For the successful development of the astrophysics and, accordingly, for obtaining more complete knowledge of the Universe, it is extremely important to combine and comprehensively analyze information of various types (e.g., about charged cosmic particles, gamma rays, neutrinos, etc.) obtained by using divers large-scale experimental setups located throughout the world. It is obvious that all kinds of activities must be performed continually across all stages of the data life cycle to help support effective data management, in particular, the collection and storage of data, its processing and analysis, refining the physical model, making preparations for publication, and data reprocessing taking refinement into account. In this paper we present a general approach to construction and the architecture of a system to be able to collect, store, and provide users' access to astrophysical data. We also suggest a new approach to the construction of a metadata registry based on the blockchain technology.
We relate the concepts used in decentralized ledger technology to studies of episodic memory in the mammalian brain. Specifically, we introduce the standard concepts of linked list, hash functions, and sharding, from computer science. We argue that these concepts may be more relevant to studies of the neural mechanisms of memory than has been previously appreciated. In turn, we also highlight that certain phenomena studied in the brain, namely metacognition, reality monitoring, and how perceptual conscious experiences come about, may inspire development in blockchain technology too, specifically regarding probabilistic consensus protocols.
Blockchain systems benefit from lessons in prior art such as fault tolerance, distributed systems, peer-to-peer systems, and game theory. In this paper we argue that blockchain algorithms should tolerate both rational (self-interested) users and Byzantine (malicious) ones, rather than assuming all non-Byzantine users are altruistic and follow the protocols blindly. Such algorithms are called BAR-tolerant [1]. To design a BAR-tolerant system, one can follow these three steps: clearly define the utility function for the rational users, prove the algorithm is such that there is no benefit from unilaterally deviating (that is, it's a Byzantine Nash Equilibrium), then prove the algorithm correct assuming the rational actors follow the protocol. We present an example attack by rational users: the gatekeeping attack, where members of a system selfishly decide to prevent newcomers from joining. This attack may affect any stake-based system where the existing members prevent newcomers from making a stake, and essentially form a cartel. We then sketch a BAR-tolerant consensus protocol for blockchain that can defend against this attack. It relies on a strict order to decide who gets to propose a new block (so there's no need to race to solve a crypto puzzle) and it relies on hardware ID tokens to make sure every computer is only represented at most once as a block proposer to mitigate Sybil attacks. It also defends against the gatekeeper attack. The BAR-tolerant approach is naturally also applicable to other blockchain algorithms.
The paper suggests a new approach based on blockchain technologies and smart contracts to creation of a distributed system for managing provenance metadata, as well as access rights to data in distributed storages, which is fault-tolerant, safe and secure from the point of view of preservation of metadata records from accidental or intentional distortions. The implementation of the proposed approach is based on the permissioned blockchains and on the Hyperledger Fabric blockchain platform in conjunction with Hyperledger Composer.
Nov 1, 2018·B. Varghese et al., "Realizing Edge Marketplaces: Challenges and Opportunities," in IEEE Cloud Computing, vol. 5, no. 6, pp. 9-20, Nov./Dec. 2018
Blesson Varghese, Massimo Villari, Omer Rana, Philip James · 7 authors
The edge of the network has the potential to host services for supporting a variety of user applications, ranging in complexity from data preprocessing, image and video rendering, and interactive gaming, to embedded systems in autonomous cars and built environments. However, the computational and data resources over which such services are hosted, and the actors that interact with these services, have an intermittent availability and access profile, introducing significant risk for user applications that must rely on them. This article investigates the development of an edge marketplace, which is able to support multiple providers for offering services at the network edge, and to enable demand supply for influencing the operation of such a marketplace. Resilience, cost, and quality of service and experience will subsequently enable such a marketplace to adapt its services over time. This article also describes how distributed-ledger technologies (such as blockchains) provide a promising approach to support the operation of such a marketplace and regulate its behavior (such as the GDPR in Europe) and operation. Two application scenarios provide context for the discussion of how such a marketplace would function and be utilized in practice.
