数规划的迭代优化用户关联,实现时延能耗联合定义的QoE代价最小化 | |
基于模拟退火的用户关联,实现用户QoE最大化 | |||
基于Markov决策的策略迭代算法来保护用户位置隐私的同时实现最优业务迁移决策 | |||
用户位置隐私保护 | 文献[50-52] | 基于chaff的保护策略来对抗窃听者,保护用户位置隐私 | |
隐私保护问题 | 基于图学习来保护用户位置隐私的同时实现基本的业务提供 | ||
深度强化学习联合区块链授权与认证的用户数据加密技术,实现安全的内容缓存服务 | |||
用户数据隐私保护 | 文献[53-56] | 博弈论联合中国余数论的内容加密协议,实现用户数据隐私保护下的多归属访问缓存业务 | |
基于概率论的公钥加密技术,实现数据隐私保护下的用户排名查询业务基于混沌系统的伪随机置换加密技术 |
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