R. P. Jagadeesh Chandra Bose, Kanchanjot Kaur Phokela, Vikrant Kaulgud, Sanjay Podder
There has been a considerable shift in the way how software is built and delivered today. Most deployed software systems in modern times are created by (autonomous) distributed teams in heterogeneous environments making use of many artifacts, such as externally developed libraries, drawn from a variety of disparate sources. Stakeholders such as developers, managers, and clients across the software delivery value chain are interested in gaining insights such as how and why an artifact came to where it is, what other artifacts are related to it, and who else is using this. Software provenance encompasses the origins of artifacts, their evolution, and usage and is critical for comprehending, managing, decision-making, and analyzing software quality, processes, people, issues etc. In this paper, we propose an extensible framework based on standard provenance model specifications and blockchain technology for capturing, storing, exploring, and analyzing software provenance data. Our framework (i) enhances trustworthiness of provenance data (ii) uncovers non-trivial insights through inferences and reasoning, and (iii) enables interactive visualization of provenance insights. We demonstrate the utility of the proposed framework using open source project data.
Alex Kaplunovich, Karuna Pande Joshi, Yelena Yesha
While adopting Blockchain technologies to automate their enterprise functionality, organizations are recognizing the challenges of scalability and manual configuration that the state of art present. Scalability of Hyperledger Fabric is an open challenge recognized by the research community. We have automated many of the configuration steps of installing Hyperledger Fabric Blockchain on AWS infrastructure and have benchmarked the scalability of that system. We have used the UCR (University of California Riverside) Time Series Archive with 128 timeseries datasets containing over 191,177 rows of data totaling 76,453,742 numbers. Using an automated Serverless approach, we have loaded this dataset, by chunks, into different AWS instances, triggering the load by SQS messaging. In this paper, we present the results of this benchmarking study and describe the approach we took to automate the Hyperledger Fabric processes using serverless Lambda functions and SQS triggering. We will also discuss what is needed to make the Blockchain technology more robust and scalable.
The access efficiency of traceability information has always been one of the main challenges faced by blockchain tracking schemes. At present, the tracking scheme based on blockchain mainly uses the open source Ethereum to realize the record of data flows and the query about transaction information. It causes the consumption of consensus resource high and the transaction query slow, which makes it difficult to meet the need of data tracking. To solve the above problems, this paper proposes a blockchain data provenance scheme based on grouping consensus and B-M tree. Firstly, a grouping consensus mechanism is constructed based on PBFT mechanism to improve the speed of transaction confirmation and complete the fast record of flow information. Then, a B-M transaction tree is designed based on AVL tree and Merkle tree to achieve the efficient query of traceability information under the ensuring that the transaction information can't be tampered. Finally, the correctness, security and simulation results show that the scheme has certain advantages over the traditional blockchain traceability scheme in record and query.
Muhammad Taimour Azhar, Muhammad Burhan Khan, Muhammad Mohsin Zafar
Block chain technology is a distributed or decentralized system that consist of nodes also called participants that communicate with each other to perform transactions. These transactions are then securely stored as blocks in the form of a chain. This is a continuous growing list of blocks and the transactions are executed by using cryptographic protocols. The point to be noted is that there is no need of any third party to perform the transaction, only the concerned stakeholders are involved. The study in this paper suggests the innovative use of Block chain platform and discusses the implementation process in the Project Management office (PMO) scenario. The main responsibility of PMO in an organization is to deliver projects on time while overcoming the risks and mitigations. Similarly, Financial Capitalization and Cash flow are also significant processes. So, different key roles of PMO are presented along with the concerned stakeholders. Each stakeholder is referred to as a particular node of our Block Chain system. In this study we would discuss and share the proof of implementation of Project Life Cycle with an existing Block chain ledger platform. It is concluded after reviewing the latest stuff in the subjected area that Block chain based Hyperledger platforms by Linux Foundation are getting maturity day-by-day. Thus, contributing towards another revolution in Financial, Management and Technical processes. Our end result brief the significant outcomes with the advantages of the Project Life Cycle proposed architecture implemented on Hyperledger platform.
Abstract In the current paper the issues of the workload relocation in the fog- and edge-computing environments are in-question. The workload relocation problem is closely connected to the scheduling problems, yet, outside the cloud there is almost unlimited number of nodes to place the computational tasks. So the search space for the optimization problem grows, and the time of the workload relocation degrades. We emphasize the techniques to limit the set of candidate nodes for the tasks distribution. In the paper two approaches are proposed and considered in terms of time consumption. The simple models are developed with the following simulation. Also the distributed-ledger-based modifications of the techniques are proposed and examined.
