The proposed PoR consensus mechanism is designed to improve resilience against Byzantine failures by enabling reliable pairwise decision making under distributed adversarial environments and minimizes communication overhead during the block finalization by considering first two third of node responses, thereby enhancing the overall network throughput.
Abstract
In recent times, industries are expanding globally to meet the needs of growing population. Government and other regulatory bodies monitor industries to ensure compliance with standards particularly discharges that may pose threat to nearby residents. However, regulatory bodies often struggle with limited human resources that hinder the effectiveness of audit. This issue can be addressed by installing Internet of Things (IoT) devices in the industry to collect the data and store it on the servers, enabling regulatory bodies to review it remotely and conduct onsite inspection when anomalies detected. The challenging aspect is that the centrally stored data are vulnerable to cyberattacks and it can be tampered. Blockchain technology can provide a promising solution as it stores the data in the distributed ledger that is inherently tamper proof. However, using blockchain to store the data collected by IoT devices face challenges related to scalability. Further, latency will be also a concern due to the time taken by the consensus mechanism to validate the blocks and add them to the chain. To address these challenges, we introduce a novel consensus algorithm named Proof of Reward (PoR) tailored for applications demanding high throughput. The PoR consensus mechanism is designed to improve resilience against Byzantine failures by enabling reliable pairwise decision making under distributed adversarial environments. Further, the proposed consensus minimizes communication overhead during the block finalization by considering first two third of node responses, thereby enhancing the overall network throughput. The communication overhead of the proposed consensus is 34.78% lesser compared to Practical Byzantine Fault Tolerance (PBFT) and 18.55% lesser compared to Istanbul Byzantine Fault Tolerant (IBFT). The obtained results highlight the effectiveness of the proposed consensus algorithm.
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