Blockchains can provide integrity and authenticity, but their limited storage capacity can be a challenge when it comes to storing large amounts of data. To address this issue, off-chain storage solutions such as the InterPlanetary File System (IPFS) can be utilized. This has led to the emergence of various applications that utilize both blockchain and IPFS. After reviewing a large body of literature utilizing blockchain and IPFS, we found that the coordinated interaction between blockchain and IPFS can help solve many problems and provide many research opportunities. Therefore, this survey paper aims to introduce the interaction mechanism between blockchain and IPFS. We first provide a general overview and comparison of different P2P data networks to help understand why IPFS is suitable as the storage layer for blockchains. Subsequently, we use select applications that leverage blockchain and IPFS to show how the mechanism works and explore new developments in this area. Specifically, we identify research areas and provide a qualitative comparison of these different applications. From the comparison, we derive research goals related to the interaction mechanism between blockchain and IPFS.
A novel data structure that enables the storage and retrieval of linear array numeric data with logarithmic time complexity updates, range sums, and rescaling is introduced and studied. Computing sums of ranges of arrays of numbers is a common computational problem encountered in data compression, coding, machine learning, computational vision, and finance, among other fields. Efficient data structures enabling log n updates of the underlying data (including range updates), queries of sums over ranges, and searches for ranges with a given sum have been extensively studied (n being the length of the array). Two solutions to this problem are well-known: Fenwick trees (also known as Binary Indexed Trees) and Segment Trees. The new data structure extends the capabilities for the first time to further enable multiplying (rescaling) ranges of the underlying data by a scalar as well in log n. Scaling by 0 can be enabled, with the effect that subsequent updates may take (log n)2time. The new data structure introduced here consists of a pair of interacting Fenwick tree-like structures, one of which holds the unscaled values and the other of which holds the scalars. Experimental results demonstrating performance improvements for the multiplication operation on arrays from a few dozen to over 30 million data points are discussed. This research was done as part of Ajna Labs in the course of developing a decentralized finance protocol. It enables an efficient on-chain encoding and processing of an order book-like data structure used to manage lending, interest, and collateral.
Cryptocurrencies, introduced in 2009 with the first cryptocurrency, Bitcoin, have grown significantly in recent years and attracted attention globally. One of the main characteristics of cryptocurrencies and their key innovation is that they are underpinned by distributed ledger technology (DLT) or blockchain as a type of DLT. This technology enables cryptocurrencies to be transferred, stored or traded electronically within DLT-based systems in a peer-to-peer manner among (pseudonymous) system participants across the world without the involvement of the usual central trusted authorities or intermediaries such as banks. This raises the question of if, and how, one should ascertain internationality for cryptocurrency transfers taking place within truly global systems underpinned by DLT for private international law purposes. This article aims to raise awareness of and address the question of internationality in the context of cryptocurrency transfers in DLT-based systems. It considers internationality in private international law, potential factors that might be relevant in ascertaining internationality for cryptocurrency transfers through a comparison to that for electronic funds transfers (EFTs), and the approaches of the International Institute for the Unification of Private Law (UNIDROIT) and the Hague Conference for Private International Law (HCCH) on internationality in their current projects concerning digital assets and digital economy respectively.
The music industry has undergone a profound transformation in the digital age, shifting from traditional physical media to digital formats and streaming services. This article provides an overview of this evolution, emphasizing key milestones and trends. It begins by exploring the dominance of physical media, such as vinyl records, cassette tapes, and CDs, and the impact of these formats on music distribution and consumption. The digital revolution is then examined, highlighting the emergence of digital music formats like MP3 and AAC, along with pioneering services like Napster and iTunes that facilitated digital music consumption. The subsequent section discusses the rise of streaming services like Spotify and Apple Music, which have redefined how music is accessed and monetized. In the current landscape, several trends are shaping the music industry, including the integration of artificial intelligence (AI) for music recommendation and composition, blockchain technology for transparent royalty tracking, and the use of non-fungible tokens (NFTs) to tokenize music ownership. Finally, the article speculates on the future of the music industry in the digital era, considering possibilities such as virtual reality (VR) and augmented reality (AR) experiences for live performances and the evolving role of social media in music trends and fan engagement. As the music industry continues to adapt to technological advancements and changing consumer preferences, it faces both opportunities and challenges. Navigating these shifts requires collaboration, innovation, and a commitment to fairly compensating artists. The journey of the music industry through the digital age is a dynamic narrative that will continue to unfold in fascinating ways.