Ankur Sharma, Felix Schuhknecht, Divya Agrawal, Jens Dittrich
Within the last few years, a countless number of blockchain systems have emerged on the market, each one claiming to revolutionize the way of distributed transaction processing in one way or the other. Many blockchain features, such as byzantine fault tolerance (BFT), are indeed valuable additions in modern environments. However, despite all the hype around the technology, many of the challenges that blockchain systems have to face are fundamental transaction management problems. These are largely shared with traditional database systems, which have been around for decades already. These similarities become especially visible for systems, that blur the lines between blockchain systems and classical database systems. A great example of this is Hyperledger Fabric, an open-source permissioned blockchain system under development by IBM. By having a relaxed view on BFT, the transaction pipeline of Fabric highly resembles the workflow of classical distributed databases systems. This raises two questions: (1) Which conceptual similarities and differences do actually exist between a system such as Fabric and a classical distributed database system? (2) Is it possible to improve on the performance of Fabric by transitioning technology from the database world to blockchains and thus blurring the lines between these two types of systems even further? To tackle these questions, we first explore Fabric from the perspective of database research, where we observe weaknesses in the transaction pipeline. We then solve these issues by transitioning well-understood database concepts to Fabric, namely transaction reordering as well as early transaction abort. Our experimental evaluation shows that our improved version Fabric++ significantly increases the throughput of successful transactions over the vanilla version by up to a factor of 3x.
Mark C. Ballandies, Marcus M. Dapp, Evangelos Pournaras
More than 1000 distributed ledger technology (DLT) systems raising $600 billion in investment in 2016 feature the unprecedented and disruptive potential of blockchain technology. A systematic and data-driven analysis, comparison and rigorous evaluation of the different design choices of distributed ledgers and their implications is a challenge. The rapidly evolving nature of the blockchain landscape hinders reaching a common understanding of the techno-socio-economic design space of distributed ledgers and the cryptoeconomies they support. To fill this gap, this paper makes the following contributions: (i) A conceptual architecture of DLT systems with which (ii) a taxonomy is designed and (iii) a rigorous classification of DLT systems is made using real-world data and wisdom of the crowd. (iv) A DLT design guideline is the end result of applying machine learning methodologies on the classification data. Compared to related work and as defined in earlier taxonomy theory, the proposed taxonomy is highly comprehensive, robust, explanatory and extensible. The findings of this paper can provide new insights and better understanding of the key design choices evolving the modeling complexity of DLT systems, while identifying opportunities for new research contributions and business innovation. Supplementary Information: The online version contains supplementary material available at 10.1007/s10586-021-03256-w.
Blockchains is a special type of distributed systems that operates in unsafe networks. In most blockchains, all nodes should reach consensus on all state transitions with Byzantine fault tolerant algorithms, which creates bottlenecks in performance. In this paper, we propose a new type of blockchains, namely Value-Centric Blockchains (VCBs), in which the states are specified as values (or more comprehensively, coins) with owners and the state transition records are then specified as proofs of the ownerships of individual values. We then formalize the "rational" assumptions that have been used in most blockchains. We further propose a VCB, VAPOR, that guarantees secure value transfers if all nodes are rational and keep the proofs of the values they owned, which is merely parts of the whole state transition record. As a result, we show that VAPOR enjoys significant benefits in throughput, decentralization, and flexibility without compromising security.
Since the inception of blockchain and Bitcoin (Nakamoto (2008)), a decentralized-distributed ledger system and its associated cryptocurrency, respectively, the world has witnessed a slew of newer adaptations and applications. Although the original distributed ledger technology (DLT) of blockchain is deemed secure and decentralized, the confirmation of transactions is inefficient by design. Recently adopted, directed acyclic graph (DAG)-based distributed ledgers validate transactions efficiently without the physically and environmentally costly building process of blocks (Lerner (2015)). However, centrally-controlled confirmation against the odds of multiple validation disqualifies the DAG as a decentralized-distributed ledger. In this regard, we introduce an innovative DLT by reconstructing a chain of antichains based on a given DAG-pool of transactions. Each antichain (box) contains distinct nodes whose approved transactions are recursively validated by subsequently augmenting nodes. The boxer node closes the box and keeps the hash of all transactions confirmed by the box-genesis node. Designation of boxers and box-geneses is conditionally randomized for decentralization. The boxes are serially concatenated with recursive confirmation (boxchain) without incurring the cost of box generation. Rewards (boxcoin) are paid to the contributing nodes of the ecosystem whose trust is built on the doubly-secure protocol of confirmation. A value-preserving medium of payment (boxdollar) is among numerous practical applications discussed herein.
