In this correspondence, a novel framework is proposed for analyzing data offloading in a multi-access edge computing system. Specifically, a two-phase algorithm, is proposed, including two key phases: 1) user association phase and 2) task offloading phase. In the first phase, a ruin theory-based approach is developed to obtain the users association considering the users' transmission reliability and resource utilization efficiency. Meanwhile, in the second phase, an optimization-based algorithm is used to optimize the data offloading process. In particular, ruin theory is used to manage the user association phase, and a ruin probability-based preference profile is considered to control the priority of proposing users. Here, ruin probability is derived by the surplus buffer space of each edge node at each time slot. Giving the association results, an optimization problem is formulated to optimize the amount of offloaded data aiming at minimizing the energy consumption of users. Simulation results show that the developed solutions guarantee system reliability, association efficiency under a tolerable value of surplus buffer size, and minimize the total energy consumption of all users.

翻译：本文提出了一种新颖的框架，用于分析多接入边缘计算系统中的数据卸载过程。具体而言，提出了一种两阶段算法，包括两个关键阶段：1) 用户关联阶段和2) 任务卸载阶段。在第一阶段，基于破产理论的方法被开发出来，以考虑用户传输可靠性和资源利用效率来获取用户关联。同时，在第二阶段，采用基于优化的算法来优化数据卸载过程。特别地，破产理论用于管理用户关联阶段，并考虑基于破产概率的偏好配置文件来控制提议用户的优先级。此处，破产概率通过每个边缘节点在每个时隙的剩余缓冲区空间推导得出。给定关联结果后，构建一个优化问题来优化卸载数据量，旨在最小化用户的能量消耗。仿真结果表明，所开发的解决方案在容忍的剩余缓冲区大小值下保证了系统可靠性和关联效率，并最小化了所有用户的总能量消耗。