In this letter, 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: \emph{1) user association phase} and \emph{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. 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 under a tolerable value of surplus buffer size and minimize the total energy consumption of all users.
翻译:在此信中,提议了一个用于分析多存取边缘计算系统中数据卸载的新框架。 具体地说, 提议了一个两阶段算法, 包括两个关键阶段: \ emph{ { 1 用户关联阶段} 和\ emph{ 2 任务卸载阶段} 。 在第一阶段, 开发了一个基于废理论的方法, 以获取用户协会, 同时考虑到用户传输的可靠性。 同时, 在第二阶段, 使用基于优化算法来优化数据卸载过程。 特别是, 使用废理论来管理用户关联阶段, 并审议一个基于机率的偏好配置来控制推荐用户的优先性。 这里, 毁坏概率来自每个边缘节点在每个时间档的剩余缓冲空间。 给关联结果说明, 优化问题是要优化卸载数据的数量, 以最大限度地减少用户的能源消耗。 模拟结果显示, 开发的解决方案保证系统可靠性, 在可承受的剩余缓冲值下保证系统可靠性, 并最大限度地减少所有用户的能源消耗总量 。