� priority should be large enough to allow block proposers to gossip their

? priority should be large enough to allow block

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λ priority should be large enough to allow block proposers to gossip their priorities and proofs. Measurements of mes- sage propagation in Bitcoin’s network [ 18 ] suggest that gos- siping 1 KB to 90% of the Bitcoin peer-to-peer network takes about 1 second. We conservatively set λ priority to 5 seconds. λ block ensures that Algorand can make progress even if the block proposer does not send the block. Our experiments (§10) show that about 10 seconds suffices to gossip a 1 MB block. We conservatively set λ block to be a minute. λ step should be high enough to allow users to receive messages from committee members, but low enough to allow Parameter Meaning Value h assumed fraction of honest weighted users 80% R seed refresh interval (# of rounds) 1,000 (§5.2) τ proposer expected # of block proposers 26 (§B.1) τ step expected # of committee members 2,000 (§B.2) T step threshold of τ step for BA 68.5% (§B.2) τ final expected # of final committee members 10,000 (§C.1) T final threshold of τ final for BA 74% (§C.1) MaxSteps maximum number of steps in Binary BA 150 (§C.1) λ priority time to gossip sortition proofs 5 seconds λ block timeout for receiving a block 1 minute λ step timeout for BA step 20 seconds λ stepvar estimate of BA completion time variance 5 seconds Figure 4 : Implementation parameters. Algorand to make progress (move to the next step) if it does not hear from sufficiently many committee members. We conservatively set λ step to 20 seconds. We set λ stepvar , the estimated variance in BA completion times, to 10 seconds. 10 EVALUATION Our evaluation quantitatively answers the following: What is the latency that Algorand can achieve for con- firming transactions, and how does it scale as the number of users grows? (§10.1) What throughput can Algorand achieve in terms of trans- actions per second? (§10.2) What are Algorand’s CPU, bandwidth, and storage costs? (§10.3) How does Algorand perform when users misbehave? (§10.4) Does Algorand choose reasonable timeout parameters? (§10.5) To answer these questions, we deploy our prototype of Algorand on Amazon’s EC2 using 1,000 m4.2xlarge virtual machines (VMs), each of which has 8 cores and up to 1 Gbps network throughput. To measure the performance of Algo- rand with a large number of users, we run multiple Algorand users (each user is a process) on the same VM. By default, we run 50 users per VM, and users propose a 1 MByte block. To simulate commodity network links, we cap the bandwidth for each Algorand process to 20 Mbps. To model network la- tency we use inter-city latency and jitter measurements [ 53 ] and assign each machine to one of 20 major cities around the world; latency within the same city is modeled as negligible. We assign an equal share of money to each user; the equal distribution of money maximizes the number of messages that users need to process. Graphs in the rest of this section plot the time it takes for Algorand to complete an entire round, and include the minimum, median, maximum, 25th, and 75th percentile times across all users.
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  • Spring '19
  • NA
  • hash function, Cryptographic hash function, Algorand

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