Resource Fairness and Prioritization of Transactions in Permissioned Blockchain Systems (Industry Track)

Goel, Seep; Singh, Abhishek; Garg, Rajiv Kumar; Verma, Mudit; Jayachandran, Praveen

doi:10.1145/3284028.3284035

Cited by 19 publications

(11 citation statements)

References 8 publications

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“…• Incentive Mechanism: Provide equal incentives to users who participated in the creation of the block [186,187].…”

Section: • Transaction Fairnessmentioning

confidence: 99%

A Taxonomy Study on Securing Blockchain-based Industrial Applications: An Overview, Application Perspectives, Requirements, Attacks, Countermeasures, and Open Issues

Hameed¹,

Barika²,

Garg³

et al. 2021

Preprint

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Blockchain technology has taken on a leading role in today's industrial applications by providing salient features and showing significant performance since its beginning. Blockchain began its journey from the concept of cryptocurrency and is now part of a range of core applications to achieve resilience and automation between various tasks. With the integration of Blockchain technology into different industrial applications, many application designs, security and privacy challenges present themselves, posing serious threats to users and their data. Although several approaches have been proposed to address the specific security and privacy needs of targeted applications with functional parameters, there is still a need for a research study on the application, security and privacy challenges, and requirements of Blockchain-based industrial applications, along with possible security threats and countermeasures. This study presents a state-of-the-art survey of Blockchain-based Industry 4.0 applications, focusing on crucial application and security and privacy requirements, as well as corresponding attacks on Blockchain systems with potential countermeasures. We also analyse and provide the classification of different security and privacy techniques used in these applications to enhance the advancement of security features. Furthermore, we highlight some open issues in industrial applications that help to design secure Blockchain-based applications as future directions.

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“…• Incentive Mechanism: Provide equal incentives to users who participated in the creation of the block [186,187].…”

Section: • Transaction Fairnessmentioning

confidence: 99%

A Taxonomy Study on Securing Blockchain-based Industrial Applications: An Overview, Application Perspectives, Requirements, Attacks, Countermeasures, and Open Issues

Hameed¹,

Barika²,

Garg³

et al. 2021

Preprint

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“…The miners select the transaction having high transaction fee. Realistically, the transaction having low transaction's fee is rarely picked up by the miners [44].…”

Section: Unfair Transaction Selectionmentioning

confidence: 99%

A Study on Public Blockchain Consensus Algorithms: A Systematic Literature Review

Jalal¹,

Shukur²,

Bakar³

2020

Preprint

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The purpose of this study is to present a systematic review of the literature on public blockchain consensus algorithms. Blockchain consensus algorithms have gain much popularity in last few years especially in the cryptocurrency field. Based on a systematic review of the relevant literature, we provide a classification of blockchain consensus algorithms, philosophy behind creation of blockchain consensus algorithms and as well as the rewards and incentive strategies of various public blockchain consensus algorithms. On the basis of these results, the research gaps and future work directions are identified for further study.

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“…Goel et al [25] argued that the default first-in-first-out ordering of transactions is unfair and inefficient. They proposed a weighted fair queuing strategy for ordering transactions which can support different quality of service for different transactions.…”

Section: Related Workmentioning

confidence: 99%

“…Although many recent efforts [34,35,27,25,23,30] have proposed various optimizations to improve the performance of Fabric, none of them have studied the impact of scaling techniques, such as vertical and horizontal scaling, on the performance of Fabric. Hence, in this paper, we study the efficiency of various scaling techniques and identify bottlenecks.…”

Section: Introductionmentioning

confidence: 99%

Scaling Hyperledger Fabric Using Pipelined Execution and Sparse Peers

Thakkar¹,

Natarajan²

2020

Preprint

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Many proofs of concept blockchain applications built using Hyperledger Fabric, a permissioned blockchain platform, have recently been transformed into production. However, the performance provided by Hyperledger Fabric is of significant concern for enterprises due to steady growth in network usage. Hence, in this paper, we study the performance achieved in a Fabric network using vertical scaling (i.e., by adding more vCPUs) and horizontal scaling (i.e., by adding more nodes) techniques. We observe that network scales very poorly with both of these techniques. With vertical scaling, due to serial execution of validation & commit phases of transactions, the allocated vCPUs are underutilized. With horizontal scaling, due to redundant work between nodes, allocated resources are wasted though it is utilized. Further, we identify these techniques to be unsuited for dynamically scaling a network quickly to mitigate an overload situation, and hence, it results in a 30% drop in the performance.To increase the CPU utilization and hence the performance, we re-architect Fabric to enable pipelined execution of validation & commit phases by introducing dirty state management using a trie data structure. Additionally, we facilitated the validation phase to validate transactions in parallel by introducing a waiting-transactions dependency graph. To avoid redundant work performed between nodes and to quickly scale up a network, we propose a new type of peer node called sparse peer, which selective commits transactions. Overall, we improved the throughput by 3× and reduced the time taken to scale up a network by 96%.

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Resource Fairness and Prioritization of Transactions in Permissioned Blockchain Systems (Industry Track)

Cited by 19 publications

References 8 publications

A Taxonomy Study on Securing Blockchain-based Industrial Applications: An Overview, Application Perspectives, Requirements, Attacks, Countermeasures, and Open Issues

A Taxonomy Study on Securing Blockchain-based Industrial Applications: An Overview, Application Perspectives, Requirements, Attacks, Countermeasures, and Open Issues

A Study on Public Blockchain Consensus Algorithms: A Systematic Literature Review

Scaling Hyperledger Fabric Using Pipelined Execution and Sparse Peers

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