Bitcoin’s success as a global cryptocurrency has paved the way for the emergence of blockchain, a revolutionary category of distributed systems. However, the growing popularity of blockchain has led to a significant divergence from its core principles in many systems labeled as “blockchain.” This divergence has introduced complexity into the blockchain ecosystem, exacerbated by a lack of comprehensive reviews on blockchain and its variants. Consequently, gaining a clear and updated understanding of the diverse spectrum of current blockchain and blockchain-like systems has become challenging. This situation underscores the necessity for an extensive literature review and the development of thematic taxonomies. This survey seeks to offer a comprehensive and current assessment of existing blockchains and their variations while delineating the boundaries between blockchain and blockchain-like systems. To achieve this objective, we propose a holistic reference model for conceptualizing and analyzing these systems. Our layer-wise framework envisions all distributed ledger technologies (DLTs) as composed of four principal layers: data, consensus, execution, and application (DCEA). In addition, we introduce a new taxonomy that enhances the classification of blockchain and blockchain-like systems, offering a more useful perspective than existing works. Furthermore, we conduct a state-of-the-art review from a layered perspective, employing 23 evaluative criteria predefined by our framework. We perform a qualitative and quantitative comparative analysis of 44 DLT solutions and 26 consensus mechanisms while discussing differences and boundaries between blockchain and blockchain-like systems. We emphasize the significant challenges and tradeoffs encountered by distributed ledger designers, decision-makers, and project managers during the design or adoption of a DLT solution. Finally, we outline crucial research challenges and directions in the field of DLTs.

Trust is an important factor in the success of P2P networks. It is needed to ensure that nodes in the network can be trusted to behave honestly and to deliver on their promises (e.g sharing resources). While traditional reputation trust management systems (RTMS) such as BTrust or EigenTrust have proven effective, there is room for further enhancement by integrating advanced graph neural network (GNN) models. This paper proposes a novel approach to enhance Trust Management Systems (TMS) by incorporating an Edge-Feature Attention Mechanism into the Edge Graph Neural Network (EGNN) model, which takes into account the direction of edges. The proposed GBTrust model is specifically designed for trust management in P2P networks, leveraging the interactions and relationships among peers. By incorporating the Edge-Feature Attention Mechanism, the model dynamically assigns importance to different edge features based on their relevance, thereby improving the discrimination of the importance of various neighbors and edge features in the network graph. The GBtrust model aims to provide more accurate and adaptive detection of malicious peers, thereby enhancing the overall security and reliability of P2P networks.

In recent years, Blockchain arose as a key technology in building autonomous decentralised financial systems. Its ability to digitize trust enables building trustless systems such as cryptocurrencies where users do not need to rely on any third party to exchange value. The success of cryptocurrencies to operate without any intermediaries draw the interest of business operators who seek to bypass intermediation and thus to reduce cost and gain competitive advantages. As a result, Blockchain was used outside the crypto-sphere to build decentralized systems. However, this portage led to the inception of new types of Blockchains adapted to different specifications and with different designs. Consequently, the technology has diverged from its baseline (Bitcoin) to the point where some systems marketed as “blockchain” share only a few design concepts with the original Blockchain design proposed by Satoshi Nakamoto. This conceptual divergence alongside the lack of comprehensive models and standards made it difficult for both system designers and decision-makers to clearly understand what is a blockchain or to choose a suitable solution.This survey has a double goal; on the one hand, it attempts to contribute to the discussion on the ontological status of DLTs by providing a taxonomy oriented-framework (DCEA) for conceptualizing and examining DLT. On the other hand, it also attempts to present an up-to-date review and evaluation of current blockchains and their variants as constructed of four layers: the data, consensus, execution and application layers.

With the appearance of virtualization, the spread of internet, the development of broadband networks, and also the advent of externalization and application rental; cloud computing (CC) has emerged as being the next generation of distributed computing paradigm. Based on “pay-for-what-you-use” model, CC offers significant benefits including costs reduction, on demand provisioning, rapid elasticity, resources pooling, etc. But despite all its potential gains, the model also introduces many challenges from which the major concern that hampers its adoption is the lack of an integrated approach for CC governance. With regard to this matter, the main contributions of this paper is first, to analyze the existing standards and research works considering different aspects of IT governance; and second, to identify, analyze, and organize the main CC governance requirements that constitute the cornerstone for the development of an integrated approach for CC governance.