Roben Castagna Lunardi, Henry Cabral Nunes, Vinicius da Silva Branco, Bruno Hugentobler Lipper · 6 authors
Blockchain emerged as a solution for data integrity, non-repudiation, and availability in different applications. Data sensitive scenarios, such as Health Care, can also benefit from these blockchain properties. Consequently, different research proposed the adoption of blockchain in Health Care applications. However, few are discussed about incentive methods to attract new users, as well as to motivate the system or application usage by existing end-users. Also, little is discussed about performance during code execution in blockchains. In order to tackle these issues, this work presents the preliminary evaluation of TokenHealth, an application for collaborative health practice monitoring with gamification and token-based incentives. The proposed solution is implemented through smart contracts using Solidity in the Ethereum blockchain. We evaluated the performance of both in Ropsten test network and in a Private instance. The preliminary results show that the execution of smart contracts takes less than a minute for a full cycle of different smart contracts. Also, we present a discussion about costs for using a Private instance and the public Ethereum main network.
Onel L. Alcaraz López, Hirley Alves, Richard Demo Souza, Samuel Montejo‐Sánchez · 6 authors
Recent advances on wireless energy transfer (WET) make it a promising\nsolution for powering future Internet of Things (IoT) devices enabled by the\nupcoming sixth generation (6G) era. The main architectures, challenges and\ntechniques for efficient and scalable wireless powering are overviewed in this\npaper. Candidates enablers such as energy beamforming (EB), distributed antenna\nsystems (DAS), advances on devices' hardware and programmable medium, new\nspectrum opportunities, resource scheduling and distributed ledger technology\nare outlined. Special emphasis is placed on discussing the suitability of\nchannel state information (CSI)-limited/free strategies when powering\nsimultaneously a massive number of devices. The benefits from combining DAS and\nEB, and from using average CSI whenever available, are numerically illustrated.\nThe pros and cons of the state-of-the-art CSI-free WET techniques in ultra-low\npower setups are thoroughly revised, and some possible future enhancements are\noutlined. Finally, key research directions towards realizing WET-enabled\nmassive IoT networks in the 6G era are identified and discussed in detail.\n
Blockchain offers a decentralized, immutable, transparent system of records. It offers a peer-to-peer network of nodes with no centralised governing entity making it unhackable and therefore, more secure than the traditional paper-based or centralised system of records like banks etc. While there are certain advantages to the paper-based recording approach, it does not work well with digital relationships where the data is in constant flux. Unlike traditional channels, governed by centralized entities, blockchain offers its users a certain level of anonymity by providing capabilities to interact without disclosing their personal identities and allows them to build trust without a third-party governing entity. Due to the aforementioned characteristics of blockchain, more and more users around the globe are inclined towards making a digital transaction via blockchain than via rudimentary channels. Therefore, there is a dire need for us to gain insight on how these transactions are processed by the blockchain and how much time it may take for a peer to confirm a transaction and add it to the blockchain network. This paper presents a novel approach that would allow one to estimate the time, in block time or otherwise, it would take for a mining node to accept and confirm a transaction to a block using machine learning. The paper also aims to compare the predictive accuracy of two machine learning regression models- Random Forest Regressor and Multilayer Perceptron against previously proposed statistical regression model under a set evaluation criterion. The objective is to determine whether machine learning offers a more accurate predictive model than conventional statistical models. The proposed model results in improved accuracy in prediction.
Currently, there is no universal method to track who shared what, with whom, when and for what purposes in a verifiable way to create an individual incentive for data owners. A platform that allows data owners to control, delete, and get rewards from sharing their data would be an important enabler of user data-sharing. We propose a usable blockchain- and smart contracts-based framework that allows users to store research data locally and share without losing control and ownership of it. We have created smart contracts for building automatic verification of the conditions for data access that also naturally supports building up a verifiable record of the provenance, incentives for users to share their data and accountability of access. The paper presents a review of the existing work of research data sharing, the proposed blockchain-based framework and an evaluation of the framework by measuring the transaction cost for smart contracts deployment. The results show that nodes responded quickly in all tested cases with a befitting transaction cost.