Chryssis Georgiou, Michel Raynal, Elad M. Schiller
Numerous distributed applications, such as cloud computing and distributed ledgers, necessitate the system to invoke asynchronous consensus objects an unbounded number of times, where the completion of one consensus instance is followed by the invocation of another. With only a constant number of objects available, object reuse becomes vital. We investigate the challenge of object recycling in the presence of Byzantine processes, which can deviate from the algorithm code in any manner. Our solution must also be self-stabilizing, as it is a powerful notion of fault tolerance. Self-stabilizing systems can recover automatically after the occurrence of arbitrary transient faults, in addition to tolerating communication and (Byzantine or crash) process failures, provided the algorithm code remains intact. We provide a recycling mechanism for asynchronous objects that enables their reuse once their task has ended, and all non-faulty processes have retrieved the decided values. This mechanism relies on synchrony assumptions and builds on a new self-stabilizing Byzantine-tolerant synchronous multivalued consensus algorithm, along with a novel composition of existing techniques.
Ethereum is one of the first blockchains executing smart contracts (financial applications directly executed on the ledger using a virtual machine). The performance of the Ethereum virtual machine has become a bottleneck caused by high volumes of transactions due to blockchain applications, including decentralized finance and non-fungible tokens. Hence, there is a need to detail the execution characteristics of the Ethereum virtual machine before its performance can be improved. This work introduces an off-line Ethereum virtual machine tracer called EVMTracer that produces runtime data dependence graphs from executed transactions as an alternative program representation. From the runtime dependence graphs, we can deduce valuable metrics about program execution characteristics, including the degree of parallelization and computational redundancies in smart contracts. Our experiments encompass all blocks up to 12M on the Ethereum mainnet. We found a geometric mean of 1.90× theoretical maximum speedup when executing the smart contracts in parallel and identified 34.97% of SLOAD instructions as redundant.
Franck Cassez, Joanne Fuller, Milad K. Ghale, David J. Pearce · 5 authors
The Ethereum protocol implements a replicated state machine. The network participants keep track of the system state by: 1) agreeing on the sequence of transactions to be processed and 2) computing the state transitions that correspond to the sequence of transactions. Ethereum transactions are programs, called smart contracts, and computing a state transition requires executing some code. The Ethereum Virtual Machine (EVM) provides this capability and can execute programs written in EVM bytecode. We present a formal and executable semantics of the EVM written in the verification-friendly language Dafny: it provides (i) a readable, formal and verified specification of the semantics of the EVM; (ii) a framework to formally reason about bytecode.
Cryptocurrencies have taken the finance world by storm and emerged as global payment tokens in the emerging area of decentralized finance and also as investment avenues of great interest among investors, especially during and post-Covid times.Cryptocurrency or a crypto is a collection of binary data which is designed to work as a medium of exchange. However, today cryptocurrency has taken many forms and derived different utilities. With cryptocurrency being at the centre of decentralised financing, various forms of new / modern decentralised financing avenues have opened up. A cryptocurrency can be used as a form of digital currency, as cash to pay for the purchase of everyday items, to purchase of large items such as buildings, cars etc. It can be bought through several digital wallets or through trading platforms like WazirX, CoinSwitch, CoinDCX, etc., Meanwhile, cryptocurrencies are treated as property or investment avenues as well in several countries. In India, mostly crypto is treated as an investment avenue similar in functionality that of a share.Though crypto is a buzz-word in finance world these days, there are a lot of uncertainties involved with it when it comes to its regulation, taxation and volatility, etc. Thus, in this paper an attempt is made to understand the factors which influences the investors to invest in cryptocurrencies.
