Decentralised Autonomous Organisations (DAOs) have the capability of being a disruptive Web3 technology. Their usage of cryptographically secure distributed ledgers shows promise of replacing existing technical and financial intermediaries. However, this promise has not been fully materialised yet: existing attempts typically rely on centralisation as the required decentralised components do not exist or are not mature enough. We present our Web3 Deployment Experiment around a robust decentralised economy to address these issues. Our economy is unique due to the removal of all centralised components and governance. It is resilient against legal and economic attacks as no individual or organisation can compromise its functioning. We dub this characteristic extreme decentralisation. Similar to BitTorrent and Bitcoin, our extreme decentralisation DAOs carefully avoid single points of failure and are effectively unstoppable. Within our experiment around a music economy, we bypass all intermediaries in finance, technology, and the music industry itself with a direct donation to musicians. We demonstrate the viability of collective decision-making within our decentralised economy and present a set of principles for Web3 DAOs. Our implementation shows that the DAO ecosystem is fully deployable on smartphones, allowing anyone to create a DAO without reliance on central authorities or components.
Waterfall is a highly-scalable smart contract platform for the development of decentralized applications (dapps) and financial services. The distributed protocol is based on Directed Acyclic Graphs (DAGs) with fast finality Proof-of-Stake (PoS) consensus. The Waterfall platform consists of the Coordinating and Shard networks achieving high transaction throughput due to parallelized block production. The DAG structure facilitates scalability, which is one of the main challenges of decentralized technologies. The Coordinating network maintains a register of Validators, and also assigns block producers, committee members, and leaders in each time slot. In addition, the linearization and finalization of the distributed ledger are performed in the Coordinating network increasing overall security and synchronization.
Peer-to-peer (P2P) content delivery is up-and-coming to provide benefits comprising cost-saving and scalable peak-demand handling compared with centralized content delivery networks (CDNs), and also complementary to the popular decentralized storage networks such as Filecoin. However, reliable P2P delivery demands proper enforcement of delivery fairness, i.e., the deliverers should be rewarded in line with their in-time delivery. Unfortunately, most existing studies on delivery fairness are on the basis of non-cooperative game-theoretic assumptions that are arguably unrealistic in the ad-hoc P2P setting. We propose an expressive yet still minimalist security requirement for desired fair P2P content delivery, and give two efficient blockchain-enabled and monetary-incentivized solutions${\mathsf {FairDownload}}$and${\mathsf {FairStream}}$for P2P downloading and P2P streaming scenarios, respectively. Our designs not only ensure delivery fairness where deliverers are paid (nearly) proportional to their in-time delivery, but also guarantee exchange fairness where content consumers and content providers are also fairly treated. The fairness of each party can be assured even when other two parties collude to arbitrarily misbehave. Our protocols provide a general design of fetching content chunk from any specific position so the delivery can be resumed in the presence of unexpected interruption. Further, our systems are efficient in the sense of achieving asymptotically optimal on-chain costs and optimal delivery communication. We implement the prototype and deploy on the Ethereum Ropsten network. Extensive experiments in both LAN and WAN settings are conducted to evaluate the on-chain costs as well as the efficiency of downloading and streaming. Experimental results show the practicality and efficiency of our protocols.
Community detection is essential in P2P network analysis as it helps identify connectivity structure, undesired centralization, and influential nodes. Existing methods primarily utilize topological data and neglect the rich content data. This paper proposes a technique combining topological and content data to detect communities inside the Bitcoin network using a deep feature representation algorithm and Deep Feedforward Autoencoders. Our results show that the Bitcoin network has a higher clustering coefficient, assortativity coefficient, and community structure than expected from a random P2P network. In the Bitcoin network, nodes prefer to connect to other nodes that share the same characteristics.
In the past, the term âDecentralized Autonomous Organization (DAO)â was used to refer to a loosely organized network of autonomous entities, such as a corporation, a cooperative, or a non-profit party. Since Ethereum pioneered smart contracts in the blockchain, the Ethereum Virtual Machine (EVM) can connect public nodes scattered throughout the network into a virtual machine to execute Turing-complete programs. The EVM can also run other applications such as decentralized autonomous organization (DAO), which is a new type of blcokchain-based organization that uses smart contracts to perform tasks on a distributed scale. The smart contracts have organizational rules and operational logic embedded and automatically execute organizational decisions and proposals making it highly decentralized and more democratic. The DAOs are organizations that are not subject to legal, physical, or economic constraints, as well as the ability to operate outside the control of a single central authority or a single governing body. Because DAO is formed by many smart contract that operate together, which makes it highly decentralized and has a strong democratic system. This paper discusses the pros and cons of DAO, and the potential of DAO in community development, especially in non-profit organizations. It is hope to provide an overall picture of DAO, and the roadmap for future development of DAO on the right track.
