Blockchains are currently gaining attention as a newly emerging technology in both academia and industry, capable of impacting a variety of domains beyond cryptocurrencies. Performance modeling can be used to provide us with a deeper understanding of the behavior and dynamics within blockchain peer-to-peer networks. Blockchain system architects can leverage network models to properly tune their system and to reduce design costs significantly. In this article, we focus on the original and well-established Bitcoin blockchain network. In particular, we propose a random graph model for performance modeling and analysis of the inventory-based protocol for block dissemination. This model addresses the impact of key blockchain parameters on the overall performance of Bitcoin. We derive some explicit and closed-form equations for block propagation delay and traffic overhead in the Bitcoin network. We also adapt our model to study the impact of deploying a relay network and investigate the effect of the relay network size on the network performance and decentralization. We implement our model using the popular network simulator OMNet++. We validate the accuracy of our theoretical model and its implementation with our dataset mined from the Bitcoin network. Our results show the tradeoff between the default number of connections per node, network bandwidth, and block size in order to compute the optimal block propagation delay over the network. Additionally, we found that bigger relay networks can jeopardize the decentralization of the Bitcoin network.
Payment Channel Networks or PCNs have gained prominence ensuring faster relaying of transactions. However, this Layer-two solution has its own fair share of problems. Topological analysis on Lightning Network reveals that Griefing Attack is a major problem whereby an adversary intentionally exhausts the channel capacity of the network. It can be used for mounting series of targeted attacks like Denial-of-Service Attack, Node Isolation Attack and Channel Exhaustion Attack on honest participants as well. Though the attack does not always result in a direct monetary gain of the attacker, blocking of channel capacity for several days prevented several nodes from processing any future transaction request, leading to substantial collateral damage. Certain portions of the payment channel network get stalled which hampers the throughput and utility of the network. Mitigating Griefing Attack still remains an open problem. In this paper, we propose an efficient countermeasure for the attack, known as Griefing-Penalty. Mounting such an attack requires the attacker to pay a penalty proportional to the collateral cost of executing a payment. The penalty is used for compensating parties who incurred loss by locking funds. Our proposed strategy works for any timelock based payment protocol and ensures faster resolution of payments. To illustrate it, we propose a new payment protocol HTLC-GP or Hashed Timelock Contract with Griefing-Penalty. It not only preserves privacy but also ensures that an attacker cannot ascribe blame on any honest intermediary present in the path relaying a payment.
Andrew Cullen, Pietro Ferraro, William H. Sanders, Luigi Vigneri · 5 authors
In the Internet of Things (IoT) domain, devices need a platform to transact seamlessly without a trusted intermediary. Although distributed ledger technologies (DLTs) could provide such a platform, blockchains, such as Bitcoin, were not designed with IoT networks in mind, hence are often unsuitable for such applications: they offer poor transaction throughput and confirmation times, put stress on constrained computing and storage resources, and require high transaction fees. In this article, we consider a class of IoT-friendly DLTs based on directed acyclic graphs, rather than a blockchain, and with a reputation system in the place of Proof of Work (PoW). However, without PoW, the implementation of these DLTs requires an access control algorithm to manage the rate at which nodes can add new transactions to the ledger. We model the access control problem and present an algorithm that is fair, efficient, and secure. Our algorithm represents a new design paradigm for DLTs in which concepts from networking are applied to the DLT setting for the first time. For example, our algorithm uses distributed rate setting, which is similar in nature to transmission control used in the Internet. However, our solution features novel adaptations to cope with the adversarial environment of DLTs in which no individual agent can be trusted. Our algorithm guarantees utilization of resources, consistency, fairness, and resilience against attackers. All of these are achieved efficiently and with regard for the limitations of IoT devices. We perform extensive simulations to validate these claims.
With the development of smart cities, not only are all corners of the city connected to each other, but also connected from city to city. They form a large distributed network together, which can facilitate the integration of distributed energy station (DES) and corresponding smart aggregators. Nevertheless, because of potential security and privacy protection arisen from trustless energies trading, how to make such energies trading goes smoothly is a tricky challenge. In this paper, we propose a blockchain-based multiple energies trading (B-MET) system for secure and efficient energies trading by executing a smart contract we design. Because energies trading requires the blockchain in B-MET system to have high throughput and low latency, we design a new byzantine-based consensus mechanism (BCM) based on node's credit to improve efficiency for the consortium blockchain under the B-MET system. Then, we take combined heat and power (CHP) system as a typical example that provides distributed energies. We quantify their utilities, and model the interactions between aggregators and DESs in a smart city by a novel multi-leader multi-follower Stackelberg game. It is analyzed and solved by reaching Nash equilibrium between aggregators, which reflects the competition between aggregators to purchase energies from DESs. In the end, we conduct plenty of numerical simulations to evaluate and verify our proposed model and algorithms, which demonstrate their correctness and efficiency completely.
