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Supply chain management (SCM) plays a vital role in the global economy, as evidenced by recent COVID-19 supply chain challenges. Traditional SCM faces security and efficiency issues, but they can be addressed by leveraging digital twins…
Distributed implementations are crucial in speeding up large scale machine learning applications. Distributed gradient descent (GD) is widely employed to parallelize the learning task by distributing the dataset across multiple workers. A…
Traditional financial institutions face inefficiencies that can be addressed by distributed ledger technology. However, a primary barrier to adoption is the privacy concerns surrounding publicly available transaction data. Existing private…
With the development of communication technologies in 5G networks and the Internet of things (IoT), a massive amount of generated data can improve machine learning (ML) inference through data sharing. However, security and privacy concerns…
In this research, the evolution of Distributed Ledger Technology (DLT) in supply chains has been mapped from the inception of the technology until June 2020, utilising primarily public data sources. Two hundred seventy-one blockchain…
As a pivotal innovation in digital infrastructure, blockchain ledger technology catalyzes the development of nascent business paradigms and applications globally. Utilizing Rothwell and Zegveld's taxonomy of twelve innovation policy tools,…
Blockchain technology has emerged as a disruptive force with transformative potential across numerous industries, promising efficient and automated solutions that can revolutionize traditional systems. By leveraging decentralized ledger…
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain…
Rapidly growing distributed ledger technologies (DLTs) have recently received attention among researchers in both industry and academia. While a lot of existing analysis (mainly) of the Bitcoin and Ethereum networks is available, the lack…
Open technologies, decentralized computation and intelligent applications enable the third-generation web, Web 3.0, thereby digitizing whole industries. The emerging Economy of Things (EoT) will be based on software agents running on…
We propose LazyLedger, a design for distributed ledgers where the blockchain is optimised for solely ordering and guaranteeing the availability of transaction data. Responsibility for executing and validating transactions is shifted to only…
Integrating native AI support into the network architecture is an essential objective of 6G. Federated Learning (FL) emerges as a potential paradigm, facilitating decentralized AI model training across a diverse range of devices under the…
Numerous IoT applications, like building automation or process control of industrial sites, exist today. These applications inherently have a strong connection to the physical world. Hence, IT security threats cannot only cause problems…
Blockchain technology is a Distributed Ledger Technology mainly used to store information in an immutable and secure way, but scalability and throughput issues are major challenges. Integration of the NoSQL paradigm within a Blockchain…
In recent years, blockchain technology has been recognized as a transformative innovation in the tech world, and it has quickly become the core infrastructure of digital currencies such as Bitcoin and an important tool in various…
Central Bank Digital Currency (CBDC) can be defined as a virtual currency based on node network and digital encryption algorithm issued by a country which has a legal credit protection. CBDCs are supported by Distributed Ledger Technologies…
Blockchain has come a long way: a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain evolves into another data management system,…
The paths leading to future networks are pointing towards a data-driven paradigm to better cater to the explosive growth of mobile services as well as the increasing heterogeneity of mobile devices, many of which generate and consume large…
In the new space economy, space agencies, large enterprises, and start-ups aim to launch space multi-robot systems (MRS) for various in-situ resource utilization (ISRU) purposes, such as mapping, soil evaluation, and utility provisioning.…
Industrial processes rely on sensory data for decision-making processes, risk assessment, and performance evaluation. Extracting actionable insights from the collected data calls for an infrastructure that can ensure the dissemination of…