# Reputation Consensus Mechanism for Blockchain Based on Information-Centric Networking
## 4 Design
### Hybrid Consensus Mechanism
#### 4.2.1 Reputation Consensus Mechanism
In contrast to Ethereum's use of RANDAO [48] to randomly select proposers, RepuCN prioritizes the selection of ICN nodes with superior network service quality and performance to propose checkpoint blocks, focusing more on efficiency and contribution incentives. #### 5.2.1 Incentives for Long-Term Participation

* Reputation and Rewards: Nodes accumulate reputation through sustained honest participation and high service quality, earning proposal rewards to incentivize long-term involvement. * Penalty Mechanism: Malicious actions (e.g., invalid proposals) result in reputation loss and staked assets being forfeited, thus ensuring honest behavior. * Dynamic Balance: Regular blocks select proposers randomly, preventing monopolization by high-reputation nodes and encouraging broad participation. #### 5.2.2 Fairness and Decentralization

* Hybrid Consensus: Proposal rights for regular blocks are open to all nodes in the network, preventing resource centralization. * Objective Evaluation: The reputation of nodes is determined by on-chain assets and the network contributions measured by third parties, ensuring fairness. * Flexible Adjustment: The reward ratio and checkpoint interval parameters are adjustable based on specific network applications, further optimizing reward distribution for network proposers while balancing efficiency and decentralization. ### Fairness Analysis

In traditional PoS mechanisms, block proposers are selected from validators through the RANDAO random selection algorithm, with the probability of selection being proportional to the amount of staked tokens. However, in real-world networks, entities with greater stakes can increase their chances of proposal selection by deploying additional validators, leading to fairness concerns associated with the concentration of wealth. In contrast, the RepuCN mechanism selects proposers for checkpoint blocks based on the network performance of ICN consensus nodes, with higher-performing nodes having a greater likelihood of being chosen. While this mechanism may result in better-performing nodes receiving more rewards, it also introduces the risk of centralization. However, RepuCN addresses this concern in two ways. First, the proposal mechanism for regular blocks remains the same as that of Casper FFG, with reputation-based consensus applied only to checkpoint blocks, which account for a small fraction (1/32) of the total blocks. Additionally, the interval between checkpoint blocks can be adjusted to strike a balance between efficiency and fairness. Second, higher-performing nodes contribute more significantly to the consistency of network messages, and the rewards they receive can be viewed as a form of contribution-based fairness. ## 6 Evaluation

This section presents a simulation-based evaluation of RepuICN's performance. We first describe the experimental setup and assumptions, including platform configuration, implementation, and evaluation metrics. Then, we compare the RepuICN protocol with the Casper FFG consensus protocol and provide a comprehensive analysis of the simulation results. ### Experimental Setup

#### 6.1.1 Implementation

Conducting experiments on actual public blockchain networks is challenging; therefore, we utilize simulation experiments based on JABS [49] and SimBlock [50, 51] to validate our theoretical analysis. JABS is an open-source platform that supports multiple new consensus algorithms, while SimBlock is an event-driven blockchain network simulator that allows all nodes in the network to generate messages and block times. We implemented the RepuICN protocol on JABS to evaluate its performance in terms of block propagation delay, transaction throughput, and bandwidth consumption within an Ethereum network scenario. Additionally, we simulated the impact of proposer node network latency fluctuations on block propagation delay using SimBlock.