Pingcheng Ruan, Tien Tuan Anh Dinh, Dumitrel Loghin, Meihui Zhang · 7 authors
Blockchain has come a long way: a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain evolves into another data management system, the natural question is how it compares against distributed database systems. Existing works on this comparison focus on high-level properties, such as security and throughput. They stop short of showing how the underlying design choices contribute to the overall differences. Our work fills this important gap and provides a principled framework for analyzing the emerging trend of blockchain-database fusion. We perform a twin study of blockchains and distributed database systems as two types of transactional systems. We propose a taxonomy that illustrates the dichotomy across four dimensions, namely replication, concurrency, storage, and sharding. Within each dimension, we discuss how the design choices are driven by two goals: security for blockchains, and performance for distributed databases. To expose the impact of different design choices on the overall performance, we conduct an in-depth performance analysis of two blockchains, namely Quorum and Hyperledger Fabric, and two distributed databases, namely TiDB, and etcd. Lastly, we propose a framework for back-of-the-envelope performance forecast of blockchain-database hybrids.
IOTA opened recently a new line of research in distributed ledgers area by targeting algorithms that ensure a high throughput for the transactions generated in IoT systems. Transactions are continuously appended to an acyclic structure called tangle and each new transaction selects as parents two existing transactions (called tips) that it approves. G-IOTA, a very recent improvement of IOTA, targets to protect tips left behind offering hence a good confidence level. However, this improvement had a cost: the use of an additional tip selection mechanism which may be critical in IoT systems since it needs additional energy consumption. In this paper we propose a new metamorphic algorithm for tip selection that offers the best guaranties of both IOTA and G-IOTA. Our contribution is two fold. First, we propose a parameterized algorithm, E-IOTA, for tip selection which targets to reduce the number of random walks executed in previous versions (IOTA and G-IOTA) while maintaining the same security guaranties as IOTA and the same confidence level and fairness with respect to tips selection as G-IOTA. Then we propose a formal analysis of the security guaranties offered by E-IOTA against various attacks mentioned in the original IOTA proposal (e.g. large weight attack, parasite chain attack and splitting attack). Interestingly, to the best of our knowledge this is the first formal analysis of the security guaranties of IOTA and its derivatives.
Francesco Zola, Cristina Pérez‐Solà, Jon Egana, Maria Eguimendia · 5 authors
Bitcoin is a peer-to-peer distributed cryptocurrency system, that keeps all transaction history in a public ledger known as blockchain. The Bitcoin network is implicitly pseudoanonymous and its nodes are controlled by independent entities making network analysis difficult. This calls for the development of a fully controlled testing environment. This paper presents Kriptosare.gen, a dockerized automatized Bitcoin testbed, for deploying full-scale custom Bitcoin networks. The testbed is deployed in a single machine executing four different experiments, each one with different network configuration. We perform a cost analysis to investigate how the resources are related with network parameters and provide experimental data quantifying the amount of computational resources needed to run the different types of simulations. Obtained results demonstrate that it is possible to run the testbed with a configuration similar to a real Bitcoin system.
Dumitrel Loghin, Gang Chen, Tien Tuan Anh Dinh, Beng Chin Ooi · 5 authors
Motivated by the massive energy usage of blockchain, on the one hand, and by significant performance improvements in low-power, wimpy systems, on the other hand, we perform an in-depth time-energy analysis of blockchain systems on low-power nodes in comparison to high-performance nodes. We use three low-power systems to represent a wide range of the performance-power spectrum, while covering both x86/64 and ARM architectures. We show that low-end wimpy nodes are struggling to run full-fledged blockchains mainly due to their small and low-bandwidth memory. On the other hand, wimpy systems with balanced performance-to-power ratio achieve reasonable performance while saving significant amounts of energy. For example, Jetson TX2 nodes achieve around 80% and 30% of the throughput of Parity and Hyperledger, respectively, while using 18x and 23x less energy compared to traditional brawny servers with Intel Xeon CPU.
