The preemptive scheduling paradigm is known to strictly dominate the non-preemptive scheduling paradigm with respect to feasibility. On the other hand, preemptively scheduling real-time tasks on uniprocessors, unlike non-preemptive scheduling, may lead to unschedulability due to, e.g., preemption related overheads. The limited-preemptive scheduling paradigm, which is a generalization of preemptive and non-preemptive paradigms, has, however, the potential to reduce the preemption related overheads while enabling high processor utilization. In this paper, we focus on the characterization of the effects of increasing the computational resources on the limited-preemptive feasibility of real-time tasks in order to quantify the sub-optimality of limited-preemptive scheduling. Specifically, we first derive the required processor speed-up bound that guarantees limited-preemptive feasibility of any uniprocessor feasible taskset. Secondly, we demonstrate the applicability of the results in the context of controlling preemption related overheads while minimizing the required processor speed-up. In particular, we identify the preemptive behavior that minimizes preemption-related overheads, as well as derive the optimal processor speed associated with it. Finally, we examine the consequences of having more processors on limited-preemptive feasibility and derive the bound on the number of processors that guarantees a specified limited-preemptive behavior for any uniprocessor feasible real-time taskset. This paper essentially bridges the preemptive and non-preemptive real-time scheduling paradigms by providing significant theoretical results building on the limitedpreemptive scheduling paradigm, as well as provides analytical inputs to developers in order to perform various trade-offs, e.g., code refactoring, to control the preemptive behavior of real-time tasks.