Enhancing the raft consensus algorithm
Barma Vishwanth, Talakoti Snigdha
Raft consensus algorithm, machine learning, federated learning, privacy.
Use of IOT devices increased rapidly and most of the data is collected, that data is being developed into smart data to understand the activities of users in public spaces. Huge data sets are difficult to analyse using traditional processing techniques, so organisations turned to conversion of smart data by using advanced AI and Machine Learning techniques. To ensure data transparency and privacy for personal and sensitive information, private blockchains are applied with Raft Consensus algorithm. Huge data results in more number of nodes which increase transactions and number of messages. To reduce overall system degradation, the collected transactions are divided into certain amount of transactions into cells, where these cells are optimised in the blockchain system using Raft algorithm. Therefore, we developed an algorithm which is cell based and reduces massive transactions in the smart data market.
Article Details
Unique Paper ID: 163668

Publication Volume & Issue: Volume 10, Issue 11

Page(s): 2446 - 2453
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