User identification in decentralized systems is a demanding task. Identification systems should work resiliently and have efficient performance. Moreover, identification systems should protect the data that they must store against hackers and saboteurs. Keeping a system with decentralized identification without any intervention in the middle has attracted attention to improve earlier centralized identification systems. Decentralized Identifiers (DIDs) constitute a solution for identification divided into different modules. The verifiable data registry is one of the main parts of this technology, which is distributed storage of identity properties. We analyze the decentralized identification data registry and compare the performance of verifiable data registry based on blockchain and the Distributed Hash Table (DHT) on different scales of systems. Our evaluation results show that DHT has better performance. Furthermore, a model based on DHT shows that in addition to immutable storage and faster query time, it makes systems handle or search in data storage with lower searching time compared to Ethereum Blockchain as another immutable secure technology. Finally, our results show that DHT is a better solution than other models in different scenarios. Although blockchain has promising results on a small scale, it still has problems with storage and query time in large-scale systems.
Web3 aims at creating a decentralized platform that is competitive with modern cloud infrastructures that support today's Internet. However, Web3 is still limited, supporting only applications in the domains of content creation and sharing, decentralized financing, and decentralized communication. This is mainly due to the technologies supporting Web3: blockchain, IPFS, and libp2p, that although provide a good collection of tools to develop Web3 applications, are still limited in terms of design and performance. This motivates the need to better understand these technologies as to enable novel optimizations that can push Web3 to its full potential. Unfortunately, understanding the current behavior of a fully decentralized large-scale distributed system is a difficult task, as there is no centralized authority that has full knowledge of the system operation. To this end, in this paper we characterize the workload of IPFS, a key enabler of Web3. To achieve this, we have collected traces from accesses performed by users to one of the most popular IPFS gateways located in North America for a period of two weeks. Through the fine analysis of these traces, we gathered the amount of requests to the system, and found the providers of the requested content. With this data, we characterize both the popularity of requested and provided content, as well as their geo-location (by matching IP address with the MaxMind database). Our results show that most of the requests in IPFS are only to a few different content, that is provided by large portion of peers in the system. Furthermore, our analysis also shows that most requests are provided by the two largest portions of providers in the system, located in North America and Europe. With these insights, we conclude that the current IPFS architecture is sub-optimal and propose a research agenda for the future.
Zk-SNARK unleashes the great potential of ZKP (zero-knowledge proof) in the blockchain, distributed storage, etc. However, the proof-generation of zk-SNARK is excessively time intensive, making it a challenge to deploy a high-performance zk-SNARK in most real applications. As a result, NTT (Number Theoretic Transform), one of the most time-consuming parts in proof-generation, needs to be accelerated significantly. To address this issue, we propose a novel and efficient “data reordering” technique to enable a highly pipelined architecture, on which an FPGA-based hardware accelerator is designed to support the large-bitwidth and large-scale NTT tasks in zk-SNARK. Our architecture achieves a two-level pipeline: 1) the top-level pipeline is achieved among smaller NTT sub-tasks, which are decomposed from a large-scale NTT task; 2) the bottom-level pipeline is achieved in each sub-task, among butterfly operations with different step sizes. This architecture can effectively reduce the data dependency and memory access requirements, meanwhile, can be flexibly scaled to different scales of FPGAs. To balance computing efficiency and flexibility, the OpenCL equipped with HLS is used to implement the heterogeneous acceleration system. We prototype the accelerator on the AMD-Xilinx Alveo U50 card (UltraScale+ XCU50 FPGA). The evaluation results show that 1) our accelerator shows high scalability for different scales of FPGAs with a stable performance improvement; 2) it performs 1.95× faster than the one in PipeZK; 3) and it achieves 27.98×, 1.74× speedup and 6.9×, 6× energy efficiency improvement than AMD Ryzen 9 5900X single core and 12 cores respectively when integrated into the well-known ZKP open-source project, Bellman.
Private blockchain as a replicated transactional system shares many commonalities with distributed database. However, the intimacy between private blockchain and deterministic database has never been studied. In essence, private blockchain and deterministic database both ensure replica consistency by determinism. In this paper, we present a comprehensive analysis to uncover the connections between private blockchain and deterministic database. While private blockchains have started to pursue deterministic transaction executions recently, deterministic databases have already studied deterministic concurrency control protocols for almost a decade. This motivates us to propose Harmony, a novel deterministic concurrency control protocol designed for blockchain use. We use Harmony to build a new relational blockchain, namely HarmonyBC, which features low abort rates, hotspot resiliency, and inter-block parallelism, all of which are especially important to disk-oriented blockchain. Empirical results on Smallbank, YCSB, and TPC-C show that HarmonyBC offers 2.0x to 3.5x throughput better than the state-of-the-art private blockchains.
