Storage efficient blockchain models for constrained applications

Rajendra, Yuvaraj; Sahu, Sachin; Venkatesan, S.; Shukla, Sandeep K.

doi:10.1007/s10586-022-03804-y

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…While blockchain technology offers substantial benefits, there are challenges that must be addressed when adopting it in healthcare information systems: Transaction Speed: Blockchains, such as Bitcoin, often have unsatisfying transactions per second (TPS) and may experience congestion during the transmission of healthcare information, requiring higher throughput ( 8 ). In response to this challenge, Layer 2 scaling solutions like Lightning Network for Bitcoin or Sidechains for Ethereum may hold promise as resolution ( 9 , 10 ).…”

Section: Challenges To Overcomementioning

confidence: 99%

Revolutionizing healthcare information systems with blockchain

Wu,

Wang

2024

Front. Digit. Health

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Section: Challenges To Overcomementioning

confidence: 99%

Revolutionizing healthcare information systems with blockchain

Wu,

Wang

2024

Front. Digit. Health

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“…Each transaction in a blockchain is represented as a set of binary data, which includes information such as the sender and the receiver addresses, the transaction data, and the transaction timestamp. A collection of transactions verified and added to the blockchain network form a block [7], [8].…”

Section: Introductionmentioning

confidence: 99%

A Binary Matrix-Based Data Representation for Data Compression in Blockchain

Laouid,

Mostefa,

Al-Khalidi

et al. 2023

2023 Fifth International Conference on Blockchain Computing and Applications (BCCA)

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Blockchain relies on storing and verifying a large volume of data across multiple nodes, making efficient data compression techniques crucial. By reducing the size of data, compression techniques enable more data to be stored within the limited space constraints of the blockchain networks. Furthermore, compressed data consumes less bandwidth for transmission and enhances the overall performance of blockchain networks by reducing the time and resources needed for data storage and retrieval. To overcome this issue, this paper presents a new data representation approach to enable efficient storage and management of diverse data types on the blockchain, ensuring scalability, cost-effectiveness, and improved network efficiency. A binary matrix M of size m x n bits can be converted to two vectors H and V of sizes m' and n', respectively. The compression rate expressed by (m l +n l + 1Hash(M) I) x 100/(mxn) increases exponentially, i.e., 2.\ with A depends on m and n); this makes the proposed technique is very effective in data size reduction. With a matrix, for example, M = 512 x 512 bits, we achieve a rate of reduction equal to 96.42%. The original data can be recovered using H, V, and Hash(M). The conversion from M to (H, V) is simple, which optimizes energy consumption for low-power devices. Meanwhile, the challenge of recovering the original data could be exploited in a blockchain process, where the mining consensus could be identified based on the node that recovered a predefined set of vectors. Furthermore, this technique ensures that data integrity checking is available only at the nodes with a massive computation capacity.

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