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Bitcoin, the first and most well-known application of blockchain, is a decentralized digital currency that operates on a peer-to-peer network. The Bitcoin blockchain serves as a public ledger that records all transactions of the cryptocurrency (Catalini & Gans, 2016).
Despite the tremendous success of Bitcoin as a digital currency, it has long been criticized for issues such as performance and resource consumption (Chen et al., 2022). Reasonable competition is unavoidable in the Bitcoin network. However, if a significant number of malicious miners emerge and employ selfish mining tactics to gain higher profits (Yang et al., 2020; Wang et al., 2022), it becomes unfair for legitimate miners. Legitimate miners invest substantial computational power and energy into mining, yet they do not receive the deserved rewards (Franzoni et al., 2022). We aim to address these concerns by obtaining real-time data from the Bitcoin network to evaluate its efficiency. With this data, we can further analyze cheating behaviors within the network and make reasonable adjustments to miners' mining strategies to improve mining efficiency. We are committed to developing a real-time assessment framework for the Bitcoin network, aiming to detect nodes engaging in unfair mining practices and enhance the mining efficiency of legitimate miners within the network. To achieve this goal, it is crucial to obtain relevant data regarding the formation process of the blockchain in the Bitcoin network.
Traceability, known as the ability to trace the process of transactions, is the most noted fundamental characteristic of blockchain technology. For example, a company can record every step of the drug production process on the blockchain, allowing users to trace each stage of drug creation (Martin et al., 2020; Xu et al., 2020). In reality, the formation process of the blockchain in the Bitcoin network is transparent and non-traceable due to resource and efficiency considerations. For users, it is not necessary to know the formation process of the blockchain. But for researchers, inability or failure to trace the formation process of the blockchain makes it difficult to address certain issues. For instance, miners cannot determine if the received block is stale, and users cannot measure the performance of the Bitcoin system. While some blockchain systems offer API interfaces (Harry et al., 2020) to assist researchers in accessing data, these interfaces often fall short in efficiency, performance, and latency, and thus are unable to meet the requirements for real-time analysis. Some existing work (Wang et al., 2022; Zheng et al., 2022; Wong et al., 2019; Mohanta et al., 2020; Chen et al., 2020; Grossman et al., 2017) has proposed methods and implementations to obtain more relevant data in Bitcoin or other blockchain systems to address these issues. But these studies face various challenges regarding data granularity, non-traceability of the blockchain formation process, and the scalability of the framework. Currently, there is no data collection solution specifically designed for the blockchain formation in Bitcoin system, which makes it challenging to conduct research based on the real data from the Bitcoin network.
In this paper, we introduce BitTrace, a data collection framework for blockchain formation in the Bitcoin network. BitTrace is designed using the principles of microservices and a layered architecture. Each layer is responsible for specific functions, including monitoring, data collection, sending, reception, parsing, and storage. Furthermore, each layer can be scaled according to the data volume, ensuring optimal performance of the framework. The framework offers the following advantages: