A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

© 2013 IEEE. The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions

LQMPCS: Design of a Low-Complexity Q-Learning Model based on Proof-of-Context Consensus for Scalable Side Chains

Single-chained blockchains are being rapidly replaced by sidechains (or sharded chains), due to their high QoS (Quality of Service), and low complexity characteristics. Existing sidechaining models use context-specific machine-learning optimization techniques, which limits their scalability when applied to real-time use cases. Moreover, these models are also highly complex and require constant reconfigurations when applied to dynamic deployment scenarios. To overcome these issues, this text proposes design of a novel low-complexity Q-Learning Model based on Proof-of-Context (PoC) consensus for scalable sidechains. The proposed model initially describes a Q-Learning method for sidechain formation, which assists in maintaining high scalability even under large-scale traffic scenarios. This model is cascaded with a novel Proof-of-Context based consensus that is capable of representing input data into context-independent formats. These formats assist in providing high-speed consensus, which is uses intent of data, instead of the data samples. To estimate this intent, a set of context-based classification models are used, which assist in representing input data samples into distinctive categories. These models include feature representation via Long-Short-Term-Memory (LSTM), and classification via 1D Convolutional Neural Networks (CNNs), that can be used for heterogeneous application scenarios. Due to representation of input data samples into context-based categories, the proposed model is able to reduce mining delay by 8.3%, reduce energy needed for mining by 2.9%, while maintaining higher throughput, and lower mining jitters when compared with standard sidechaining techniques under similar use cases

Reconciliation of anti-money laundering instruments and European data protection requirements in permissionless blockchain spaces

Artykuł ten zmierza do pogodzenia wymagań unijnego rozporządzenia o ochronie danych osobowych (RODO) i instrumentów przeciwdziałania praniu brudnych pieniędzy i finansowania terroryzmu (AML/CFT) wykorzystywanych w dostępnych publicznie ekosystemach permissionless bazujących na technologi rozproszonych rejestrów (DLT). Dotychczasowe analizy skupiają się zazwyczaj jedynie na jednej z tych regulacji. Natomiast poddanie analizie ich wzajemnych oddziaływań ujawnia brak ich koherencji w sieciach permissionless DLT. RODO zmusza członków społeczności blockchain do wykorzystywania technologii anonimizujących dane albo przynajmniej zapewniających silną pseudonimizację, aby zapewnić zgodność przetwarzania danych z wymogami RODO. Jednocześnie instrumenty globalnej polityki AML/CFT, które są obecnie implementowane w wielu państwach stosowanie do wymogów ustanawianych przez Financial Action Task Force (FATF), przeciwdziałają wykorzystywaniu technologii anonimizacyjnych wbudowanych w protokoły sieci blockchain. Rozwiązania proponowane w tym artykule mają na celu spowodowanie kształtowania sieci blockchain w taki sposób, aby jednocześnie zabezpieczały one dane osobowe użytkowników zgodnie z wysokimi wymogami RODO, jednocześnie adresując ryzyka AML/CFT kreowane przez transakcje w takiej anonimowej lub silnie pseudonimowej przestrzeni. Poszukiwanie nowych instrumentów polityki państw jest konieczne aby zapewnić że państwa nie będą zwalczać rozwoju wszystkich anonimowych sieci blockchian, gdyż jest to konieczne do zapewnienia ich zdolność do realizacji wysokich wymogów RODO w zakresie ochrony danych przetwarzanych na blockchain. Ten artykuł wskazuje narzędzia AML/CFT, które mogą być pomocne do tworzenia blockchainów wspierających prywatność przy jednoczesnym zapewnieniu wykonalności tych narzędzi AML/CFT. Pierwszym z tych narzędzi jest wyjątkowy dostęp państwa do danych transakcyjnych zapisanych na zasadniczo nie-trantsparentnym rejestrze, chronionych technologiami anonimizacyjnymi. Takie narzędzie powinno być jedynie opcjonalne dla danej sieci (finansowej platformy), jak długo inne narzędzia AML/CFT są wykonalne i są zapewniane przez sieć. Jeżeli żadne takie narzędzie nie jest dostępne, a dana sieć nie zapewni wyjątkowego dostępu państwu (państwom), wówczas regulacje powinny pozwalać danemu państwu na zwalczanie danej sieci (platformy finansowej) jako całości. Efektywne narzędzia w tym zakresie powinny obejmować uderzenie przez państwo (państwa) w wartość natywnej kryptowaluty, a nie ściganie indywidualnych jej użytkowników. Takie narzędzia mogą obejmować atak (cyberatak) państwa lub państw który podważy zaufanie użytkowników do danej sieci.This article is an attempt to reconcile the requirements of the EU General Data Protection Regulation (GDPR) and anti-money laundering and combat terrorist financing (AML/CFT) instruments used in permissionless ecosystems based on distributed ledger technology (DLT). Usually, analysis is focused only on one of these regulations. Covering by this research the interplay between both regulations reveals their incoherencies in relation to permissionless DLT. The GDPR requirements force permissionless blockchain communities to use anonymization or, at the very least, strong pseudonymization technologies to ensure compliance of data processing with the GDPR. At the same time, instruments of global AML/CFT policy that are presently being implemented in many countries following the recommendations of the Financial Action Task Force, counteract the anonymity-enhanced technologies built into blockchain protocols. Solutions suggested in this article aim to induce the shaping of permissionless DLT-based networks in ways that at the same time would secure the protection of personal data according to the GDPR rules, while also addressing the money laundering and terrorist financing risks created by transactions in anonymous blockchain spaces or those with strong pseudonyms. Searching for new policy instruments is necessary to ensure that governments do not combat the development of all privacy-blockchains so as to enable a high level of privacy protection and GDPR-compliant data processing. This article indicates two AML/CFT tools which may be helpful for shaping privacy-blockchains that can enable the feasibility of such tools. The first tool is exceptional government access to transactional data written on non-transparent ledgers, obfuscated by advanced anonymization cryptography. The tool should be optional for networks as long as another effective AML/CFT measures are accessible for the intermediaries or for the government in relation to a given network. If these other measures are not available and the network does not grant exceptional access, the regulations should allow governments to combat the development of those networks. Effective tools in that scope should target the value of privacy-cryptocurrency, not its users. Such tools could include, as a tool of last resort, state attacks which would undermine the trust of the community in a specific network

