In this thesis, we study temperature-constrained multiprocessor real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processors. We focus on Pfair scheduling algorithms, especially ERfair scheduling scheme (a work-conserving extension to Pfair scheduling) as our main multiprocessor real-time scheduling methodology. Then, we study the benefits of simple reactive speed scaling as described in the real-time multiprocessor systems. In this thesis, in support of the temperature-awareness, we extend the applicability of the reactive speed scaling to global scheduling schemes for multiprocessors. We propose temperature-aware scheduling and processor selection schemes motivated by existing (thermally non-optimal) ERfair scheduling in order to reduce thermal stress and therefore increase the processor utilization. Then, we show that the proposed algorithm and reactive scheme can enhance the processor utilization compared with any constant speed scheme on real-time multiprocessor systems. Additionally, we show how the maximum schedulable utilization (MSU) for partitioning heuristics can be determined on the temperature-constrained multiprocessor real-time systems.