Fork-Free Hybrid Consensus with Flexible Proof-of-Activity

Bitcoin and its underlying blockchain mechanism have been attracting much attention. One of their core innovations, Proof-of-Work (PoW), is notoriously inefficient which potentially motivates a centralization of computing power, defeating the original goal of decentralization. Proof-of-Stake (PoS) is later proposed to replace PoW. However, both PoW and PoS have different inherent advantages and disadvantages, so does Proof-of-Activity (PoA) of Bentov et al. (SIGMETRICS 2014) which only offers limited combinations of two mechanisms. On the other hand, the hybrid consensus protocol of Pass and Shi (ePrint 16/917) aims to improve the efficiency by dynamically maintaining a rotating committee. Yet, there are unsatisfactory issues including chain forks and fair committee election. In this paper, we firstly devise a generalized variant of PoW. After that, we leverage our newly proposed generalized PoW to construct a fork-free hybrid consensus protocol, which addresses issues faced by the existing hybrid consensus mechanism. We further combine our fork-free hybrid consensus mechanism with PoS for a flexible version of PoA, which offers a flexible combination of PoW and PoS. Compared with Bentov et al.’s PoA, our “flexible PoA” improves the efficiency and provides more flexible combinations of PoW and PoS, resulting in a more powerful and applicable consensus protocol

Mobile Smart Contracts: Exploring Scalability Challenges and Consensus Mechanisms

Mobile smart contracts (MSCs) are essential to facilitate quick, safe, and decentralized transactions on mobile blockchain networks. Scalable blockchain solutions facilitate the establishment of a mobile blockchain ecosystem characterized by enhanced resilience and adaptability. This encourages an increase in the number of users and, thus, spreads the adoption of blockchain technology in the mobile domain. With the inception of blockchain technology, a wide range of applications use smart contracts due to their high customizability. However, problems with scalability and resource-intensive consensus procedures prevent their general use. Therefore, this work seeks to identify and analyze these constraints by conducting a systematic survey using Kitchenham's guidelines for available scalable blockchains and consensus methods. Out of a preliminary pool of 2,073 publications, our study, which consists of 25 selected studies, identifies 12 consensus mechanisms and 13 scalable blockchain systems. Our investigation shows that, despite the wide range of techniques, no blockchain solution provides the scalability and lightweight operating requirements to implement smart contracts on mobile devices. This realization draws attention to a significant gap in academic and industry-driven blockchain research that may have implications for creating MSCs. Our findings encourage academics to explore scalable and energy-efficient blockchain technology, targeting creating more approachable smart contracts designed with mobile devices in mind.</p

Mobile Smart Contracts: Exploring Scalability Challenges and Consensus Mechanisms

Mobile smart contracts (MSCs) are essential to facilitate quick, safe, and decentralized transactions on mobile blockchain networks. Scalable blockchain solutions facilitate the establishment of a mobile blockchain ecosystem characterized by enhanced resilience and adaptability. This encourages an increase in the number of users and, thus, spreads the adoption of blockchain technology in the mobile domain. With the inception of blockchain technology, a wide range of applications use smart contracts due to their high customizability. However, problems with scalability and resource-intensive consensus procedures prevent their general use. Therefore, this work seeks to identify and analyze these constraints by conducting a systematic survey using Kitchenham's guidelines for available scalable blockchains and consensus methods. Out of a preliminary pool of 2,073 publications, our study, which consists of 25 selected studies, identifies 12 consensus mechanisms and 13 scalable blockchain systems. Our investigation shows that, despite the wide range of techniques, no blockchain solution provides the scalability and lightweight operating requirements to implement smart contracts on mobile devices. This realization draws attention to a significant gap in academic and industry-driven blockchain research that may have implications for creating MSCs. Our findings encourage academics to explore scalable and energy-efficient blockchain technology, targeting creating more approachable smart contracts designed with mobile devices in mind.</p

Overview of Polkadot and its Design Considerations

In this paper we describe the design components of the heterogenous multi-chain protocol Polkadot and explain how these components help Polkadot address some of the existing shortcomings of blockchain technologies. At present, a vast number of blockchain projects have been introduced and employed with various features that are not necessarily designed to work with each other. This makes it difficult for users to utilise a large number of applications on different blockchain projects. Moreover, with the increase in number of projects the security that each one is providing individually becomes weaker. Polkadot aims to provide a scalable and interoperable framework for multiple chains with pooled security that is achieved by the collection of components described in this paper

Identifying and Scoping Context-Specific Use Cases For Blockchain-Enabled Systems in the Wild.

Advances in technology often provide a catalyst for digital innovation. Arising from the global banking crisis at the end of the first decade of the 21st Century, decentralised and distributed systems have seen a surge in growth and interest. Blockchain technology, the foundation of the decentralised virtual currency Bitcoin, is one such catalyst. The main component of a blockchain, is its public record of verified, timestamped transactions maintained in an append-only, chain-like, data structure. This record is replicated across n-nodes in a network of co-operating participants. This distribution offers a public proof of transactions verified in the past. Beyond tokens and virtual currency, real-world use cases for blockchain technology are in need of research and development. The challenge in this proof-of-concept research is to identify an orchestration model of innovation that leads to the successful development of software artefacts that utilise blockchain technology. These artefacts must maximise the potential of the technology and enhance the real-world business application. An original two phase orchestration model is defined. The model includes both a discovery and implementation phase and implements state-of-the-art process innovation frameworks: Capability Maturity Modelling, Business Process Redesign, Open Innovation and Distributed Digital Innovation. The model succeeds in its aim to generate feasible problem-solution design pairings to be implemented as blockchain enabled software systems. Three systems are developed: an internal supply-chain management system, a crowd-source sponsorship model for individual players on a team and a proof-of-origin smart tag system. The contribution is to have defined an innovation model through which context-specific blockchain usecases can be identified and scoped in the wild

Dynamic Data-Driven Digital Twins for Blockchain Systems

In recent years, we have seen an increase in the adoption of blockchain-based systems in non-financial applications, looking to benefit from what the technology has to offer. Although many fields have managed to include blockchain in their core functionalities, the adoption of blockchain, in general, is constrained by the so-called trilemma trade-off between decentralization, scalability, and security. In our previous work, we have shown that using a digital twin for dynamically managing blockchain systems during runtime can be effective in managing the trilemma trade-off. Our Digital Twin leverages DDDAS feedback loop, which is responsible for getting the data from the system to the digital twin, conducting optimisation, and updating the physical system. This paper examines how leveraging DDDAS feedback loop can support the optimisation component of the trilemma benefiting from Reinforcement Learning agents and a simulation component to augment the quality of the learned model while reducing the computational overhead required for decision-making.Comment: 10 Pages, 5 Figures accepted for publication in InfoSymbiotics/Dynamic Data Driven Applications Systems (DDDAS2022