APPLICATION OF EMOTION COMPUTING BASED ON EMOTION REGULATION COMBINED WITH EDGE COMPUTING IN EMERGENCY MANAGEMENT PLATFORM

BACKGROUND: With the development of mobile Internet and intelligent Internet of things, more and more new generation information technologies are applied in the field of emergency management. At present, the traditional cloud computing architecture can no longer meet the dynamic and real-time computing needs in these scenarios. As a new computing architecture, edge computing and affective computing achieve the sinking of computing power through computing unloading. The development of affective computing depends on the research of human intelligence and emotion in cognitive psychology, which endows computers with the same emotional ability as humans. On the emergency management platform, emotional computing and edge computing are used to build the emotional model of emergency management, decompose, unload and migrate the computing tasks to the edge, and improve the service quality of emergency services. SUBJECTS AND METHODS: Firstly, based on the idea of combining peacetime and wartime and cognitive psychology, this paper constructs emergency management emotion calculation and edge calculation models for different emergency management scenarios, including conventional emergency management emotion calculation joint edge calculation model and wartime emergency management emotion calculation joint edge calculation model. By using cognitive psychology models of different emergency scenarios, the cognitive psychology model is integrated into the process of edge computing unloading and scheduling. It corresponds to the problem of computing unloading and resource allocation in case of no emergency (peacetime), and the problem of computing unloading and resource allocation in case of emergency (wartime). Secondly, for different emergency management scenarios, based on convex optimization and fireworks algorithm, an improved fireworks algorithm based on convex optimization is proposed to form the unloading optimization strategy of emergency management mobile edge computing in different scenarios. Under the single task delay constraint, the unloading optimization strategy takes the minimum total delay of the system as the performance index. The fireworks algorithm is used to optimize the terminal task unloading decision. After determining the unloading decision, the allocation of computing resources is obtained through convex optimization. Finally, the simulation results show that the computational unloading optimization strategy can effectively reduce the total delay of the system. In order to verify the effectiveness of the emotional model, this study uses the emotional relationship scale, which was compiled by Professor Cao Hualiang in 1999. It includes 28 items and four dimensions (emotional conversation, emotional communication and making friends, dealing with people, heterosexual communication), and each dimension has 7 questions. The scale belongs to self-report scale, which answers “right” or “wrong” according to their actual situation, and evaluates individual interpersonal relationship according to the score. It has good reliability and validity, and has been widely used in domestic interpersonal relationship research. The internal consistency coefficient of the scale in this study is 0.854. RESULTS: Based on the emotional computing combined with edge computing emergency management unloading network model, taking the maximum processing delay allowed for each computing task as the constraint condition, an optimization strategy of emergency management edge computing unloading was proposed. By introducing convex optimization based on fireworks algorithm, the unloading optimization strategy of co-fwa is established. In order to minimize the total delay of the whole network, the improved fireworks algorithm is used to solve the established model, and the computational unloading decision and resource allocation scheme are obtained. Simulation results show that the algorithm can effectively reduce the total task delay of the network system under the constraint of ensuring the maximum calculation delay of a single task. CONCLUSION: Based on the idea of cognitive psychology and the combination of peace and war, this paper expounds that the emergency management system should be divided into peacetime system and wartime system, designs different emergency management mobile edge computing unloading network models and wartime emergency management mobile edge computing unloading network models, and puts forward the optimization strategy of emergency management mobile edge computing unloading based on the combination of emotional computing and edge computing, Finally, the effectiveness of the proposed computational offload optimization strategy is verified by simulation experiments. However, in this study, only the delay element under the edge computing network architecture is considered, but in practical application, the edge computing server and terminal equipment will also be limited by cost and energy consumption. Therefore, in the future research, the cost and energy consumption of the system will be further considered under the current research framework. ACKNOWLEDGEMENTS: Supported by a project grant from Shenyang Science and technology plan (Grant No.21-108-9-15) and Supported by a project grant from Liaoning University excellent talents support plan (Grant No.2020).