Deduplication detects and eliminates duplicated data but incurs overhead from disk fragmentation, data comparison costs, and write latency increases. To mitigate these issues, the deduplication process can be decentralized, caches can store fingerprints (hashes) of data, and larger deduplication unit sizes like files or sequences of blocks larger than 4KB can be used, though this may decrease the deduplication rate.

1. Data deduplication
• Deduplication
– Detect and eliminate duplicated data
• Deduplication overhead
– Disk fragmentation(read latency ), data comparison
cost(write latency )
• Mitigate deduplication overhead
– Decentralize dedup process
– Use cache for fingerprint(hash) of data
– Use large Dedup unit size
• File, sequence of data blocks, and larger block size than 4KB
• (but, dedup rate )