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README.md

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@@ -41,7 +41,7 @@ Let's consider a scenario where the data is not located on a single machine but
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<h3>Data Collision Concept</h3>
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<p>
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Above we discussed how the data is stored on the active machines of the identifier space but what if more than one key hashes to a same id(eg. "Awesome Game" & "Good Movie" noth hash to value of 10)? In order solve this problem we use the concept of chaining lists. Every node of the binary search tree of a machine holds a singly linked list instead of just holding a single key/value pair. Whenever more than two keys hash to the same id they are inserted in the relevant linked list of BST(Binary Search Tree) of the machine. And to keep track or distinguish a key/value pair of that linked list we use a unique "encryption key" which is associated with every key/value pair of that linked list. This "encryption key" is generated from the same hash function which hashes the simple key to hashed-key. The term DHT which was used earlier is just the concept of hashing a key and then storing its value somewhere. We have already discussed this hashing and storing in detail above.
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Above we discussed how the data is stored on the active machines of the identifier space but what if more than one key hashes to a same id(eg. consider "Awesome Game" & "Good Movie" now both hash to value of 10)? In order solve this problem we use the concept of chaining lists. Every node of the binary search tree of a machine holds a singly linked list instead of just holding a single key/value pair. Whenever more than two keys hash to the same id they are inserted in the relevant linked list of BST(Binary Search Tree) of the machine. And to keep track or distinguish a key/value pair of that linked list we use a unique "encryption key" which is associated with every key/value pair of that linked list. This "encryption key" is generated from the same hash function which hashes the simple key to hashed-key. The term DHT which was used earlier is just the concept of hashing a key and then storing its value somewhere. We have already discussed this hashing and storing in detail above.
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</p>
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<br/><br/>
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<h2>Development Team</h2>

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