ACM, the Association for Computing Machinery, today announced the inaugural issue of ACM Distributed Ledger Technologies: Research and Practice (DLT), a new peer-reviewed journal. Published quarterly, DLT publishes high-quality, interdisciplinary scholarships for research and development, real-world deployment, and/or evaluation of distributed ledger technologies, including blockchain, cryptocurrency, and smart contracts. DLT offers a mix of original research and innovative, practice-oriented advances by internationally renowned DLT experts and academic researchers and public and private sector organizations.
In their introductory letter for the journal, co-editors Kim-Kwang Raymond Choo and Mohammad Hammoudeh emphasize that their vision of DLT is “a place where the research and practice communities, as well as government agencies, can to meet, discuss and present DLT and related advances, challenges and opportunities.”
Articles featured in the inaugural issue include:
“Byzantine Fault Tolerance for Distributed Ledgers Revisited”, by Yonggee Wang
Byzantine Fault Tolerance (BFT) refers to the ability of a computer system to continue functioning even when some of its nodes fail or act erratically. BFT plays an important role in the operation of distributed ledger technologies. Due to the popularity of Proof of Stake (PoS) blockchains in recent years, several BFT protocols have been widely deployed in the Internet environment. In his article, Wang analyzes several BFT protocols and proposes his own more efficient variant.
“Incentive for data quality in blockchain-based systems – The case of the digital Cardossier”, by Florian Spychiger, Claudio J. Tessone, Liudmila Zavolokina and Gerhard Schwabe
The authors investigate how incentives for an authorized blockchain-based system in the automotive ecosystem can be designed to ensure high-quality data storage and usage by different stakeholders.
“A Hybrid Incentive Mechanism for Decentralized Federated Learning”, by Minfeng Qi, Ziyuan Wang, Shiping Chen and Yang Xiang
Federated Learning (FL) is a machine learning technique that allows multiple data owners to build a common robust machine learning model without sharing data, thereby protecting privacy and security. However, motivating data owners to participate in (and stay in) an FL ecosystem by continuously contributing their data to the FL model remains a barrier to implementing these techniques. In this article, the authors propose a blockchain-based hybrid incentive mechanism to address the above challenge.
“Reinshard: Optimally Shared Dual Blockchain for Concurrency Resolution”, by Vishal Sharma, Zengpeng Li, Paweł Szałachowski, Teik Guan Tan and Jianying Zhou
Decentralized control, low complexity, flexible and efficient communications are the requirements of an architecture that aims to evolve blockchains beyond the current state. The authors propose Reinshard, a new blockchain that scales more efficiently than current state-of-the-art techniques.
“A scalable and reliable infrastructure for collaborative container repositories”, by Franklin Wei, Stephen Tate, Mahalingam Ramkumar and Somya Mohanty
Containerization of cloud computing has become ubiquitous. As the availability of pre-built containers increases, there is a need for methods that can effectively secure large repositories of software containers. The authors present a “Trustworthy Container Repository” (TCR) system that provides security guarantees (confidentiality, integrity and authenticity) concerning such a repository in an evolutionary way.
In addition to Co-EiCs Choo and Hammoudeh, the DLT editorial team is made up of countries from around the world, including Austria, Australia, Canada, China, Denmark, Dubai, Finland, France, Italy, Norway, Panama, Portugal, Spain, Switzerland, South Korea, United Kingdom and United States. The editorial board also includes three senior associate editors and 31 associate editors.
Call for papers in progress – https://dl.acm.org/journal/dlt/calls-for-papers
Special Issue on Prospering Amid Disruptive TechnologiesSubmission deadline: December 1, 2022
Special issue on mathematical research for the blockchain economySubmission deadline: December 1, 2022
Special Issue on Recent Advances in Blockchain Evolution: Architecture and PerformanceSubmission deadline: December 15, 2022
ACM, the Association for Computing Machinery, is the world’s largest educational and scientific computing society, bringing together educators, researchers, and computing professionals to inspire dialogue, share resources, and address challenges in the field. ACM strengthens the collective voice of the IT profession through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for lifelong learning, career development and professional networking.
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