Abstract: Abstract: With the rapid development of communication technology， the number of mobile devices is constantly increasing， which will also lead to frequent large-scale offloading scenarios. However， solving large-scale offloading problems in polynomial time remains a challenge. In this paper， we propose a bi-level optimization algorithm based on the cooperative computing network architecture， called DCGreedy， which fuses divide-and-conquer and greedy. This algorithm can efficiently solve the offloading strategy and resource allocation scheme of all tasks in polynomial time. It can effectively reduce the total energy consumption of the system while meeting all constraints. We evaluate the performance of DCGreedy based on the total number of tasks meeting deadlines， total system energy consumption， and algorithm runtime in a simulation scenario of at least 400 mobile devices. We conducted extensive experimental comparisons between DCGreedy and four other benchmark algorithms and found that in different scale offloading scenarios， the average total energy consumption of DCGreedy was 2.11% higher than the second ranked algorithm， while the algorithm’s running time was only 0.0049%. This fully confirms that DCGreedy effectively reduces the algorithm’s running time while optimizing system energy consumption.

Key words: Key words: large-scale offloading, divide-and-conquer, greedy, mobile edge computing