<p>With the rapid development of mobile devices and Internet of Things (IoT) applications, Mobile Edge Computing (MEC), as an emerging computing architecture, has received widespread attention. MEC significantly reduces the latency and improves the real-time performance by deploying the computing resources at the edge of the network, especially in the real-time demanding application scenarios, such as smart home, autonomous driving, and virtual reality, which show great potential. However, with the increase in the number of users and the diversification of task demands, the computational pressure faced by a single MEC node is increasing, and the traditional centralized computation model gradually becomes insufficient. To cope with this challenge, multi-MEC collaboration has become an important research direction. In this paper, we explore the resource management and task allocation problems in multi-MEC collaboration systems, and propose a dynamic scheduling algorithm based on Lyapunov optimization to improve resource utilization and system stability. By optimizing the allocation and scheduling of computing resources, this paper aims to achieve load balancing and improve the overall system performance to meet the increasing user demand.</p>