Smart contracts are programs running on Ethereum, whose deployment and use require gas. Gas measures the cost of performing specific operations as an index designed to quantify the computing power consumption. Existing unoptimized smart contracts make contract developers and users spend extra gas. To save gas and optimize smart contracts, this paper proposes a new tool named GaSaver for automatically detecting gas-expensive patterns based on Solidity source code. Specifically, we first identify 12 gas-expensive patterns in smart contracts and classify them into three categories: storage-related, judgment-related, and loop-related. Then, we deploy gas-expensive patterns and group them into three levels according to gas waste degree. By conducting extensive experiments on real data sets, we find that 89.68$\%$of the 1172 smart contracts suffer from gas-expensive patterns, 94.27$\%$of 1100 new smart contracts are gas-expensive, and 80.56$\%$of 72 widely used smart contracts are affected. Finally, the experiment results show that the proposed GaSaver can effectively optimize smart contracts. Besides, the proportion of gas-expensive cases in widely used smart contracts is lower than that in the newly released smart contracts.
Karl Wüst, Kari Kostiainen, Noah Delius, Srđjan Čapkun
Due to the popularity of blockchain-based cryptocurrencies, the increasing digitalization of payments, and the constantly reducing role of cash in society, central banks have shown an increased interest in deploying central bank digital currencies (CBDCs) that could serve as a digital cash-equivalent. While most recent research on CBDCs focuses on blockchain technology, it is not clear that this choice of technology provides the optimal solution. In particular, the centralized trust model of a CBDC offers opportunities for different designs. In this paper, we depart from blockchain designs and instead build on ideas from traditional e-cash schemes. We propose a new style of building digital currencies that combines the transaction processing model of e-cash with an account-based fund management model. We argue that such a style of building digital currencies is especially well-suited to CBDCs. We also design the first such digital currency system, called Platypus, that provides strong privacy, high scalability, and expressive but simple regulation, which are all critical features for a CBDC. Platypus achieves these properties by adapting techniques similar to those used in anonymous blockchain cryptocurrencies like Zcash to fit our account model and applying them to the e-cash context.
Christian Berger, Sadok Ben Toumia, Hans P. Reiser
The novel blockchain generation of Byzantine fault-tolerant (BFT) state machine replication (SMR) protocols focuses on scalability and performance to meet the requirements of distributed ledger technology (DLT), e.g., decentralization and geographic dispersion. Validating scalability and performance of BFT protocol implementations requires careful evaluation. While experiments with real protocol deployments usually offer the best realism, they are costly and time-consuming. In this paper, we explore simulation of unmodified BFT protocol implementations as a method for cheap and rapid protocol evaluation: We can accurately forecast the performance of a BFT protocol while experimentally scaling its environment, i.e., by varying the number of nodes or geographic dispersion. Our approach is resource-friendly and preserves application-realism, since existing BFT frameworks can be simply plugged into the simulation engine without requiring code modifications or re-implementation.
Our work presents two fundamental contributions. On the application side, we tackle the challenging problem of predicting day-ahead crypto-currency prices. On the methodological side, a new dynamical modeling approach is proposed. Our approach keeps the probabilistic formulation of the state-space model, which provides uncertainty quantification on the estimates, and the function approximation ability of deep neural networks. We call the proposed approach the deep state-space model. The experiments are carried out on established cryptocurrencies (obtained from Yahoo Finance). The goal of the work has been to predict the price for the next day. Benchmarking has been done with both state-of-the-art and classical dynamical modeling techniques. Results show that the proposed approach yields the best overall results in terms of accuracy.
Since executing a smart contract on the Ethereum blockchain costs money (measured in gas ), smart contract developers spend significant effort in reducing gas usage. In this paper, we propose a new technique for reducing the gas usage of smart contracts by changing the underlying data layout. Given a smart contract P and a type-level transformation, our method automatically synthesizes a new contract P ′ that is functionally equivalent to P . Our approach provides a convenient DSL for expressing data type refactorings and employs program synthesis to generate the new version of the contract. We have implemented our approach in a tool called Solidare and demonstrate its capabilities on real-world smart contracts from Etherscan and GasStation. In particular, we show that our approach is effective at automating the desired data layout transformation and that it is useful for reducing gas usage of smart contracts that use rich data structures.