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Blockchain and distributed ledger technologies rely on distributed consensusalgorithms. In recent years many consensus algorithms and protocols have beenproposed; most of them are for permissioned blockchain networks. However, theperformance of these algorithms is not well understood. This paper introducesan approach to evaluating consensus algorithms and blockchain platforms in ahostile network environment with the presence of byzantine and other networkfailures. The approach starts by using stochastic modeling to model thebehaviors of consensus algorithms under different typical and faultyoperational scenarios. Next, we implemented a blockchain application usingdifferent consensus protocols and tested their performance using chaosengineering techniques. To demonstrate our generic evaluation approach, weanalyze the performance of four permissioned blockchain platforms and theirconsensus protocols. Our results showed that stochastic modeling is aninexpensive and efficient technique for analyzing consensus protocols. But theydo not represent the actual performance of the consensus protocols in aproduction environment. Moreover, an experiment with chaos engineeringindicates that if two different blockchain platforms use the same blockchainalgorithm or protocol, we should not assume they will have similar performance.Therefore, It is also essential to consider the role of platform architectureand how the protocols are engineered in a given platform.

Evaluating Permissioned Blockchain Using Stochastic Modeling and Chaos Engineering