Linear amortized complexity describes the average computational cost of an operation over a sequence of operations, where the total cost is proportional to the number of operations. While some individual operations might be expensive, these costs are offset by many inexpensive operations, resulting in an average cost that grows linearly with the input size. This analytical measure provides a more realistic assessment of performance for dynamic data structures. It is a critical concept in algorithm analysis.
Context
In blockchain and distributed systems, understanding linear amortized complexity is important for evaluating the efficiency of data structures and algorithms that process transactions. News related to network upgrades or protocol improvements sometimes touches upon how computational demands are optimized over time. Developers aim for designs that exhibit low amortized complexity to ensure sustainable scalability and performance as network usage increases.
This new aBFT protocol resolves the fundamental throughput-latency tension by concurrently executing transaction dissemination and agreement, ensuring robust censorship resistance.
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