In this study, a trusted holistic abstraction is proposed and analytically discussed using universal scalability law and Markovian chain Monte-Carlo method. Moreover, a feedback mechanism is modeled to explain the elasticity performance of the proposed distributed system. The system extends the data locality to the edges in a trusted manner and ensures trust while scaling the whole system and increasing the number of nodes. By the help of such a trusted solution, lineage information of the data at the edges enable fault-recovery from an available checkpoint, while maximizing the trustworthiness of the overall system. Innovative distributed data structures, make databases fresh for all scaled nodes by unifying the memory resources; minimize the need to trusted third parties via trusted distributed data structures, which uses checksums of the datum periodically. Hence, multi-layer neural networks and hierarchical tree structures, has confidential data, can be updated and trained dynamically. Searching speed and performance of an object or set of objects in massive systems is maximized while keeping the trustworthiness of the total system. Initial results indicate that the trust cost worth to pay to scale and to keep the performance of the whole system. The System also shows good elasticity in the case of sudden provisioning/de-provisioning of control nodes. The proposed system also has satisfactory resource-allocation capability with efficient clustering thanks to the introduction of distributed ledger-based transaction management and lineage data recording for dynamic management of DAG structures, has sub-modular and disjoint cluster sets. Initial results of micro-blog analytics indicate promising performance of unified batch/interactive/ad-hoc querying with the holistic abstraction.
A major yet trivial problem in the banking industry right now is how tedious and costly the traditional Know- Your-Customer(KYC) process is. The process is also tiresome for customers as they need to undergo the same process for each bank or financial institution with which they intend to work. Personal experiences of people dictate the cumbersome nature of the process, thereby demanding an efficacious alternative. Through this paper, we intend to do exactly that. We propose a new solution based on Distributed Ledger Technology or Blockchain technology, which will reduce the traditional KYC verification process cost for Institutions and cut short the general time line of the completion of the process while making it smoother for the customers. Major enhancement in our solution over the conventional methods is that the whole verification process is conducted only once for each customer, irrespective of number of institutions he or she wishes to be linked to. Also, since we are using the DLT, verification results can be securely shared with the customers thereby increasing transparency. Following this approach, we developed a Proof of Concept (POC) with the Ethereum API, websites as endpoints and an android app as front office; realising the feasibility and effectiveness of this approach. All in all, this approach improves customer experience, reduces cost overheads, and increases transparency in the process of onboarding a customer.
Han Qiu, Xiao Wu, Shuyi Zhang, Victor C. M. Leung · 5 authors
Blockchain has become novel solutions for many traditional issues in computer science and finance. Recently, with the release of Libra blockchain from Facebook, the decentralized finance concepts have another huge development. However, there are already many different blockchain systems existing now and the development of blockchain systems have become more and more complicated since each kind of blockchain development environment will consume time to be built. To make the programming on different blockchain systems more easily, we propose a novel cloud-based solution, namely ChainIDE, for the development of blockchain-based smart contracts on multiple kinds of blockchain systems. With chainIDE, cross-chain developing of smart contracts on different blockchain systems can be easily done without any time consumed by building the environment. Based on the operation statistics in this paper, we served more than 310,000 compilations in the past 30 days which makes us the most popular cloud-based cross-chain development platform in the world.
Nicolas Lagaillardie, Mohamed Aimen Djari, Önder Gürcan
Fairness is a crucial property for blockchain systems since it affects the participation: the ones that find the system fair tend to stay or enter, the ones that find the system unfair tend to leave. While current literature mainly focuses on fairness for Bitcoin-like blockchains, little has been done to analyze Tendermint. Tendermint is a blockchain technology that uses a committee-based consensus algorithm, which finds an agreement among a set of block creators (called validators), even if some are malicious. Validators are regularly selected to the committee based on their investments. When a validator does not have enough asset to invest, it can increase it with the help of participants that delegate their assets to the validators (called delegators). In this paper, we implement the default Tendermint model and a Tendermint model for fairness in a multi-agent blockchain simulator where participants are modeled as rational agents who enter or leave the system based on their utility values. We conducted experiments for both models where agents have different investment strategies and with various numbers of delegators. In the light of our experimental evaluation, we observed that while, for both models, the fairness decreases and the system shrinks in the absence of delegators, the fairness increases, and the system expands for the second model in the presence of delegators.
