Volume 8 , Issue 1 , PP: 21-32, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Mustafa El-Taie 1 , Aaras Y. Kraidi 2 *
Doi: https://doi.org/10.54216/IJWAC.080103
The era of independent, secure, and scalable networks and applications that Web3.0 promised has arrived. The resilience and reliability of the network are directly tied to the architecture of the consensus mechanisms used in this context. In the paper "Crafting resilient consensus mechanisms for the Web3.0 network through edge intelligence," the authors describe a novel approach to strengthening consensus protocols by leveraging edge computing and artificial intelligence. The primary purpose of this project is to improve Web 3.0 security by implementing consensus methods based on edge intelligence. The goal of this attempt is to reduce the inefficiencies, scalability challenges, and environmental concerns associated with more conventional approaches such as proof-of-work and proof-of-stake. The proposed method combines real-time network research with local transaction verification. This eventually leads to more scalable, secure, and effective consensus procedures, which increases the resilience and greatly decreases the cost of Web3.0 networks.The proposed method recognizes the inefficiencies, lack of scalability, and environmental unfriendliness of standard consensus procedures like the Proof of Work (PoW) and Proof of Stake (PoS) consensus processes. This approach makes use of edge intelligence in real time to assess the state of the network and make appropriate adjustments in response. What emerges is a consensus process that is greener, more scalable, and more successful overall. In addition, we provide the local transaction verification (LTV) technique, which allows edge nodes to validate transactions locally, therefore reducing latency and maximizing transaction efficiency. Our findings demonstrate how edge intelligence might improve Web3.0 consensus processes. Extensive simulations and tests show that the suggested approaches outperform conventional consensus mechanisms in terms of efficiency, security, and scalability. Cost reductions for Web3.0 network operators are also emphasized to emphasize the value of our strategy. Consensus procedures for Web3.0 networks that include edge intelligence provide a viable path toward attaining the required resilience, efficiency, and scalability. This study lays the way for a new age of distributed systems, guaranteeing the resiliency and flexibility essential to the success of Web3.0.
Blockchain , Cryptocurrency , Decentralization , Edge Computing , Internet of Things (IoT) , Machine Learning , Security , Smart Contracts , Web3.0 , Edge Intelligence
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