  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.
