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Performance and reliability are essential metrics for Arx nodes on the Arcium Network, directly influencing their reputation and participation. Both Computation Customers and third-party stake delegators must critically assess the reputation of Arx nodes. Computation Customers depend on these nodes for reliable and efficient computations, while third-party delegators seek the most dependable Arx nodes to delegate their stake to, aiming to avoid slashing penalties. Some possible criteria includes a) their uptime, b) response time, and c) historical performance to ensure they meet network standards. This onchain reputation serves as a crucial criterion for Computation Customers when selecting Clusters of Nodes and for third-party delegators deciding where to stake their assets.

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Node incentives and rewards structure

Node Operators are incentivized through a dual-source reward system: a) Self-delegation, and b) Third-party delegations Self-delegation ensures that operators have personal stakes in maintaining high performance and reliability, as any failure can result in penalties and loss of reputation. It also covers the costs associated with any migrations, including forced (unexpected) migrations, such as if a node goes offline due to accidents or unforeseen issues. A separate maintenance downtime allowance system also exists. Nodes also benefit from fees collected from third-party delegations, which boost computational capacity and overall earnings. Rewards are distributed equally among all nodes within a Cluster for each computation completed during the network’s epoch cycles. This ensures fairness within the Cluster for specific computations. For details on base pricing and priority fee markets, see Pricing and incentives. However, nodes with good reputations, such as consistent uptime or high processing capabilities, can attract more opportunities. These nodes are often included in multiple Clusters or receive higher job volumes within their assigned Clusters, increasing their overall rewards indirectly through their reputation and workload. This distinction highlights how nodes can use their performance and reliability to enhance their earning potential beyond the baseline distribution mechanism.