Distributed Ledger Technology (DLT), commonly referred to as blockchains, provide a new approach to security. Rather than securing items by blocking access, data is made immutable by creating a massively distributed data structure. Entries are secured using cryptographic primitives. Coordination is done using consensus algorithms. We start by introducing random graph theory and presenting its major result: the emergence of a giant component. We explain how and when giant components arise. We explain why the existence, or not, of giant components result in the presence, or not, of graph properties of interest. We then introduce the most widely used consensus algorithms, concentrating on potential problems. We then describe a simple light weight mining (LWM) alternative. We use Erdös's random graph theory to prove the effectiveness and efficiency of LWM. This is an example of how random graph theory can be used to design and implement robust DLT systems
Sergio Demian Lerner, Federico Jinich, Diego Masini, Shreemoy Mishra
Uncontrolled growth of blockchain state can adversely affect client performance, decentralization and security. Previous attempts to introduce duration-based state storage pricing or 'storage rent' in Ethereum have stalled, partly because of complexity. We present a new approach with finer granularity to "spread" rent payments across peers. Our proposal shifts the burden of state rent from accounts to transaction senders in a quasi-random manner. This proposal offers a simple path for initial adoption on Ethereum Virtual Machine (EVM) compatible chains, and serve as a foundation to address remaining challenges.
Han Liu, Xufei Wang, Bin Wang, Huixuan Zheng · 5 authors
The design of tokenomics, i.e., distribution and circulation mechanisms of cryptocurrency tokens, is a top priority for almost all Web3 applications which relates to their own economic systems via native cryptocurrency tokens. Unfortunately, while the sustainability of tokenomics largely determines the long-term development of a Web3 application, the tooling support for the design of it has been far too insufficient. A common practice at the time of writing is to specify tokenomics with a combination of documents, spreadsheets, code scripts etc.. In this paper, we introduce the TMI development platform for the modelling and analysis of Web3 tokenomics. TMI creates a domain-specific language and its graphical development environment for developers to succinctly model crypto-economic relations in a drag-and-drop way. Based on created models, TMI allows developers to formally analyse their tokenomics via checking fundamental economic properties, e.g., The core team of a project holds less than 20% of the project token in 36 months. A demonstration video of TMI is available at https://youtu.be/LDn-eRxPMTw.
Ethereum is one of the most actively used blockchain platforms that supports various decentralized services such as DeFi, NFT, and the Metaverse. Such services are enabled by Solidity smart contracts. A block is mined by executing a batch of transactions and reaching an agreement among consensus nodes. However, since the execution model of Ethereum is Order-Execute, all transactions must be ordered first and executed sequentially, resulting in limited block feed to consensus phase. This may lead to underutilization of consensus capacity. In this paper, we propose a parallel execution model for Solidity smart contracts using append-only shared logs. The parallel execution model consists of the following components: (1) key-value state sharding, (2) Solidity simulation module for each shard, (3) append-only log shared among Solidity simulation module; Append-only log stores the read-write set of a transaction in each entry, (4) the block mining module that is responsible for creating a block based on the shared log information and initiating the block consensus phase.
Once deployed, a decentralized blockchain system ensures that it will operate faithfully so that no one can interfere with or manipulate its predefined regulations, such as block size and block creation interval investigated in this paper. However, fixed regulations prevent that system from adapting to the change of the environment, such as increasing the underlying network capacity, and result in sub-optimal performance. For example, Bitcoin remains at 7 TPS (transactions per second), even operating over the current Internet. In this paper, we propose a new paradigm for defining the behavior of a consensus system, named as Meta-Regulation, which allows autonomous evolution of the system behavior. A meta-regulation adjusts the actual behavior of a consensus system in response to the changing capacity of the underlying infrastructure and the community of participants. We demonstrate the effectiveness of the proposed meta-regulation by achieving significantly improved throughput and latency for Bitcoin, adapted to the current capacity of the Internet. Our experimental results show that Meta-Regulation can achieve at least$7\times $performance improvement over Bitcoin network deployed in 2009, resulting in 49.7 TPS or 68% reduction confirmation latency by fully utilizing the bandwidth and the computing power of average network nodes.
