As intelligent terminal devices become more and more common in daily life, the amount of work involved in computer work is increasing. Excessive task migrations can create significant resource stress on edge servers and ultimately have a negative impact. In this paper, we introduce four parameters and weight ratio factors to address the issue of imbalanced distribution of computational resources among edge servers in the field of edge computing. Compared with the traditional serial task processing structure, the edge collaborative parallel task processing architecture proposed in this paper improves the resource utilization by 40 \(\%\) on average, and the task processing time is shortened by 8 times on average. In addition, compared with the existing task scheduling algorithms in the edge collaborative parallel task processing architecture, the proposed fair collaboration strategy can effectively reduce the average CPU utilization of edge servers by nearly 10 \(\%\) , providing more computing resources. The average task processing latency is reduced by 0.9 s compared to the greedy algorithm and 0.1 s compared to the genetic algorithm.