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Adaptive Parameter Adjustment of Local Repair Codes in Decentralized Storage Network Data Redundancy Strategies
This paper explores adaptive parameter tuning for local repair codes in decentralized storage networks. By analyzing network dynamics and data access patterns, we propose a dynamic adjustment mechanism that optimizes redundancy levels based on real-time storage demands. Simulation results demonstrate improved fault tolerance and reduced storage overhead, enhancing the efficiency and robustness of decentralized data redundancy strategies.
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