Redundancy and Data Repair
Ensures continuous data availability and recovery.
DÆTA implements advanced redundancy and data repair mechanisms to ensure high data availability and durability.
Redundancy Strategy
Reed-Solomon Erasure Coding: Enables data recovery with fewer shards than the original total.
Geographic Distribution: Shards are stored on nodes in different physical locations.
Dynamic Redundancy: Adjusts based on file importance and network conditions.
Redundancy Configuration
{
"file_id": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
"total_shards": 30,
"required_shards": 20,
"distribution": {
"continent": {
"max_shards_per_continent": 10,
"min_continents": 3
},
"country": {
"max_shards_per_country": 5,
"min_countries": 6
}
}
}
Data Repair Process
Continuous Monitoring: Satellites regularly check shard availability.
Threshold Detection: Repair process initiated when available shards approach the minimum threshold.
Shard Regeneration: Missing shards are reconstructed using available data.
Replication: New shards are distributed to maintain desired redundancy.
def repair_file(file_id):
shards = get_file_shards(file_id)
available_shards = [s for s in shards if s.is_available()]
if len(available_shards) <= file.required_shards:
reconstruct_and_redistribute(file_id, available_shards)
elif len(available_shards) < file.total_shards:
regenerate_missing_shards(file_id, available_shards)
def reconstruct_and_redistribute(file_id, available_shards):
original_data = reconstruct_data(available_shards)
new_shards = generate_new_shards(original_data, file.total_shards)
distribute_shards(new_shards)
def regenerate_missing_shards(file_id, available_shards):
missing_shard_count = file.total_shards - len(available_shards)
new_shards = generate_additional_shards(available_shards, missing_shard_count)
distribute_shards(new_shards)By implementing this architecture, DÆTA ensures a robust, scalable and resilient decentralized storage network that can adapt to changing conditions and maintain high data integrity and availability.
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