Collaborative autonomy in heterogeneous multi-robot systems

As autonomous mobile robots become increasingly connected and widely deployed in different domains, managing multiple robots and their interaction is key to the future of ubiquitous autonomous systems. Indeed, robots are not individual entities anymore. Instead, many robots today are deployed as part of larger fleets or in teams. The benefits of multirobot collaboration, specially in heterogeneous groups, are multiple. Significantly higher degrees of situational awareness and understanding of their environment can be achieved when robots with different operational capabilities are deployed together. Examples of this include the Perseverance rover and the Ingenuity helicopter that NASA has deployed in Mars, or the highly heterogeneous robot teams that explored caves and other complex environments during the last DARPA Sub-T competition. This thesis delves into the wide topic of collaborative autonomy in multi-robot systems, encompassing some of the key elements required for achieving robust collaboration: solving collaborative decision-making problems; securing their operation, management and interaction; providing means for autonomous coordination in space and accurate global or relative state estimation; and achieving collaborative situational awareness through distributed perception and cooperative planning. The thesis covers novel formation control algorithms, and new ways to achieve accurate absolute or relative localization within multi-robot systems. It also explores the potential of distributed ledger technologies as an underlying framework to achieve collaborative decision-making in distributed robotic systems. Throughout the thesis, I introduce novel approaches to utilizing cryptographic elements and blockchain technology for securing the operation of autonomous robots, showing that sensor data and mission instructions can be validated in an end-to-end manner. I then shift the focus to localization and coordination, studying ultra-wideband (UWB) radios and their potential. I show how UWB-based ranging and localization can enable aerial robots to operate in GNSS-denied environments, with a study of the constraints and limitations. I also study the potential of UWB-based relative localization between aerial and ground robots for more accurate positioning in areas where GNSS signals degrade. In terms of coordination, I introduce two new algorithms for formation control that require zero to minimal communication, if enough degree of awareness of neighbor robots is available. These algorithms are validated in simulation and real-world experiments. The thesis concludes with the integration of a new approach to cooperative path planning algorithms and UWB-based relative localization for dense scene reconstruction using lidar and vision sensors in ground and aerial robots

Scanning the European Ecosystem of Distributed Ledger Technologies for Social and Public Good: What, Why, Where, How, and Ways to Move Forward

Distributed Ledger Technologies (DLTs), such as blockchains, are primarily tamper-resistant and time-stamped databases. They allow multiple parties to record, verify and share data on a peer-to-peer basis across a network, in decentralised, synchronised and transparent ways, with limited human intervention and reduced intermediate steps. These technologies are mostly known for business use cases, from cryptocurrencies to asset track and tracing. But there are numerous organisations nowadays searching for alternative ways to harness the potential of DLTs in the pursuit of public and social good, from local to global challenges, and towards more inclusive, cooperative, sustainable, ethical or accountable digital and physical worlds. This Science for Policy report explores the current status of this particular field both theoretically and empirically, in the framework of the project #DLT4Good: Co-creating a European Ecosystem of DLTs for Social and Public Good. Part One offers a conceptual overview of the connections between main features of DLTs and their potential for social and public good goals. Emphasis is placed on different approaches to decentralisation, and on core building blocks of DLTs linked with values such as trust, privacy, self-sovereignty, autonomy, inclusiveness, transparency, openness, or the commons. Part Two comprises a scanning of the current European ecosystem of DLT projects with activities in this field. It contains a summarized version of a database published online with 131 projects, and a quantitative review of main trends. It also includes a qualitative assessment of 10 projects selected from the larger sample to showcase this field and its diversity. Part Three concludes with six independent position papers and recommendations from experts and advisors of the #DLT4Good project. The main topics addressed range from decentralized governance to collaborative economies, with highlights on issues such as trust, verifiability, transparency, privacy or bottom-up coordination