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This paper introduces a novel approach, called Short Leap Shared Protection with spare capacity Reallocation (SLSP-R), to deal with dynamic reconfiguration of spare capacity for MPLS-based recovery in the Internet backbone networks. SLSP-R is based on the SLSP framework and is designed to quantify the impact of computation complexity on network performance. The basic idea for SLSP-R is to subdivide a lengthy optimization process into several subtasks in order to trade the optimization quality with computation time. For this purpose, we compare three strategies for grouping working paths before an integer programming (InP) formulation is solved, namely, the Most Overlapped, Most Diverse, and Randomly Distributed. Analytical modeling of the problem is provided to show the feasibility of the subgrouping strategy. A numerical experiment as well as simulation-based study are conducted on four networks with different topology to evaluate the SLSP-R algorithm. The design methodology to determine the size of each subset of working paths is verified in the simulation.