Abstract
Several trusted tasks use consensus algorithms to solve agreement challenges. Usually, consensus agreements are used to ensure data integrity and reliability in untrusted environments. In many distributed networking fields, the Proof of Work (PoW) consensus algorithm is commonly used. However, the standard PoW mechanism has two main limitations, where the first is the high power consumption and the second is the 51% attack vulnerability. In this paper, we look to improve the PoW consensus protocol by introducing several proof rounds. Any given consensus node should resolve the game of the current round Roundi before participating in the next round Roundi+1. Any node that resolves the game of Roundi can only pass to the next round if a predetermined number of solutions has been found by other nodes. The obtained evaluation results of this technique show significant improvements in terms of energy consumption and robustness against the 51% and Sybil attacks. By fixing the number of processes, we obtained an energy gain rate of 15.63% with five rounds and a gain rate of 19.91% with ten rounds.
Highlights
Distributed computing is a computing field that studies distributed systems (DS) whose components are located on different networked computers spread over different geographies and which communicate by transmitting messages in order to achieve a common goal [1]
In the first scenario shown by Figure 3, we fixed Number of rounds (NbrR) to 5, and we made several tests, during which we increased the number of processes (NbrP = 5, 10, 15, 20) to study the effect of this increase and its influence on the gain
We have proposed an effective and applicable consensus algorithm, and shown that, in blockchain or in any setting where we need an agreement, it is adaptable
Summary
Distributed computing is a computing field that studies distributed systems (DS) whose components are located on different networked computers spread over different geographies and which communicate by transmitting messages in order to achieve a common goal [1]. A consensus can not always be achieved systematically asynchronously Despite this result, it is possible to obtain satisfactory results in practice, as for instance by the non-perfect algorithms of Paxos Lamport [5] (in the context of obvious failures and no Byzantine faults). Shostak and Pease showed in [2], via the Byzantine Generals Problem, that If f is the number of faulty processes, it takes at least 3 f + 1 processes (in total) for the consensus to be obtained. Under these conditions, the PoW technique has ensured the consensus perfectly, but its major problem is the enormous consumption of energy.
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