Blockchain has the potential to revolutionize the way we store, use, and process data. Information on most blockchains can be viewed by every node hosting the blockchain, which means that most blockchains cannot handle private data. Decentralized databases exist that guarantee privacy by encrypting user data with the user's private key, but this prevents easy data sharing. However, in many real world applications, from student data to medical records, it is desirable that user data is anonymously searchable. In this paper we present a novel system that gives users ownership over their data while at the same time enabling them to make their data searchable within previously agreed upon limits. Our system implements a strong notion of ownership using a self-sovereign identity system and a weak notion of ownership using multiple centralized databases together with a blockchain and a tumbling process. We discuss applications of our methods to university's student records and medical data.
Nelson Kibichii Bore, Ravi Kiran Raman, Isaac M. Markus, Sekou L. Remy · 11 authors
Policy decisions are increasingly dependent on the outcomes of simulations and/or machine learning models. The ability to share and interact with these outcomes is relevant across multiple fields and is especially critical in the disease modeling community where models are often only accessible and workable to the researchers that generate them. This work presents a blockchain-enabled system that establishes a decentralized trust between parties involved in a modeling process. Utilizing the OpenMalaria framework, we demonstrate the ability to store, share and maintain auditable logs and records of each step in the simulation process, showing how to validate results generated by computing workers. We also show how the system monitors worker outputs to rank and identify faulty workers via comparison to nearest neighbors or historical reward spaces as a means of ensuring model quality.
Emilija Stojmenova Duh, Andrej Duh, Uroš Droftina, Tim Kos · 7 authors
Scholarly communication is today immersed in publish or perish culture that propels noncooperative behaviour in the sense of strategic games played by researchers. Here we introduce and describe a blockchain based platform for decentralized scholarly communication. The design of the platform rests on community driven publishing reviewing processes and implements incentives that promote cooperative user behaviour. Key to achieve cooperation in blockchain based scholarly communication is to transform a static research paper into a modifiable research paper under continuous peer review process. We describe and discuss the implementation of a modifiable research paper as a smart contract on the blockchain.
Bitcoin's enormous success has inspired the development of alternative blockchains, such as consortium chains. Several cross-chain protocols have been proposed as ways of connecting these universes of individual blockchains in a distributed and secure manner. In this paper, we present Niji, a new cross-chain protocol that allows parties to perform virtual Bitcoin payment securely on a consortium chain, without any trusted third-party or mediators. Our work focuses on the issue that it is difficult for a consortium chain's token to hold a stable market value, and Niji makes it possible for smart contract services to acquire means of payment in the consortium chain. With the Bitcoin payment channel built on the consortium chain, the process from payment to service provision runs autonomously without any interaction between parties. Niji introduces the concept of a transaction template to validate Bitcoin payments efficiently on different blockchains, and it allows a service provider to delegate all of its tasks for verifying state updates to a smart contract on the consortium chain. We also propose a novel bi-directional payment channel adapted for design of the Niji protocol, which can update payments non-interactively between parties. We implemented a prototype of the Niji protocol and conducted an experiment measuring the computational cost and latency that demonstrates the protocol's feasibility on practical platforms.
S. Keshav, W. Golab, B. Wong, S. Rizvi · 5 authors
Distributed consensus is a key enabler for many distributed systems including distributed databases and blockchains. Canopus is a scalable distributed consensus protocol that ensures that live nodes in a system agree on an ordered sequence of operations (called transactions). Unlike most prior consensus protocols, Canopus does not rely on a single leader. Instead, it uses a virtual tree overlay for message dissemination to limit network traffic across oversubscribed links. It leverages hardware redundancies, both within a rack and inside the network fabric, to reduce both protocol complexity and communication overhead. These design decisions enable Canopus to support large deployments without significant performance degradation. The existing Canopus protocol is resilient in the face of node and communication failures, but its focus is primarily on performance, so does not respond well to other types of failures. For example, the failure of a single rack of servers causes all live nodes to stall. The protocol is also open to attack by Byzantine nodes, which can cause different live nodes to conclude the protocol with different transaction orders. In this paper, we describe RCanopus (`resilent Canopus') which extends Canopus to add liveness, that is, allowing live nodes to make progress, when possible, despite many types of failures. This requires RCanopus to accurately detect and recover from failure despite using unreliable failure detectors, and tolerance of Byzantine attacks. Second, RCanopus guarantees safety, that is, agreement amongst live nodes of transaction order, in the presence of Byzantine attacks and network partitioning.
