Blockchain is a disruptive technology that focuses on the safe exchange of data between several distributed applications. Despite its widespread adoption, there are areas that require further research towards the understanding of their performance characteristics. In addition, consensus algorithms, a vital part of blockchain, require a more comprehensive understanding of their technical principles and characteristics. Along with the design of different types of consensus algorithms, several challenges, such as system scalability and power consumption, have been raised. Therefore, more comprehensive research is needed to investigate the degree to which consensus algorithms are built and how they perform. To this end, this study extends the body of knowledge and contributes towards the assessment of blockchain protocol performance. We present a comprehensive taxonomy of selected studies on blockchain performance, identifying similarities and differences while attempting to identify existing work on simulators and benchmarking frameworks that aim to explore the performance of blockchain-enabled consensus algorithms.

Flexible and distributed energy markets are a reality that is progressively reaching many regions. Despite their clear benefits, they should be accepted by the prosumers. Additionally, blockchain technology and smart contracts have been characterised as a technological enabler for the energy sector and P2P Energy Markets (PEM). However, little research has been done to explore blockchain's user-centred perspective. Therefore, this paper analyses the reluctance and/or concerns of prosumers regarding smart contracts, and investigates their perception on blockchain within PEMs. The authors present the results of a survey conducted across several European countries addressing the implementation of automated trading systems and analysing the adoption of smart contracts. Considering that the main survey outcomes are related to the regulation and legislation uncertainty around blockchain usage, this paper explores also the fit of smart contracts from a legal perspective. Additionally, a set of recommendations to be used as the basis for the design and development of PEMs is delivered, aiming to adopt blockchain and smart contracts. As a key take-away, the authors confirm the crucial role that blockchain will play in the deployment of fair, secure, flexible and distributed energy markets by ensuring transparency in the exchange of information between prosumers and energy stakeholders.

In the evolving domain of blockchain, a critical challenge lies in the performance analysis of blockchains under controlled test conditions. This paper focuses on validating the Blockchain Benchmarking Framework (BBF), developed for the evaluation of blockchain protocols in a controlled environment. The BBF’s robustness and versatility are demonstrated through its application to the official Docker clients of Ripple’s XRP Ledger (XRPL) and Ethereum, deployed in private, local and controlled environments. These deployments are utilized to simulate network dynamics, transaction throughput, and resilience in a variety of scenarios. Our methodology encompasses tests ranging from standard operational conditions to adverse scenarios, including node failures and simulated double-spend attacks. These controlled environments are essential for evaluating the BBF’s efficacy in stress testing blockchain protocols and assessing their stability and robustness. The BBF’s ability to accurately capture and analyze performance characteristics is highlighted, providing insights into the operational mechanics, scalability, and resilience of these blockchain clients. The findings emphasize the BBF’s adaptability and effectiveness in managing different blockchain protocols, reaffirming its potential for broader application in pre-launch testing and analysis of blockchain performance. This study contributes to the understanding of how blockchain clients can be preliminarily assessed before mainnet deployment as well as to validate all the design decisions made by the protocol under different settings and synthetic scenarios.

Recently, the need for unified orchestration frameworks that can manage extremely heterogeneous, distributed, and resource-constrained environments has emerged due to the rapid development of cloud, edge, and IoT computing. Kubernetes and other traditional cloud-native orchestration systems are not built to facilitate autonomous, decentralized decision-making across the computing continuum or to seamlessly integrate non-container-native devices. This paper presents the Distributed Adaptive Cloud Continuum Architecture (DACCA), a Kubernetes-native architecture that extends orchestration beyond the data center to encompass edge and Internet of Things infrastructures. Decentralized self-awareness and swarm formation are supported for adaptive and resilient operation, a resource and application abstraction layer is established for uniform resource representation, and a Distributed and Adaptive Resource Optimization (DARO) framework based on multi-agent reinforcement learning is integrated for intelligent scheduling in the proposed architecture. Verifiable identity, access control, and tamper-proof data exchange across heterogeneous domains are further ensured by a zero-trust security framework based on distributed ledger technology. When combined, these elements enable increasingly autonomous workload orchestration, trading centralized control for adaptive, decentralized operation with enhanced interoperability, scalability, and trust. Thus, the proposed architecture enables self-managing and context-aware orchestration systems that support next-generation AI-driven distributed applications across the entire computing continuum.