Andrew Cullen, Pietro Ferraro, William H. Sanders, Luigi Vigneri · 5 authors
Distributed Ledger Technologies (DLTs) (the agnostic term for blockchain) are a potential solution for many pressing issues arising in the Internet of Things (IoT) domain. These issues include facilitating secure transactions between IoT devices and immutably recording data. Most DLT architectures were not designed with IoT in mind and consequentially do not satisfy the requirements of many IoT applications. However, the relatively new class of Directed Acyclic Graph (DAG) based DLTs show great promise for IoT networks. These DLTs require the rate at which transactions are issued and disseminated to be explicitly managed in order to ensure fairness among users. We present a congestion control algorithm for these DLTs, which optimises dissemination rate and guarantees that all nodes receive the same information and have fair access even in a dishonest environment, subject to the computing limitations of nodes. Our algorithm takes inspiration from well-known areas of networking research, such as QoS, and TCP. However, an important distinction between the DLT setting and traditional networks is the unique nature of traffic in DLT networks and the fact that nodes cannot trust familiar feedback measurements, such as packet acknowledgements or congestion notifications. Our solution realises a decentralised congestion control algorithm for DLTs without the need for trust among nodes.
We present a novel game-theoretic, Bayesian reinforcement learning (RL) and deep learning (DL) framework to represent interactions of miners in public and consortium blockchains with mobile edge computing (MEC). Within the framework, we formulate a stochastic game played by miners under incomplete information. Each miner can offload its block operations to one of the base stations (BSs) equipped with the MEC server. The miners select their offloading BSs and block processing rates simultaneously and independently, without informing other miners about their actions. As such, no miner knows the past and current actions of others and, hence, constructs its belief about these actions. Accordingly, we devise a Bayesian RL algorithm based on the partially-observable Markov decision process for miner's decision making that allows each miner to dynamically adjust its strategy and update its beliefs through repeated interactions with each other and with the mobile environment. We also propose a novel unsupervised Bayesian deep learning algorithm where the uncertainties about unobservable states are approximated with Bayesian neural networks. We show that the proposed Bayesian RL and DL algorithms converge to the stable states where the miners' actions and beliefs form the perfect Bayesian equilibrium (PBE) and myopic PBE, respectively.
The emergence of smart contract promotes the popularity of blockchain applications, leading the dramatically growth of Ethereum blockchain data size. The analysis on blockchain data is urgently needed for users, e.g., collecting statistics of tokens, monitoring the status of Ethereum blockchain. However, Ethereum could only support simple searches on blockchain data on account of its storage model. This paper proposes the EBTree, an index for Ethereum blockchain Data, and implements it based on Ethereum client (Geth1.8). With the properties of B+ tree, EBTree could support real-time top-k, range, equivalent search on Ethereum blockchain data. Besides, EBTree takes up relatively small s-torage space because it only stores the identifiers of blockchain data. Meanwhile, considering of the time intervals of mining block and synchronizing data from Ethereum network, the time of insertion in EBTree has little influence on the performance of Ethereum client. We conduct experiments to evaluate the performance of EBTree. According to the result of experiments, EBTree shows great performance on searches and insertion at low cost of storage.
Blockchain technologies have drawn massive attention to the world these past few years mostly because of the burst of cryptocurrencies like Bitcoin, Etherium, Ripple and many others. A Blockchain, also known as distributed ledger technology, has demonstrated huge potential in saving time and costs. This open-source technology which generates a decentralized public ledger of transactions is widely appreciated for ensuring a high level of privacy through encryption and thus sharing the transaction details only amongst the participants involved in the transactions. The Blockchain is used not only for cryptocurrency but also by various companies to meet their business ends, such as efficient management of supply chains and logistics. The rise and fall of numerous crypto-currencies based on blockchain technology have generated debate among tech-giants and regulatory bodies. There are various groups which are working on standardizing the blockchain technology. At the same time, numerous groups are actively working, developing and fine-tuning their own blockchain platforms. Platforms such as etherium, hyperledger, parity, etc. have their own pros and cons. This research is focused on the performance analysis of blockchain platforms which gives a comparative understanding of these platforms.