Broadcasting plays a vital role in the consensus mechanisms of blockchain systems, since the consensus of each block must wait until the previous block is received by (nearly) all the nodes in the blockchain systems. Therefore, optimizing the performance of broadcasting can significantly improve the performance of the blockchain system. However, compared with other traditional P2P applications such as file downloading or video delivery, the broadcasting in blockchain has two new requirements, namely low redundancy and low propagation latency, which all the existing mechanisms (e.g. flooding, structural DHT etc.) can not meet well. In this paper, we propose Swift, a new broadcasting mechanism for blockchain systems. It optimizes the P2P topology construction and broadcast algorithm in the structured network based on unsupervised learning and greedy algorithm, effectively reducing the propagation latency of the blockchain P2P network while avoiding the waste of redundant bandwidth. We implemented a prototype of Swift and evaluated its performance on a testbed network that consists of 1000 blockchain nodes. The experimental findings show that Swift can reduce propagation latency by 19.8% with similar bandwidth consumption, generating an 18% increase in the throughput performance of the blockchain. Finally, with the increase in connections, Swift can simultaneously achieve low latency and maintain a relatively stable redundant bandwidth waste, instead of linearly increasing in flooding.
Web3, one of the novel paradigms which may drive the evolution of the future Web, is offering an invaluable volume of data stored in the supporting blockchains. Researchers from different fields such as network science, computational social science and data mining, might benefit from these large collections of temporal and heterogeneous data capturing different kinds of interaction among people and between people and the platforms. In this study we focus on a specific issue related to these modern techno-social systems, i.e. the understanding of the rules driving their growth. To reach this goal, we performed an analysis based on graph evolution rules - GERs - on different networks gathered from Web3 platforms such as Steemit or OpenSea. Graph evolution rules mining is a frequency-based method for evaluating network evolution which does not require any prior growth process for disentangling how networks evolve. By comparing the evolution rules of social network platforms and asset trading services through GER profiles, we observe that some evolution rules are common to all Web3 platforms, regardless of the system specificity. On the other hand, in specific cases, the frequency of graph evolution rules is influenced by the nature of the platform: whereas social and token-transfer networks are characterized by rules which increase network transitivity and reciprocity, NFT trading networks, especially those specialized in a specific type of digital asset, are driven by rules which form trading chains. These findings suggest that the GER approach and the GER profiles are a good starting point to get insights into the evolutionary behavior of a network and to define a classification of graph evolution rules.
In this paper, we propose GameBlockchain, an open-source blockchain framework designed to support secure transactions of NFTs in modern computer games. Its purpose is to enable game industry stakeholders such as game developers, content creators, and regular gamers to create and exchange game assets in a more secure and trusted environment. The security of traditional databases and potential data tampering or dangerous user behavior is improved, as outlined in the paper, by blockchain technology, which is used to record critical operations in a ledger, preserving the identity of the user at all times. From a technical perspective, the main goal is to provide an architecture that is easy to use, flexible, understandable, and has an extensible SDK. Using the framework, game developers and regular users should be able to create and trade assets without third-party providers, and use all related services directly in the game interface itself, without having to switch between applications or pay additional transfer fees to providers. We also encourage the development of games with shared marketplaces and wallets on both the developer and user sides, making it easier to monetize assets and services.
Feijie Wu, Ho Yin Yuen, Henry C. B. Chan, Victor C. M. Leung · 5 authors
Applying peer-to-peer (P2P) architecture to online video games has already attracted both academic and industrial interests, since it removes the need for expensive server maintenance. However, there are two major issues preventing the use of a P2P architecture, namely how to provide an effective distributed data storage solution, and how to tackle potential cheating behaviors. Inspired by emerging blockchain techniques, we propose a novel consensus model called Proof-of-Play (PoP) to provide a decentralized data storage system that incorporates an anti-cheating mechanism for P2P games, by rewarding players that interact with the game as intended, along with consideration of security measures to address the Nothing-at-stake Problem and the Long-range Attack. To validate our design, we utilize a game-theory model to show that under certain assumptions, the integrity of the PoP system would not be undermined due to the best interests of any user. Then, as a proof-of-concept, we developed a P2P game ( Infinity Battle ) to demonstrate how a game can be integrated with PoP in practice. Finally, experiments were conducted to study PoP in comparison with Proof-of-Work (PoW) to show its advantages in various aspects.