Current blockchain systems face the problems of poor scalability, low performance, and high cost. To address the previous bottlenecks, we plan to employ the DAG-based structure as the primary method and propose a concrete model, called 3D-DAG, to improve the scalability. The model consists of two layers: mainchain and sidechain, which separately severs for maintaining the pivot sequence and improving the parallelism. Our expecting results should significantly improve the performance and scalability without compromising the security.
Due to the limitation of the capacity of each block, when the number of transactions increases at the same time, it will face congestion problems and reduce the efficiency of accounting. Collaborative computing and data slicing are effective methods to improve performance, and they have been widely used in various fields. This paper proposes a tree chain architecture that adds peer-to-peer blockchain to main chain of the Ethereum. When there is a task to be processed in the main chain, the architecture assigns the task to "branch" or "leaf". The "branch" first determines whether the task can be sliced. If the task can be sliced, divide the task into leaf nodes for processing, otherwise let the branch nodes handle. By assigning tasks in this way, it is possible to help the main chain reduce the computational pressure and increase the system throughput.
Jae-Yun Kim, Jun-Mo Lee, Yeon-Jae Koo, Sang-Hyeon Park · 5 authors
As ethereum blockchain has become popular, the number of users and transactions has skyrocketed, causing an explosive increase of its data size. As a result, ordinary clients using PCs or smartphones cannot easily bootstrap as a full node, but rely on other full nodes such as the miners to run or verify transactions. This may affect the security of ethereum, so light bootstrapping techniques such as fast sync has been proposed to download only parts of full data, yet the space overhead is still too high. One of the biggest space overhead that cannot easily be reduced is caused by saving the state of all accounts in the block's state trie. Fortunately, we found that more than 90% of accounts are inactive and old transactions are hard to be manipulated. Based on these observations, this paper propose a novel optimization technique called ethanos that can reduce bootstrapping cost by sweeping inactive accounts periodically and by not downloading old transactions. If an inactive account becomes active, ethanos restore its state by running a restoration transaction. Also, ethanos gives incentives for archive nodes to maintain the old transactions for possible re-verification. We implemented ethanos by instrumenting the go-ethereum (geth) client and evaluated with the real 113 million transactions from 14 million accounts between 7M-th and 8M-th blocks in ethereum. Our experimental result shows that ethanos can reduce the size of the account state by half, which, if combined with removing old transactions, may reduce the storage size for bootstrapping to around 1GB. This would be reasonable enough for ordinary clients to bootstrap on their personal devices.
Blockchain systems (more precisely Distributed Ledger Technologies (DLTs)) represent a different digital ecosystem compared with traditional computer systems. One major difference are the performance and scalability factors which will be discussed and analytically investigated in this paper. In doing so, we provide guidance for defining a research agenda focusing on the investigation of the crucial role of scalability for blockchain systems. System performance -- measured in terms of (1) consensus response time (blockchain network latency or time to convergence/agreement); (2) number of transactions per second or throughput, and (3) computing (and power) resources consumed -- can be understood by considering the design dimensions of a blockchain system, namely: (i) the type of blockchain system needed from a requirements perspective which in turn determines; (ii) the complexity of the consensus protocol used; (iii) the topography of the traffic flow on the network; (iv) the performance and complexity of the domain-specific language that implements smart contracts; and (v) by the anticipated growth in size and complexity of the distributed ledger itself.
Modern Blockchains support the execution of user programs, called smart contracts. As a trusted computing platform, smart contracts bring decentralization, computation integrity, open access and information transparency to average users on the Internet. However, running smart-contract programs leads to high costs, known as Gas. Such costs prevent the use of smart contracts in data-intensive application scenarios, such as high-frequency trading and transparency logging. This paper addresses the Gas-based cost effectiveness in the most consuming layer of a smart contract, namely data storage. We present GRuB, a dynamic data-replication framework that monitors the smart-contract workload and makes online replication decisions. A new online algorithm is proposed that provides constant-bounded 'competitiveness' in Gas. To further save Gas, the workload monitor and decision maker are run off the Blockchain and with security against the forging of workload trace being monitored. A GRuB prototype is built, including a smart-contract component on Ethereum and an off-chain middleware on top of Google LevelDB. The cost evaluation under the YCSB workloads shows that GRuB can converge quickly to changing workloads and save Gas significantly compared with static replication schemes. Two case studies are conducted for data-intensive applications, including high-frequency trading and transparency logging, in which running GRuB leads to affordable Gas.