Sang‐Min Choi, Jiho Park, Quan Nguyen, André Cronje
We describe \emph{Fantom}, a framework for asynchronous distributed systems. \emph{Fantom} is based on the Lachesis Protocol~\cite{lachesis01}, which uses asynchronous event transmission for practical Byzantine fault tolerance (pBFT) to create a leaderless, scalable, asynchronous Directed Acyclic Graph (DAG). We further optimize the \emph{Lachesis Protocol} by introducing a permission-less network for dynamic participation. Root selection cost is further optimized by the introduction of an n-row flag table, as well as optimizing path selection by introducing domination relationships. We propose an alternative framework for distributed ledgers, based on asynchronous partially ordered sets with logical time ordering instead of blockchains. This paper builds upon the original proposed family of \emph{Lachesis-class} consensus protocols. We formalize our proofs into a model that can be applied to abstract asynchronous distributed system.
Transaction throughput, confirmation latency and confirmation reliability are fundamental performance measures of any blockchain system in addition to its security. In a decentralized setting, these measures are limited by two underlying physical network attributes: communication capacity and speed-of-light propagation delay. Existing systems operate far away from these physical limits. In this work we introduce Prism, a new proof-of-work blockchain protocol, which can achieve 1) security against up to 50% adversarial hashing power; 2) optimal throughput up to the capacity C of the network; 3) confirmation latency for honest transactions proportional to the propagation delay D, with confirmation error probability exponentially small in CD ; 4) eventual total ordering of all transactions. Our approach to the design of this protocol is based on deconstructing the blockchain into its basic functionalities and systematically scaling up these functionalities to approach their physical limits.
Dr. Julian Hosp, Toby Hoenisch, Paul Kittiwongsunthorn
Since the creation of Bitcoin in 2009 we have seen a great push towards public and private blockchains. In order to avoid fragmentation, a global network connecting all these blockchains is envisioned. Just like the Internet facilitates communication and the transfer of information, we propose a system, similar in size and reach for payments and transactions: A cryptographically-secure off-chain multi-asset instant transaction network (COMIT) can connect and exchange any asset on any blockchain to any other blockchain using a cross-chain routing protocol (CRP). COMIT is a super blockchain network that allows for instant transactions which are enforced using off-chain smart contracts. It leverages Payment Channels and Hashed Timelock Contracts (HTLC) across chains to solve the problem of double spending attacks without requiring a settlement onto the underlying blockchains. COMIT's connectivity is provided by Liquidity Providers (LP), who operate on one or more blockchains, acting as payment hubs and nodes on a single chain and market makers in a decentralized network for cross-chain asset conversions. This paper lays out how COMIT works, the benefits for Users, Liquidity Providers and Businesses; and how this does not only accelerate the adoption of blockchain technology, but furthermore allows for an integration with the traditional banking system.
Ahmed S. Almasoud, Maged M. Eljazzar, Farookh Hussain
In recent years, Blockchain technology has been highly valued and disruptive. Several researches have presented a merge between blockchain and current application i.e. medical, supply chain, and e-commerce. Although Blockchain architecture does not have a standard yet, IBM, MS, AWS offer BaaS (Blockchain as a Service). In addition to the current public chains i.e. Ethereum, NEO, and Cardeno; there are some differences between several public ledgers in terms of development and architecture. This paper introduces the main factors that affect integration of Artificial Intelligence with Blockchain. As well as, how it could be integrated for forecasting and automating; building self-regulated chain.
Blockchain has emerged as a trusted and secure distributed ledger for transactions while also being decentralised, distributed and its legitimacy not guaranteed by a trusted authority. Since the appearance of Bitcoin, Blockchain has known many implementations based on P2P architectures. This paper presents how the blockchain and smart contracts technologies can be integrated into the SwarmESB ecosystem. SwarmESB is a framework that helps building distributed applications, which benefit from privacy and scalability features. Our proposal will present the flexibility in building not only microservices based applications, but also decen-tralised applications employing blockchain and smart-contracts by modeling a sample Dapp.
