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Recently, the academic community has been giving much attention to Cooperative Learning System, a group learning method combined with pedagogy and social psychology. It allows group members to gain knowledge through collaborations and…
There are different kinds of blockchains, which have been applied in various areas. Blockchains are relatively independent systems that are apt to form isolated data islands. Then cross-chain interaction is proposed to connect different…
Blockchains and peer-to-peer systems are part of a trend towards computer systems that are "radically decentralised", by which we mean that they 1) run across many participants, 2) without central control, and 3) are such that qualities 1…
Edge computing brings computation near end users, enabling the provisioning of novel use cases. To satisfy end-user requirements, the concept of edge federation has recently emerged as a key mechanism for dynamic resources and services…
Blockchain is an innovative distributed ledger technology which has attracted a wide range of interests for building the next generation of applications to address lack-of-trust issues in business. Blockchain as a service (BaaS) is a…
Public permissionless blockchains facilitate peer-to-peer digital transactions, yet face performance challenges specifically minimizing transaction confirmation time to decrease energy and time consumption per transaction. Performance…
Proponents of blockchains believe that this technology will revolutionize e-commerce. To evaluate this belief, we invite several groups of students to transact on a decentralized peer-to-peer marketplace built on the platform provided by…
In general, deep learning models use to make informed decisions immensely. Developed models are mainly based on centralized servers, which face several issues, including transparency, traceability, reliability, security, and privacy. In…
This work proposes a dual-functional blockchain framework named BagChain for bagging-based decentralized learning. BagChain integrates blockchain with distributed machine learning by replacing the computationally costly hash operations in…
We propose a formal approach for specifying and implementing decentralised coordination in distributed systems, with a focus on smart contracts. Our model captures dynamic roles, data-driven transitions, and external coordination…
Cryptocurrencies and their foundation technology, the Blockchain, are reshaping finance and economics, allowing a decentralized approach enabling trusted applications with no trusted counterpart. More recently, the Blockchain and the…
For permissionless blockchains, scalability is paramount. While current technologies still fail to address this problem fully, many research works propose sharding or other techniques that extensively adopt parallel processing of…
This paper proposes a new paradigm: generative blockchain, which aims to transform conventional blockchain technology by combining transaction generation and recording, rather than focusing solely on transaction recording. Central to our…
We develop a model of coordination and allocation of decentralized multi-sided markets, in which our theoretical analysis is promisingly optimizing the decentralized transaction packaging process at high-throughput blockchains or Web 3.0…
Blockchains rely on a consensus among participants to achieve decentralization and security. However, reaching consensus in an online, digital world where identities are not tied to physical users is a challenging problem. Proof-of-work…
There is increased interest in smart vehicles acting as both data consumers and producers in smart cities. Vehicles can use smart city data for decision-making, such as dynamic routing based on traffic conditions. Moreover, the multitude of…
Machine learning algorithms learn from data and use data from databases that are mutable; therefore, the data and the results of machine learning cannot be fully trusted. Also, the machine learning process is often difficult to automate. A…
Machine learning (ML) has been pervasively researched nowadays and it has been applied in many aspects of real life. Nevertheless, issues of model and data still accompany the development of ML. For instance, training of traditional ML…
Biological cells can transmit, process and receive chemically encoded data in the same way as network devices transmit, process, and receive digitally encoded data. Communication protocols have led to the rapid development of computer…
Large models have achieved remarkable performance across a range of reasoning and understanding tasks. Prior work often utilizes model ensembles or multi-agent systems to collaboratively generate responses, effectively operating in a…