Ethereum Research team has proposed a family of Casper blockchain consensus protocols for Ethereum 2.0. It has been shown in the literature that Casper Friendly Finality Gadget (Casper FFG) for Ethereum 2.0's beacon network cannot achieve liveness property in partially synchronous networks such as the Internet environment. The ``Correct-by-Construction'' family of Casper blockchain consensus protocols (CBC Casper) has been proposed as a finality gadget for the future release of Ethereum 2.0 blockchain. Unfortunately, neither constructive finality rule nor satisfactory liveness property has been obtained for CBC Casper, and it is commonly believed that CBC Casper could not achieve liveness property in asynchronous networks. This paper provides the first probabilistic CBC Casper protocol that achieves liveness property against $t=\lfloor \frac{n-1}{3}\rfloor$ Byzantine participants in complete asynchronous networks. The seminal work by Fisher, Lynch, and Paterson (FLP) shows that there does not exist a deterministic BFT protocol in complete asynchronous networks against a single failure. Existing BFT protocols for complete asynchronous networks are all probabilistic which are based either on individual coin-flipping or on common coin-flipping. This paper proposes the first secure and deterministic leaderless blockchain BFT protocol XP against $t=\lfloor \frac{n-1}{3}\rfloor$ Byzantine participants in complete asynchronous networks. This result does not contradict with FLP's impossibility results since XP leverages the total order properties of candidate blocks in blockchains (similar properties may not hold for general BFT application scenarios).
Ethereum Research team has proposed a family of Casper blockchain consensus protocols for Ethereum 2.0. It has been shown in the literature that Casper Friendly Finality Gadget (Casper FFG) for Ethereum 2.0's beacon network cannot achieve liveness property in partially synchronous networks such as the Internet environment. The "Correct-by-Construction" family of Casper blockchain consensus protocols (CBC Casper) has been proposed as a finality gadget for the future release of Ethereum 2.0 blockchain. Unfortunately, neither constructive finality rule nor satisfactory liveness property has been obtained for CBC Casper, and it is commonly believed that CBC Casper could not achieve liveness property in asynchronous networks. This paper provides the first probabilistic CBC Casper protocol that achieves liveness property against (n-1)/3 Byzantine participants in complete asynchronous networks.
Han Zhang, Weimin Lang, Chengming Liu, Bingpeng Zhang
With the rapid development of Internet of things technology, IoT security problems are increasingly prominent. Blockchain is a new application model of distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and other computer technologies, which provides a new solution to solve the security problems of IoT. This paper envisages a blockchain-based security approach architecture for IoT, which aims to construct a space of mutual trust between devices for reliable data transmission.
Monolithic blockchain architectures employed in Bitcoin and other major alt-coins are inherently non-scalable. In recent past, some hierarchical approaches have been explored to shard the decentralized blockchain to improve scalability. However, there is no discussion in the literature about how to determine an optimal shard size to maximize performance and how the presence of malicious or faulty nodes can impact on choosing an optimal shard size. To address these issues, this paper presents a sharding scheme and validation protocols for a hierarchical blockchain architecture named OptiShard. The hierarchy divides the network nodes into multiple disjoint shards and the majority of transactions are distributed among these shards in non-overlapped fashion. Optimal shard size is determined based on two parameters: performance and correctness of transaction validation in the presence of malicious or faulty nodes. OptiShard provides guaranteed majority of good shards, subject to a maximum allowable threshold of faulty nodes, by choosing the right shard size. It also provides a mechanism for identifying faulty shards and discarding all their transactions through the overlapping of a small fraction of transactions across all the shards. Experimental results performed on up to 800 Amazon EC2 nodes conform to the theoretical performance analyses and exhibit the impact of sharding the network on performance.
Over the past decades, the concept of embedded energy production popularly known as microgrids is getting implemented in a wider range due to numerous benefits which include flexibility, efficiency, improved stability, and cost-effectiveness. Opportunities for microgrids in the electricity market are becoming higher these days due to which consumers are now becoming prosumers. Energy trading in microgrids happens in peer to peer manner where there is a need for third-party involvement. To eliminate this involvement, a technology is needed to make the entire system a decentralized one which is "Blockchain". In this paper, a systematic review is conducted on how blockchain technology can be implemented in the energy sector for mitigating the issues and how peer to peer energy trading happens in the microgrids thereby smart contracts are created for purpose of P2P energy trading using solidity tool.
