Recently, great progress has been witnessed in the application of mobile cloud computing in the field of health care such as online medical inquiries. However, due to the limitation of cognitive intelligence, QoE (Quality of Experience) is hampered by two problems, the first of which is that the traffic pressure of the core network cannot well meet the requirements of delay-sensitive emotional services, especially for users with different emergencies, while the second is that current applications cannot provide personalized service for different users. Based on the two problems, we propose an emotion-aware mobile edge computing architecture based on emotional task priority to guide the allocation of edge resources and to provide intelligent and personalized emotional services with higher QoE. Specifically, we first introduce the entities involved in the proposed architecture of emotion-aware mobile edge computing system. Next, we describe our optimal computing resource allocation strategy, including important concepts and a detailed algorithm. Finally, we build a test platform and conduct experiments, which show that the proposed architecture obtains better performance in terms of system utility compared with baseline methods.

最近，在移动云计算在医疗保健领域（如在线医疗查询）中的应用已见证了巨大的进步。但是，由于认知智能的局限性，QoE（体验质量）受到两个问题的困扰，第一个问题是核心网络的流量压力不能很好地满足对延迟敏感的情感服务的需求，特别是对于用户而言具有不同的紧急情况，其二是当前的应用程序无法为不同的用户提供个性化服务。针对这两个问题，我们提出了一种基于情感任务优先级的情感感知移动边缘计算架构，以指导边缘资源的分配，并提供具有更高QoE的智能化个性化情感服务。具体来说，我们首先介绍参与情感感知的移动边缘计算系统架构所涉及的实体。接下来，我们描述我们的最佳计算资源分配策略，包括重要的概念和详细的算法。最后，我们建立了一个测试平台并进行了实验，结果表明，与基线方法相比，所提出的体系结构在系统实用性方面获得了更好的性能。