When scheduling a set of real-time tasks, researchers can choose between preemptive and non-preemptive algorithms. However, these algorithms each have their own advantages and drawbacks, necessitating specific analysis in different contexts. In contrast to these two extremes, researchers have proposed the concept of limited-preemption algorithms. Such limited-preemption algorithms serve as feasible alternatives to the former two approaches. Currently, research on this algorithm is based on a homogenous computing environment.In this paper, we investigate the fixed-preemption point method in limited-preemption algorithms. We compare the impact of limited-preemption EDF algorithm on the performance of homogenous multiprocessors under different fixed-preemption strategies. We introduce a preemptive strategy where high-priority tasks can only be preempted at the most suitable fixed-preemption points, and we provide an effective schedulability analysis for this strategy. The EDF scheduling algorithm based on the best-fit fixed preemption strategy is called the Best Preemptive EDF(BP-EDF). We have introduced an effective schedulability analysis for BP-EDF. Experimental results indicate that the strategy with the most suitable fixed-preemption points demonstrates superior schedulability compared to the other two strategies. Furthermore, its performance in terms of task preemption frequency closely approaches that of the strategy employing fixed-preemption at the lowest priority points.