Bitcoin and blockchain technology allow for value to be transferred in small increments. This property makes Bitcoin suitable for pay-as-you-go data streaming models as an alternative to subscription-based media streaming services. One of the key mechanisms Bitcoin provides to enable such use cases is payment channels. These channels allow two parties to perform value exchanges at high frequency, without settling each individual event on-chain, making them suitable for mediating the purchase of a digital data stream on a packet-by-packet basis. However, some existing designs for Bitcoin payment channels rely on funding transactions to escrow tokens, which increases the operational cost of a data stream and can lead to the funds of peers becoming temporarily stranded in the channel. In this paper, we outline a novel payment channel design that overcomes these challenges. Our construction leverages the inherent malleability of Bitcoin transactions to allow either party to unilaterally terminate the stream at any point, without sacrificing the security of the incremental payments that have occurred up to the termination point.
Junhyeong Ryu, Aeri Kim, Meryam Essaid, Hongtaek Ju
This paper presents the development results for the Wireshark dissector of the Ethereum Node Discovery Protocol for monitoring and analyzing Ethereum P2P networks. The new version v5 of the Ethereum Node Discovery Protocol applied encryption to the traffic. Therefore, the Wireshark Node Discovery Protocol based on previous versions, such as the v4 dissector, can no longer be used to analyze the network. This paper develops a dissector that interprets encrypted packets of the Node Discovery Protocol based on Ethereum Node Discovery Protocol v5. Node Discovery Protocol analysis can be used to research network properties and improve network performance.
Christos Karapapas, Georgios Syros, Iakovos Pittaras, George C. Polyzos
The popularity of blockchain games continues to grow as Non-Fungible Tokens (NFTs) become the center of attention, contributing to the move towards Web3. We leverage the InterPlanetary File System (IPFS) and NFTs, backed by blockchains, to build a flexible, decentralized, and fair baseline system for trading games. Our solution creates a fully decentralized system, where new business models are enabled. In particular, we introduce and support the evolvability of ingame assets, enable their resale with dynamic pricing, depending on their rarity, and automatically provide a cut to the digital artists, without the need for a trusted (third) party. Our system guarantees that the in-game assets will remain online long-term, by orchestrating various decentralized services. Thus, users do not risk losing control over the artefacts or their value, even if the gaming company loses interest, or goes bankrupt. We considered and compared the Ethereum Name Service (ENS) and the InterPlanetary Name System (IPNS) as the naming component of the system and selected ENS for our solution, despite the fact it introduces monetary cost. Finally, we validate our claims and evaluate the feasibility and performance of the proposed system through a proof of concept implementation.
Aimen Djari, Emmanuelle Anceaume, Sara Tucci-Piergiovanni
The arrival of Bitcoin [1] drove the shift to decentralized ecosystems through the exchange of transactions without intermediary. However, one of the main challenges that need to face permissionless blockchains are scalability and security. In this paper, we present a performance evaluation of Sycomore++, a permissionless graph-based distributed ledger whose main feature is to dynamically self-adapt the number of created blocks to the current number of submitted transactions, and compare them with the ones of Bitcoin and Sycomore, a graph-based distributed ledger. Our evaluation relies on agent-based simulations to evaluate the capability of these distributed ledgers to address the aforementioned challenges, within different execution contexts.
In order to realize collaboration on a global scale, academic research requires often large quantities of data to be shared between geographically dispersed organizations. The requirement to protect and govern data in a network of loosely coupled, autonomous institutions is an incentive for decentralized solutions, where the participants are in full control of their data without trusting a third-party provider to store and process the data. In order to increase data availability and fault tolerance in decentralized collaborative systems, we propose a layer, which is based on replication and decentralized authority over the data. The solution consists of an idea of peer-sets, which are groups of peers implementing collective data management, a consensus protocol which synchronizes a distributed ledger between peers, and an atomic commitment protocol used to implement optional two-way references between documents. This architecture may be utilized in various decentralized collaborative data-sharing systems, such as Onedata.
Eventual consistency is a consistency model that favors liveness over safety. It is often used in large-scale distributed systems where models ensuring a stronger safety incur performance that are too low to be deemed practical. Eventual consistency tends to be uniformly applied within a system, but we argue a demand exists for differentiated eventual consistency, e.g. in blockchain systems. We propose update-query consistency with primaries and secondaries (UPS) to address this demand. UPS is a novel consistency mechanism that works in pair with our novel two-phase epidemic broadcast protocol gossip primary-secondary (GPS) to offer differentiated eventual consistency and delivery speed. We propose two complementary analyses of the broadcast protocol: a continuous analysis and a discrete analysis based on compartmental models used in epidemiology. Additionally, we propose the formal definition of a scalable consistency metric to measure the consistency trade-off at runtime. We evaluate UPS in two simulated worldwide settings: a one-million-node network and a network emulating that of the Ethereum blockchain. In both settings, UPS reduces inconsistencies experienced by a majority of the nodes and reduces the average message latency for the remaining nodes.