Feeding external data to a blockchain, a.k.a. data feed, is an essential task to enable blockchain interoperability and support emerging cross-domain applications, notably stablecoins. Given the data-intensive feeds in real life (e.g., high-frequency price updates) and the high cost in using blockchain, namely Gas, it is imperative to reduce the Gas cost of data feeds. Motivated by the constant-changing workloads in finance and other applications, this work focuses on designing a dynamic, workload-aware approach for cost effectiveness in Gas. This design space is understudied in the existing blockchain research which has so far focused on static data placement. This work presents GRuB, a cost-effective data feed that dynamically replicates data between the blockchain and an off-chain cloud storage. GRuB's data replication is workload-adaptive by monitoring the current workload and making online decisions w.r.t. data replication. A series of online algorithms are proposed that achieve the bounded worst-case cost in blockchain's Gas. GRuB runs the decision-making components on the untrusted cloud off-chain for lower Gas costs, and employs a security protocol to authenticate the data transferred between the blockchain and cloud. The overall GRuB system can autonomously achieve low Gas costs with changing workloads. We built a GRuB prototype functional with Ethereum and Google LevelDB, and supported real applications in stablecoins. Under real workloads collected from the Ethereum contract-call history and mixed workloads of YCSB, we systematically evaluate GRuB's cost which shows a saving of Gas by 10% ~ 74%, with comparison to the baselines of static data-placement.
Christoph Egger, Pedro Moreno-Sánchez, Matteo Maffei
Current cryptocurrencies provide a heavily limited transaction throughput that is clearly insufficient to cater their growing adoption. Payment-channel networks (PCNs) have emerged as an interesting solution to the scalability issue and are currently deployed by popular cryptocurrencies such as Bitcoin and Ethereum. While PCNs do increase the transaction throughput by processing payments off-chain and using the blockchain only as a dispute arbitrator, they unfortunately require high collateral (i.e., they lock coins for a non-constant time along the payment path) and are restricted to payments in a path from sender to receiver. These issues have severe consequences in practice. The high collateral enables denial-of-service attacks that hamper the throughput and utility of the PCN. Moreover, the limited functionality hinders the applicability of current PCNs in many important application scenarios. Unfortunately, current proposals do not solve either of these issues, or they require Turing-complete language support, which severely limit their applicability.
The recent surge in blockchain applications and database systems has renewed the interest in traditional Byzantine Fault Tolerant consensus protocols (BFT). Several such BFT protocols follow a primary-backup design, in which a primary} replica coordinates the consensus protocol. In primary-backup designs, the normal-case operations are rather simple. At the same time, primary-backup designs place an unreasonable burden on primaries and allows malicious primaries to affect the system throughput substantially, however. To resolve this situation, we propose the MultiBFT paradigm, a protocol-agnostic approach towards improving the performance of primary-backup consensus protocols. At the core of MultiBFT is an approach to continuously order the client-transactions by running several instances of the underlying BFT protocol in parallel. We bring forth our paradigm to two well-established BFT protocols and demonstrate that the rendered parallelized protocols are not only safe and live but also significantly outperform, up to $2\times$, their original non-parallelized forms. Further, we show that our MultiBFT paradigm reaches a throughput of up to $320$K transactions per second.
FastChain is a simulator built in NS-3 which simulates the networked battlefield scenario with military applications, connecting tankers, soldiers and drones to form Internet-of-Battlefield-Things (IoBT). Computing, storage and communication resources in IoBT are limited during certain situations in IoBT. Under these circumstances, these resources should be carefully combined to handle the task to accomplish the mission. FastChain simulator uses Sharding approach to provide an efficient solution to combine resources of IoBT devices by identifying the correct and the best set of IoBT devices for a given scenario. Then, the set of IoBT devices for a given scenario collaborate together for sharding enabled Blockchain technology. Interested researchers, policy makers and developers can download and use the FastChain simulator to design, develop and evaluate blockchain enabled IoBT scenarios that helps make robust and trustworthy informed decisions in mission-critical IoBT environment.