Renlord Yang, Toby Murray, Paul Rimba, Udaya Parampalli
Ethereum's Gas mechanism attempts to set transaction fees in accordance with the computational cost of transaction execution: a cost borne by default by every node on the network to ensure correct smart contract execution. Gas encourages users to author transactions that are efficient to execute and in so doing encourages node diversity, allowing modestly resourced nodes to join and contribute to the security of the network. However, the effectiveness of this scheme relies on Gas costs being correctly aligned with observed computational costs in reality. In this work, we performed the first large scale empirical study to understand to what degree this alignment exists in practice, by collecting and analyzing Tera-bytes worth of nanosecond-precision transaction execution traces. Besides confirming potential denial-of-service vectors, our results also shed light on the role of I/O in transaction costs which remains poorly captured by the current Gas cost model. Finally, our results suggest that under the current Gas cost model, nodes with modest computational resources are disadvantaged compared to their better resourced peers, which we identify as an ongoing threat to node diversity and network decentralization.
Thanh Son Lam Nguyen, Guillaume Jourjon, Maria Potop-Butucaru, Kim Thai
Blockchain has become one of the most attractive technologies for applications, with a large range of deployments such as production, economy, or banking. Under the hood, Blockchain technology is a type of distributed database that supports untrusted parties. In this paper we focus Hyperledger Fabric, the first blockchain in the market tailored for a private environment, allowing businesses to create a permissioned network. Hyperledger Fabric implements a PBFT consensus in order to maintain a non forking blockchain at the application level. We deployed this framework over an area network between France and Germany in order to evaluate its performance when potentially large network delays are observed. Overall we found that when network delay increases significantly (i.e. up to 3.5 seconds at network layer between two clouds), we observed that the blocks added to our blockchain had up to 134 seconds offset after 100 th block from one cloud to another. Thus by delaying block propagation, we demonstrated that Hyperledger Fabric does not provide sufficient consistency guaranties to be deployed in critical environments. Our work, is the fist to evidence the negative impact of network delays on a PBFT-based blockchain.
Ethereum clients execute transactions in a sequential order prescribed by the consensus protocol. This is a safe and conservative approach to blockchain transaction processing which forgoes running transactions in parallel even when doing so would be beneficial and safe, e.g., when there is no intersection in the sets of accounts that the transactions read or modify. In this work we study the degree of transaction parallelizability and present results from three different simulations using real Ethereum transaction data. Our simulations demonstrate that notable gains are achievable with parallelization, and suggest that the potential for parallelizability improves as transaction rates increase.
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.
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.
Arati Baliga, I Subhod, Pandurang Kamat, Siddhartha Chatterjee
Quorum is a permissioned blockchain platform built from the Ethereum codebase with adaptations to make it a permissioned consortium platform. It is one of the key contenders in the permissioned ledger space. Quorum supports confidentiality and privacy of smart contracts and transactions, and crash and Byzantine fault tolerant consensus algorithms. In this paper, we characterize the performance features of Quorum. We study the throughput and latency characteristics of Quorum with different workloads and consensus algorithms that it supports. Through a suite of micro-benchmarks, we explore how certain transaction and smart contract parameters can affect transaction latencies.
<p style='text-indent:20px;'>In Bitcoin system, transactions are prioritized according to transaction fees. Transactions without fees are given low priority and likely to wait for confirmation. Because the demand of micro payment in Bitcoin is expected to increase due to low remittance cost, it is important to quantitatively investigate how transactions with small fees of Bitcoin affect the transaction-confirmation time. In this paper, we analyze the transaction-confirmation time by queueing theory. We model the transaction-confirmation process of Bitcoin as a priority queueing system with batch service, deriving the mean transaction-confirmation time. Numerical examples show how the demand of transactions with low fees affects the transaction-confirmation time. We also consider the effect of the maximum block size on the transaction-confirmation time.