The popularization and rapid development of distributed energy becomes a trend of the times. Distributed energy prosumers should be able to trade with each other to reduce losses, increase efficiency, flexibility and economy. The traditional centralized power settlement scheme is not suitable for the utilization on the situation of distributed energy transaction settlement. Energy internet as the next generation energy system integrating cuttingedge information technologies with energy system could realize peerto- peer energy services. The distributed interactive concept of the energy trading is highly consistent with the principle of blockchain. In this paper, aiming at the problems of information disunity, trust system difficult to establish, power deviation waste and cost advance caused by power pre-sale, a power transaction asynchronous settlement system for microgrid is proposed based on blockchain technology. The experiment results illustrate that the system obtains promising performance by reasonable set grid structure which could meet the requirements of practical applications.
State sharding is a common solution to the scalability problem in blockchain systems, allowing nodes to hold a partial view of the system state. With such sharding, the processing of a transaction might not be completed locally within a node and require the involvement of multiple shards. Such cross-shards transactions have a high negative impact on system performance and are frequent with traditional state partition solutions which are often based on a simple mapping of data into shards. By locating together parts of the system state accessed by frequent transactions, the amount of cross-shard transactions can be reduced. On the other hand, the representation of such particular mappings can be memory intensive. In this paper, we study traffic-aware sharding that can be described in memory-efficient mappings. We first survey existing mapping schemes in common blockchains. We indicate the tradeoff between the size of the mapping of data to shards and the required transaction processing time and suggest algorithms for finding memory-light sharding of low cross-shard rate. We examine the efficiency of the solutions and the required frequency of sharding recomputation based on real transaction information of the Ethereum network.
The mechanism of peers randomly choosing logical neighbors without any knowledge about underlying physical topology can cause a delay overhead in information propagation which makes the system vulnerable to double spend attacks. This paper introduces a proximity-aware extensions to the current Bitcoin protocol, named Master Node Based Clustering (MNBC). The ultimate purpose of the proposed protocol is to improve the information propagation delay in the Bitcoin network.
The number of Internet of Things devices is growing dramatically, generating a huge amount of data which is becoming a valuable asset for data analysts. This trend culminates towards the creation of an IoT data marketplace, where streams of data from heterogeneous sources are sent in real time to various data consumers and are metered for monetization purposes. Publish/subscribe systems, such as Message Queuing Telemetry Transport (MQTT), are a promising solution to act as a transport layer for real-time data streams in a decoupled and large scale manner. However, pub/sub systems lack two key properties for an IoT data marketplace: (1) it does not provide any monetization logic; (2) it assumes that the pub/sub brokers are trusted entities, which is not the case in a decentralized or federated marketplace setting. In this paper, we address these issues using a reliable and transparent monetization system based on Distributed Ledger Technology (DLT) and smart contracts. We propose three monetization solutions and demonstrate the trade-off between the overhead of tracking IoT data on a blockchain vs. the accuracy of the monetization for data producers and consumers. In particular, we provide a Bloom filter-based solution for efficient verification of data exchange. We implement our system using Ethereum and Solidity and evaluate with respect to contract gas cost.
Henry C. Nunes, Roben Castagna Lunardi, Avelin F. Zorzo, Regio A. Michelin · 5 authors
Currently, blockchain proposals are being adopted to solve security issues, such as data integrity, resilience, and non-repudiation. To improve certain aspects, e.g., energy consumption and latency, of traditional blockchains, different architectures, algorithms, and data management methods have been recently proposed. For example, appendable-block blockchain uses a different data structure designed to reduce latency in block and transaction insertion. It is especially applicable in domains such as Internet of Things (IoT), where both latency and energy are key concerns. However, the lack of some features available to other blockchains, such as Smart Contracts, limits the application of this model. To solve this, in this work, we propose the use of Smart Contracts in appendable-block blockchain through a new model called context-based appendable-block blockchain. This model also allows the execution of multiple smart contracts in parallel, featuring high performance in parallel computing scenarios. Furthermore, we present an implementation for the context-based appendable-block blockchain using an Ethereum Virtual Machine (EVM). Finally, we execute this implementation in four different testbed. The results demonstrated a performance improvement for parallel processing of smart contracts when using the proposed model.