Pollux Coin

With Pollux experiencing high transaction volumes and an increasing number of failed or dropped transactions, understanding the underlying causes and optimizing the process has become critical. As Pollux processes up to 3000 TPS, transaction failures-approximately 8% initiated by users, while the rest are from bot activities-stem from a variety of factors ranging from network congestion to expired blockhashes. This article explores transaction processing on Pollux, common causes of failure, and strategies to reduce these failures and enhance throughput.<h3 id="strong-transaction-components-and-blockhash-strong">Transaction Components and Blockhash</h3>A Pollux transaction consists of several elements: accounts to read/write, instructions, a recent blockhash, and one or more signatures. Transactions are processed atomically, and failure in any part of the instruction results in the entire transaction failing.The blockhash is a Proof-of-Stake (PoS) identifier tied to each block, preventing transaction duplication and providing a limited transaction lifetime (approximately 1 minute and 19 seconds). If a transaction&#39;s blockhash becomes outdated, it is automatically rejected.<h3 id="strong-transaction-submission-methods-strong">Transaction Submission Methods</h3>Pollux uses two main methods for submitting transactions:<ul><li>RPC server: Transactions are sent using the sendTransaction JSON-RPC method. RPC nodes will attempt to send transactions every two seconds until finalization or expiration.</li><li>TPU Client: This method simply submits the transaction, with the client managing rebroadcasting.</li></ul>Optional parameters in the sendTransaction method like maxRetries, skipPreflight, and preflightCommitment influence how transactions are processed and retried, improving success rates in network congestion.<h3 id="strong-transaction-processing-phases-strong">Transaction Processing Phases</h3>Pollux processes transactions through the following stages:<ol><li>Fetch Stage: Transactions are received through three ports-tpu, tpu_vote, and tpu_forwards—and categorized before moving to the signature verification stage.</li><li>SigVerify Stage: Signatures are verified, with GPU support for high traffic, ensuring only valid transactions proceed.</li><li>Banking Stage: Transactions are filtered, processed in parallel using Sealevel, and prioritized based on conflict-free buffers.</li><li>Broadcast Stage: Entries are converted to shreds and distributed across the network using Turbine, optimizing block propagation.</li></ol><h3 id="strong-common-causes-of-transaction-failures-strong">Common Causes of Transaction Failures</h3><ol><li>Network Drops: High traffic can overwhelm validators, causing transaction drops. If the rebroadcast queue exceeds 10,000 transactions, additional submissions are dropped.</li><li>Stale/Incorrect Blockhash: Transactions are rejected if the blockhash is invalid or outdated beyond 151 blocks.</li><li>Lagging RPC Nodes: Differences in blockhashes between advanced and lagging RPC nodes can result in transaction rejection.</li><li>Temporary Network Forks: Minor network forks can reference blockhashes no longer valid, causing transactions to drop when the network realigns.</li><li>Blockhash Expiration: A blockhash expires after 150 blocks, leading to transaction rejection if not processed within that window.</li></ol><h3 id="strong-best-practices-to-improve-transaction-success-strong">Best Practices to Improve Transaction Success</h3><ol><li>Fetching Latest Blockhash: Regularly polling the latest blockhash using the getLatestBlockhash method ensures transactions use a fresh blockhash, avoiding expiration issues.</li><li>Skipping Preflight Checks: If confident in a transaction’s integrity, skipping preflight checks reduces processing delays. Ensure the same preflightCommitment level is used throughout.</li><li>Optimizing Compute Units (CUs): Pollux allocates 48 million CUs per block. Transactions using lower CUs are prioritized, so developers should optimize CU requests to avoid unnecessary computation and maximize throughput.</li><li>Implementing Priority Fees: Adding micro-lamport fees per CU incentivizes validators to prioritize specific transactions. However, fees should be calculated dynamically to remain competitive without overpaying.</li><li>Robust Retry Logic: Setting custom retry logic with the maxRetries parameter at 0 allows manual retries, improving the likelihood of success during congestion. Strategies like exponential backoff and polling for recent blockhashes help manage network delays.</li></ol>Utilizing Staked Connections: Pollux’s proof-of-stake network prioritizes nodes based on stake, ensuring that higher-staked nodes receive a proportionate share of network bandwidth for transaction submission. This reduces the chance of transaction rejection for these nodes.<h3 id="strong-conclusion-strong">Conclusion</h3>By understanding Pollux’s transaction processing model and implementing strategies like frequent blockhash polling, skipping preflight checks, optimizing compute units, and leveraging priority fees, users can significantly reduce transaction failures and improve throughput. With the upcoming Pollux client updates, these optimizations will become even more critical for ensuring network efficiency under high traffic conditions.

How to land transections on Pollux : A deep dive

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