ACM, the Association for Computing Machines, today announced the inaugural edition of ACM Distributed Ledger Technologies: Research and Practice (DLT), a new peer-reviewed journal. Published every three monthsAnd the DLT It publishes a high-quality, interdisciplinary scholarship on research, development, real-world deployment, and/or evaluation of distributed ledger technologies, including blockchain, cryptocurrency, and smart contracts. DLT offers a blend of original research work and innovative, practice-based developments by internationally distinguished experts and researchers in DLT from academia and public and private sector organisations.
In their introductory letter to the journal, co-editors Kim Kwang Raymond Cho and Mohamed Hammouda emphasized that their vision for DLT is “a place where research communities and practitioners, as well as government agencies, can come together, discuss and present DLT related developments, challenges, and opportunities.”
Articles featured in the inaugural issue include:
“Reconsidering the Byzantine fault tolerance for distributed ledgers,” by Yonggee Wang
Byzantine Fault Tolerance (BFT) refers to the ability of a computer system to continue to function even when some of its nodes fail or behave erratically. BFT plays an important role in making distributed ledger technologies work. Due to the popularity of Proof of Stake (PoS) blockchains in recent years, many BFT protocols have been deployed in a wide range of Internet environment. In her paper, Wang analyzes several BFT protocols and suggests their most efficient variation.
“Data Quality Stimulation in Blockchain-Based Systems – The Case of Digital Cardossier,” By Florian Spischegger, Claudio J. Tissoni, Lyudmila Zavolokina, and Gerhard Schwab
The authors investigate how to design incentives for a licensed blockchain-based system in the automotive ecosystem to ensure high-quality data is stored and used by various stakeholders.
“A Mixed Incentive Mechanism for Decentralized Federal Learning,” By Minfeng Qi, Ziyuan Wang, Shiping Chen, Yang Xiang
Federated Learning (FL) is a machine learning approach that allows multiple data owners to build a powerful shared machine learning model without sharing data – thus protecting privacy and security. However, incentivizing data owners to participate in (and remain within) the FL ecosystem by consistently contributing their data to the FL model remains an obstacle to implementing these technologies. In this article, the authors propose a hybrid blockchain-based incentive mechanism to address the above challenge.
“Reinchard: The Perfectly Segmented Dual Blockchain for Concurrency Resolve,” By Vishal Sharma, Zengpeng Li, Pawe Szałachowski, Teik Guan Tan and Jianying Zhou
Decentralized control, low complexity, flexible and efficient communications are the requirements for an architecture that aims to scale the blockchain beyond the current state. The authors, Reinshard, propose a new blockchain that scales more efficiently than current state-of-the-art technologies.
“A trustworthy and scalable infrastructure for collaborative container warehouses,” Written by Franklin Wei, Stephen Tate, Mahlingam Ramkumar and Soumya Mohanty
In-cloud computing containers are becoming ubiquitous. With the increasing availability of ready-made containers, there is a need for methods capable of efficiently securing large repositories of software containers. The authors present a Trusted Container Depot (TCR) system that provides security guarantees (confidentiality, integrity, and authenticity) with respect to such a repository in a scalable manner.
In addition to Co-EiCs Choo and Hammoudeh, the DLT editorial team was drawn from countries around the world including Austria, Australia, Canada, China, Denmark, Dubai, Finland, France, Italy, Norway, Panama, Portugal, Spain, Switzerland, South Korea, the United Kingdom and the United States. The editorial board also includes three senior associate editors and 31 associate editors.
The current call to papers – https://dl.acm.org/journal/dlt/calls-for-papers
A special issue about thriving amid disruptive technologiesApplication deadline: December 1, 2022
Special Edition on Mathematical Research for the Blockchain EconomyApplication deadline: December 1, 2022
Special Issue on Recent Advances in Blockchain Evolution: Architecture and PerformanceApplication deadline: December 15, 2022
ACM, Association for Computing Machinery It is the world’s largest educational and scientific computing community, uniting computing educators, researchers, and professionals to inspire dialogue, share resources, and address field challenges. ACM strengthens the collective voice of the computing 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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