While illustrating the difficulty of the network’s global maintenance due to its complexity, the research paper highlights potential percussions of the existing shortcomings of the current coin selection methods. Our work answers the concerns brought to light, proposing a coin selection method that disincentivizes dust creation whilst enhancing the overall performance in the context of UTXO-based cryptocurrencies. Each transaction has a version number, transaction inputs number, several transaction inputs and outputs and lock time.
The Multicriteria Model
If the coin selection strategies are properly designed, the system will be filled with such UTXOs, this may become a burden for normal users to manage 4. There exist an abundance of techniques for multi-objective optimization, some recent ones include particle swarm optimization 21 and deep reinforcement learning 22. However, compared to the classical greedy and genetic algorithms these recent optimization techniques respectively have disadvantages that render them a lesser match compared to the greedy and genetic algorithm. In the case of the particle swarm algorithm, it falls easily into local optimum when working in a higher dimensional space and has a low convergence rate. On the other hand, deep reinforcement learning requires hefty computation, an extensive amount of time, and lack data to train the network. In this section, our proposed strategy to select coins based on the greedy and genetic algorithm will be introduced, as well as the characteristics of this new approach will be examined.
A coin selection strategy based on the greedy and genetic algorithm
Erhardt’s thesis looks at a sample of different wallets and their implemented policies in regards to the effect on transaction fees and the UTXO pool 18. It also introduces the Branch’n’Bound algorithm to find an exact match of the transaction target value. Drawing on quantitative experiment results, Erhardt makes suggestions to the Bitcoin Core’s algorithm on their coin selection method which was later adopted by the developers as a secondary method.
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Although the method we proposed is better than the Bitcoin method in both distance and the number of UTXOs, this algorithm requires more time to solve the problem, as we discussed in section 4. From Table 2, it can be observed that our proposed method does not fall short in performance of UTXO quantity control. Hence, while hitting the target more accurately our method will not create transactions that require excessive transaction fees, this holds true stably. This performance can be clearly perceived in the graphs depicting the comparison of UTXO quantities selected by all three methods in Figs. The transaction outputs will generate new UTXOs, and the transaction inputs consume UTXOs, which are the source of coins. Bitcoin is a decentralized application that uses the UTXO model, in which UTXOs are consumed as transaction input and created by transaction outputs.
- The study is designed to provide a guide to which crypto assets may become more widespread over time.
- Although the time complexity of the Bitcoin method is O(n) , it can not guarantee that method can find solution that is close enough to the optimal solution.
- Thus, our review of related work looks at selection strategies that prioritize target value accuracy 17, 18, enhance the knapsack algorithm 19, and protect user privacy 20.
- Under these circumstances, different users cannot have the same account number.
Support
Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs.
Study investigates crypto selection
We created three identical wallets, with 2000 UTXOs and 10% of dust where the fee-per-byte rate is 22. In each round, a set of UTXOs is summed to assign as the target value of which our proposed algorithm and Bitcoin’s method need to retrieve UTXOs to match. Then, if necessary the change output is added back to the wallets before three identical sets of 200 UTXOs including 10% dust is added to all wallets respectively.
- The unlocking and locking scripts are used respectively to prove that the input UTXOs are owned by the payer and that the output UTXOs are locked to the beneficiary.
- The payer can create and broadcast transactions through the P2P network without going through other third-party platforms.
- This paper proposes a new coin selection strategy based on the greedy and genetic algorithm.
- As greedy algorithm and genetic algorithm are used, the time taken to search for the solution will be extended.
These implications indicate the urgency for an efficient coin selection strategy for UTXO-based cryptocurrencies. A high-performance coin selection method would be one that puts into consideration selecting an appropriate amount of UTXOs to prevent high transaction fees as well as reducing the production of dust by spending low value coins earlier. This paper proposes a new coin selection strategy based on the greedy and genetic algorithm. It aims to make full use of low value coins to reach the transaction amount to prevent dust production and maintain or even possibly reduce the number of coins to avoid excessive transaction fees. However, this algorithm will discriminate against low value UTXO’s, and the sum of the UTXO combination amount is not always the closest solution to the target amount. Thus, the genetic algorithm finds a UTXO combination with the least number of UTXOs and the closest amount to the target amount.
The payer can create and broadcast transactions through the P2P network without going through other third-party platforms. All transactions are stored in the block openly, transparently and distributed. Bitcoin addresses are equivalent to accounts in traditional financial systems, but addresses are not linked to the actual social identity, which protects the privacy of users. There is no relationship between the account and password in the traditional financial system, therefore the account and password are stored in the back-end database.
Under these circumstances, different users study investigates crypto selection cannot have the same account number. Since the Bitcoin system is decentralized, there is no third party to detect whether the account is duplicated, so a specific mathematical relationship between account and password is needed for identification and verification. A private key is a number, and the public key is generated by a one-way encryption function called the elliptic curve multiplication of the private key. For each transaction output, there is a locking script containing a hash of the public key of the beneficiary, declaring who is the beneficiary of this transaction. The unlocking script provides the transaction’s signature generated by private key to prove the beneficiary of the referenced transaction.