EASL:用于区块链上敏捷区块数据检索的增强型仅附加跳转列表索引

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Jared Newell, Sabih ur Rehman, Quazi Mamun, Md Zahidul Islam
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引用次数: 0

摘要

区块链的弱点被广泛认为是,由于数据块的顺序结构,检索数据需要线性的时间成本。为了解决这个问题,传统方法依赖于应用于区块链每个副本的数据库索引技术。然而,这只能部分解决问题,因为如果索引不是分布式的,区块链网络中的设备就无法使用。如果要在区块链中整合和分发索引,那么不变性这一独特属性就要求采用更具创新性的方法。为此,我们提出了增强型仅附加跳转列表(EASL)。这种专门的索引技术在区块链中利用二进制搜索和跳转列表,从而使数据检索的成本降至亚线性。EASL 索引技术由每个新添加的区块链区块维护,利用明确记录的索引结构增强了可读性和稳健性。我们提出的技术比其前身--确定性只附加跳转列表(DASL)索引技术--计算效率提高了 42%,存储消耗效率提高了 60%。这是通过敏捷的数据检索实现的,从而减少了维护索引的计算工作量和检索区块链数据的网络带宽,节约了能源成本。该技术的代码已在 GitHub {https://github.com/jarednewell/EASL/} 上公开,以加快未来的研究并鼓励这种有效数据索引的实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EASL: Enhanced append-only skip list index for agile block data retrieval on blockchain
The weakness of blockchain is widely recognised as the linear, temporal cost required for retrieving data due to the sequential structure of data blocks. To address this, conventional approaches have relied on database indexing techniques applied to each individual replica copy of a blockchain. However, this only partially addresses the problem, because if the index is not distributed it is not available for devices in the blockchain network. If an index is to be incorporated and distributed within blockchain, the unique attribute of immutability necessitates a more innovative approach. To that end, we propose an Enhanced Append-only Skip List (EASL). This specialised indexing technique utilises binary search with skip lists in blockchain, resulting in a sublinear cost for data retrieval. The EASL indexing technique is maintained by each newly appended blockchain block and offers enhanced readability and robustness using an explicitly recorded index structure. Our proposed technique is 42% more efficient in computing and 60% more efficient in storage consumption than its predecessor, the Deterministic Append-only Skip List (DASL) indexing technique. This is achieved through agile data retrieval, resulting in energy cost savings from less computational effort to maintain the index, and less network bandwidth to retrieve blockchain data. The code for the proposed technique is publicly available on GitHub {https://github.com/jarednewell/EASL/}, to expedite future research and encourage the practical application of this effectual data index.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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