Today's blockchain designs suffer from a trilemma claiming that no blockchain system can simultaneously achieve decentralization, security, and performance scalability. For current blockchain systems, as more nodes join the network, the efficiency of the system (computation, communication, and storage) stays constant at best. A leading idea for enabling blockchains to scale efficiency is the notion of sharding: different subsets of nodes handle different portions of the blockchain, thereby reducing the load for each individual node. However, existing sharding proposals achieve efficiency scaling by compromising on trust - corrupting the nodes in a given shard will lead to the permanent loss of the corresponding portion of data. In this paper, we settle the trilemma by demonstrating a new protocol for coded storage and computation in blockchains. In particular, we propose PolyShard: ``polynomially coded sharding'' scheme that achieves information-theoretic upper bounds on the efficiency of the storage, system throughput, as well as on trust, thus enabling a truly scalable system. We provide simulation results that numerically demonstrate the performance improvement over state of the arts, and the scalability of the PolyShard system. Finally, we discuss potential enhancements, and highlight practical considerations in building such a system.
Yackolley Amoussou-Guenou, Antonella del Pozzo, Maria Potop-Butucaru, Sara Tucci-Piergiovanni
In this paper we analyze Tendermint proposed in [7], one of the most popular blockchains based on PBFT Consensus. The current paper dissects Tendermint under various system communication models and Byzantine adversaries. Our methodology consists in identifying the algorithmic principles of Tendermint necessary for a specific combination of communication model-adversary. This methodology allowed to identify bugs [3] in preliminary versions of the protocol ([19], [7]) and to prove its correctness under the most adversarial conditions: an eventually synchronous communication model and asymmetric Byzantine faults.
Ravi Kiran Raman, Roman Vaculín, Michael Hind, Sekou L. Remy · 9 authors
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, and healthcare to understand phenomena, and design high-stakes policies affecting everyday health and economy. For instance, the OpenMalaria framework is a computationally-intensive simulation used by various non-governmental and governmental agencies to understand malarial disease spread and effectiveness of intervention strategies, and subsequently design healthcare policies. Given that such shared results form the basis of inferences drawn, technological solutions designed, and day-to-day policies drafted, it is essential that the computations are validated and trusted. In particular, in a multi-agent environment involving several independent computing agents, a notion of trust in results generated by peers is critical in facilitating transparency, accountability, and collaboration. Using a novel combination of distributed validation of atomic computation blocks and a blockchain-based immutable audits mechanism, this work proposes a universal framework for distributed trust in computations. In particular we address the scalaibility problem by reducing the storage and communication costs using a lossy compression scheme. This framework guarantees not only verifiability of final results, but also the validity of local computations, and its cost-benefit tradeoffs are studied using a synthetic example of training a neural network.
We study the probabilistic distribution of the confirmation time of Bitcoin transactions, conditional on the current memory pool (i.e., the queue of transactions awaiting confirmation). The results of this paper are particularly interesting for users that want to make a Bitcoin transaction during `heavy-traffic situations', when the transaction demand exceeds the block capacity. In such situations, Bitcoin users tend to bid up the transaction fees, in order to gain priority over other users that pay a lower fee. We argue that the time until a Bitcoin transaction is confirmed can be modelled as a particular stochastic fluid queueing process (to be precise: a Cramér-Lundberg process). We approximate the queueing process in two different ways. The first approach leads to a lower bound on the confirmation probability, which becomes increasingly tight as traffic decreases. The second approach relies on a diffusion approximation with a continuity correction, which becomes increasingly accurate as traffic intensifies. The accuracy of the approximations under different traffic loads are evaluated in a simulation study.
We study a stochastic game framework with dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving the problem or for providing their computational resources, while incur a certain cost based on the invested time and computational power. We first study a scenario where the reward is offered for solving the problem, such as in blockchain mining. We show that, in Markov perfect equilibrium, players with cost parameters exceeding a certain threshold, do not invest; while those with cost parameters less than this threshold, invest maximal power. Here, players need not know the system state. We then consider a scenario where the reward is offered for contributing to the computational power of a common central entity, such as in volunteer computing. Here, in Markov perfect equilibrium, only players with cost parameters in a relatively low range in a given state, invest. For the case where players are homogeneous, they invest proportionally to the 'reward to cost' ratio. For both the scenarios, we study the effects of players' arrival and departure rates on their utilities using simulations and provide additional insights.