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With the increase in the size and number of shared risk link groups (SRLGs) in optical wavelength-division multiplexing (WDM) networks, the capacity efficiency of shared-path protection becomes much poorer due to the SRLG-disjoint constraint, and thus the blocking probability becomes much higher. Furthermore, due to severe traps caused by SRLGs, it becomes more difficult to find an SRLG-disjoint backup path with trap avoidance within reasonable computational complexity. As a result, in a mesh WDM network with a large number of SRLGs or a large SRLG size, 100% SRLG failure protection is no longer a practical protection scheme. To solve this problem, we present a new protection scheme called best effort SRLG failure protection, in which we try to provide an SRLG-disjoint backup path by choosing the backup path sharing the least number of SRLGs with the working path; this is to make the impact of SRLG failures as low as possible and accept as many as possible connection requests. As a result, the proposed best effort SRLG failure protection scheme manages to make a trade-off between blocking probability and survivability. 100% SRLG failure protection becomes a special case of best effort SRLG failure protection when the working path and backup path share zero SRLG. Due to the NP-completeness of this problem, we propose a heuristic to find the optimal result of the best effort SRLG-disjoint backup path under dynamic traffic. We formulate the connection survivability against SRLG failures and analyze the possibility of backup sharing under best effort SRLG failure protection. Analytical and extensive simulation results with various network topology and SRLG parameters demonstrate that, compared with 100% SRLG failure protection, the proposed best effort SRLG failure protection scheme offers much better capacity efficiency and much lower blocking probability while keeping survivability as high as possible. This can be explained by the fact that by slightly loosing the SRL- - G-disjoint constraint, shared-path protection will become more capacity efficient and more efficient in overcoming traps.