In blockchain ecosystems, an Oracle is a service tool which provides real-world data for smart contracts and other blockchain applications. At present, there are several Oracle implementation schemes, e.g. centralized Oracles, decentralized Oracles, and hardware Oracles. However, these schemes typically suffer from single source of data and low scalability. Application Specific Knowledge Engine (ASKE) is an integrated topic/application-centered knowledge portal that supports effective information retrieval and analysis. Inspired by ASKE, in this paper, we propose a novel Oracle implementation scheme. The proposed scheme can realize multi-source data extraction and analysis, then working prototypes are demonstrated to show the validity of the scheme.
As a distributed system, blockchain is currently an attractive choice for the back-end of public services because of its benefits. Decentralized and carries a consensus mechanism making data stored into irreversible ledger is an advantage of the blockchain. This study discusses the architecture design of academic recording systems in Indonesia, which is currently centralized to be decentralized in permitted networks. Participants involved in the network system, namely institutions as academic staff, teachers, students, and external parties, which each participant has the authority and arrangement with smart-contracts. Evaluation results show less time on the proposed system to complete business processes than the currently system. The task of validation activities can be eliminated and perform smart-contract functions inside to become a "trust-less operation", in which academic data are ensured to be protected from abused or damage due to human error. The data that has been included in the ledger consists of personal performance from the history of academic activities required by students that can be traced by interested parties such as organizations wishing to recruit employees, as well as educational institutions that require the achievement of specific information needed by prospective applicants.
Abstract We have implemented a blockchain system based on Ethereum for use by a university to store student grades and to provide a cryptocurrency. Based upon an exploratory, qualitative evaluation we have found several tensions between the concept of a university as an organization and the concept of distributed autonomous organizations (DAOs) in Ethereum. These include tensions in (i) mechanisms of trust, (ii) boundaries of openness and (iii) values in procedures. In this article we outline our implementation and the evaluation process.
Non-governmental organizations (NGO) depend on their members to survive. They need to reach the potential volunteers. They also aspire to keep track of their members' effectiveness and to motivate those members to be more active. The volunteers need a transparent system, where their privacy is preserved. Our meetings with several NGOs show that there is a solid need for a transparent, effective and trustworthy system, where NGOs can track their members' effectiveness, create enthusiasm and even collaborate with the volunteers from other NGOs. A system, where gamification principles are used for member motivation and the reputation of any member is calculated by his/her activities, is proposed. The blockchain technology will be used for the gamification process and the decentralized digital identity management. The decentralized digital identity management approach will help in providing the volunteers to gain full control over their identities and ensure the privacy. A design approach for the proposed system, the expected requirements and some possible use case scenarios have been presented. The prototype is implemented via Hyperledger Fabric and Hyperledger Indy software platforms, as a proof of concept. Chaincodes are to be implemented for the system to work autonomously.
Abstract Blockchain and blockchain‐based decentralised applications have been attracting increasing attention recently. In public blockchain systems, users usually connect to third‐party peers or run a peer to join the P2P blockchain network. However, connecting to unreliable blockchain peers will lead to resource waste and even loss of cryptocurrencies by repeated transactions. In order to select reliable blockchain peers, it is urgently needed to evaluate and predict their reliability of them. Faced with this problem, we propose hybrid blockchain reliability prediction (H‐BRP), a Hybrid Blockchain Reliability Prediction model, to extract the blockchain reliability factors and then make the personalised prediction for each user. Comprehensive experiments conducted on 100 blockchain requesters and 200 blockchain peers demonstrate the effectiveness of the proposed H‐BRP model. Further, the implementation and dataset of 2,000,000 test cases are released.
ABSTRACT In this research, we often refer to Nakamoto's (2008) seminal paper, “Bitcoin: A Peer-to-Peer Electronic Cash System,” to consider his proposed abstracted characteristics and how auditors could look at companies' transactions interfacing to a private/semi-private blockchain with Nakamoto's general characteristics and address the related audit domain for such transactions. We then take these design requirements for auditors and, using design science research (DSR), we consider the transaction processing and contracting contexts that match those requirements in permissioned blockchains.The blockchains discussed in this paper would typically be business-to-business or business-to-consumer, private or semi-private, and residing in either a private, semi-private, or public cloud. Those blockchains will each have their own design and operational procedures, including validation procedures (the miners). We consider the audit issues of data reliability, data security, and transaction transparency in accounting transactions that lend themselves to a permissioned blockchain as well as other contextual issues.