The advent of Ethereum opened up a pandora box of decentralized possibilities. While allowing for the replicated, decentralized computation of Turing-complete instructions, platforms such as Ethereum do not offer the possibility of direct, interactive, real-time processing of usersâ inputs that could later affect the decentralized state machine. They cannot directly observe, replicate and authenticate usersâ actions performed in real-time while presenting the results of these. They lack mechanics that would incentivize full-nodes to provide low-latency-constrained services to users in-between epochs of a decentralized state machine, thus pushing dAppsâ developers towards hybrid architecturesâones employing centralized servers while not even considering certain applications, due to the aforementioned limitations. In this research paper, we explore our results of an attempt to create a âdecentralized operating systemâ user experience a reality. We propose an architecture which solves the problems of the responsiveness and finalization of multiple actions performed by users in real-timeâwithout the need for users to pre-authenticate but after having presented a single, unitary consent to commitâthrough the hereby proposed Deferred Authentication mechanism. To allow for this, we employ an in-house developed #GridScript programming language, used by our decentralized state machine, along with a computer-vision-enabled and AI-aided mobile app (available for both iOS and Android). We introduce the concept of Decentralized Processing Threads (DPTs) and see how these enable fascinating possibilities. In addition, we look into how Access-Control-Lists (ACLs)-enabled, incentivized storage, incentivized Sybil-proof communication, embedded firewall apparatus, integrated off-the-chain payments, and crypto-incentivized off-the-chain storage aid such a system and thus render it as feasible. We highlight various interesting troubles we have encountered, such as state recovery after disconnects of the UI and the replication of its state across both nodes maintaining the network and web browsers. We depict âoff-the-chainâ mechanics, which we use to reward for real-time services provided to users by nodes maintaining the network. We tackle crypto-incentivized WebRTC swarms not needing centralized servers for signaling. We look into a user-friendly approach to Non-Fungible Tokens (NFTs). The test-bed is readily available with multiple functional UI dApps already in place. Indeed, the paper presents UI and UX design decisions we have undertaken based on conclusions from statistical research results on a group of 50,341 volunteers over 4 years, which we have used to formulate what we codenamed as the Venice UI/UX design paradigm. We extend upon the notion of Token Pools to allow for the Sybil-proof incentivization of multiple-peers from a single data structure stored on the decentralized state machine.
Sharding is a promising approach to scale permissionless blockchains. In a sharded blockchain, participants are split into groups, called shards, and each shard only executes part of the workloads. Despite its wide adoption in permissioned systems, transferring such success to permissionless blockchains is still an open problem. In permissionless networks, participants may join and leave the system at any time, making load balancing challenging. In addition, the adversary in such networks can launch the single-shard takeover attack by compromising a single shard's consensus. To address these issues, participants should be securely and dynamically allocated into different shards. However, the protocol capturing such functionality - which we call shard allocation - is overlooked.
Andrew Howell, Takfarinas Saber, Malika Bendechache
New blockchain platforms are launching at a high cadence, each fighting for attention, adoption, and infrastructure resources. Several studies have measured the peer-to-peer (P2P) network decentralisation of Bitcoin and Ethereum (i.e., two of the largest used platforms). However, with the increasing demand for blockchain infrastructure, it is important to study node decentralisation across multiple blockchain networks, especially those containing a small number of nodes. In this paper, we propose NodeMaps, a data processing framework to capture, analyse, and visualise data from several popular P2P blockchain platforms, such as Cosmos, Stellar, Bitcoin, and Lightning Network. We compare and contrast the geographic distribution, the hosting provider diversity, and the software client variance in each of these platforms. Through our comparative analysis of node data, we found that Bitcoin and its Lightning Network Layer 2 protocol are widely decentralised P2P blockchain platforms, with the largest geographical reach and a high proportion of nodes operating on The Onion Router (TOR) privacy-focused network. Cosmos and Stellar blockchains have reduced node participation, with nodes predominantly operating in large cloud providers or well-known data centres.