| 标题 |
 Sensing Data Aggregation in Mobile Crowd Sensing： A Cloud-Enhanced-Edge-End Framework with DQN Based Offloading 移动人群感知中的感知数据聚合：基于DQN卸载的云增强边缘端框架
相关领域
计算机科学
云计算
GSM演进的增强数据速率
计算机网络
分布式计算
电信
操作系统
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| 网址 | |
| DOI | |
| 其它 | Mobile Crowd Sensing (MCS) has attracted extensive attention as a promising method for environmental sensing and data collection. However, due to the increasing computational tasks, bandwidth, and computing pressure, traditional “Cloud-Edge-End” MCS is insufficient to efficiently offload sensing data in real-time for data aggregation. Therefore, we consider a novel MCS framework based on the “Cloud-Enhanced-Edge-End”, the framework uses MCS idle users as edge nodes to assist edge servers to enhance computing power and reduce delay and energy consumption. To achieve efficient data aggregation in the “Cloud-Enhanced-Edge-End” MCS framework, we first consider the multi-objective optimization of delay and energy consumption to establish a utility function. Secondly, addressing the shortcomings of traditional optimization algorithms, which often struggle with complex decision spaces and dynamic environments, |
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