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Future Of Money
The present increase of attention toward blockchain-based systems is currently reaching a tipping point with the corporate focus shifting from exploring the technology potential to creating Distributed Ledger Technology (DLT)-based systems. In light of a significant number of already existing blockchain applications driven by the Internet of Things (IoT) evolution, the developers are still facing a lack of tools and instruments for appropriate and efficient performance evaluation and behavior observation of different blockchain architectures. This paper aims at providing a systematic review of current blockchain evaluation approaches and at identifying the corresponding utilization challenges and limitations. First, we outline the main metrics related to the blockchain evaluation. Second, we propose the blockchain modeling and analysis classification based on the critical literature review. Third, we extend the review with publicly accessible industrial tools. Next, we analyze the selected results for each of the proposed classes and outline the corresponding limitations. Finally, we identify current challenges of the blockchain analysis from the system evaluation perspective, as well as provide future perspectives.
Historically, blockchain systems were designed to support the data immutability among different decentralized nodes [1]. This niche of distributed systems development had already obtained a significant impact on business, touching upon all industries in the world as part of the Distributed Ledger Technology (DLT) paradigm [2]. Today’s blockchain technology applications vary from public means of record-keeping and private storage [3] to connecting various heterogeneous devices as part of the Internet of Things (IoT) paradigm [4]. Moreover, IBM researchers forecast that the DLT market based on blockchain is expected to reach $60.7 billion by 2024 [5], highlighting the timeliness of the systems’ integration needs. The tendency of the blockchain systems’ adoption could be found in almost any digitalized industry, forcing companies to prepare to profit from the blockchain technology integration [6].
Deloitte’s Global Blockchain Survey highlighted that the perception of the blockchain is presently reaching the point of no return, with the corporate focus shifting from exploring the technology potential to creating production business applications [7]. As one of the leading blockchain integration drivers, the financial sector accounted for more than 60% of the global blockchain market value in 2018 [8]. Since then, other industries have been cautious about finding use cases to ensure a good return of investment by implementing blockchain-based applications due to their extreme complexity compared to conventional centralized systems. As a result, more and more entities in more and more spheres, for instance, the biological sciences, media, government agencies, communications, agriculture, and healthcare are broadening and developing their blockchain initiatives to keep up with the pace of the technological evolution [9, 10].
Web3, Blockchain & Cryptocurrency Jobs
Given the enormous interest in blockchain-based solutions, the number of startups is increasing yearly in both private and public sectors [11, 12]. From the very beginning of the blockchain era, blockchain-related investments increased from about a million U.S. dollars in 2012 to more than one billion in 2017 [13], currently breaking the line of $23.7 billion [14]. A representative example is the blockchain protocol EOS, which has engendered a significant investment of $4.2 billion in its initial coin placement [15]. While the United States is presently considered a leader in the blockchain segment [16], it is also expected that China will be able to achieve this position in the coming years. One of the central reasons is that China’s investments in blockchain technology are almost doubling each year [17].
A recent survey of business leaders in Europe [16] showed that almost 50% of them expected the blockchain to be added to their current operating business model. Moreover, another 33% claimed they expected the blockchain to be entirely replaced by their current operating model. About 66% of global companies expressed a moderate level of interest in blockchain technology, with almost 10% currently in the process of conducting experiments or implementing blockchain solutions [18].
Cryptocurrencies, and more specifically, Bitcoin, tend to be some of the first and central applications of the broadly known blockchain paradigm, receiving much more attention than other blockchain use cases. As of the third quarter of 2019, Bitcoin reached a high market capitalization of $205.4 billion U.S. dollars [19]. While Bitcoin could be considered the largest, some other cryptocurrencies such as Ethereum, Ripple, and Litecoin have also gained a significant market share in 2019 [20]. Many believe that blockchain and its use in cryptocurrency technology will allow shifting from traditional money transactions to digital ones supported by means of secure ledgers in the coming years.
Popular Nft Use Cases
As a result of the deep blockchain systems’ penetration into our everyday lives, the number of distributed node interactions is expected to increase significantly [21], bringing more load to the energy grid [22], as well as infrastructure and peer-to-peer (P2P) networks and storage volumes [23]. While the field of conventional infrastructure-like (cloud) communication analysis and predictability is already a well-studied topic, the impact of new networking paradigms, such as fog and edge [24, 25], is expected to bring a new level of system complexity both from communications and computing perspectives. Therefore, blockchains provide some unique differences from everything that has come before. A blockchain survives faults and attacks by the use of redundant checking of multiple nodes. This resiliency goes far beyond replication since it happens across the network without any central coordinator or intermediary [26]. Generally, the design of said distributed systems requires careful planning and performance evaluation, while conventional approaches may face numerous challenges due to the increase in the complexity.
To date, there is still a lack of unified tools and instruments for the performance evaluation and behavior observation of blockchains, while the number of related applications is already sky high [27]. Blind development of blockchain-based extraordinarily complex and dynamic systems without any preliminary performance evaluation may have a tremendous negative impact during the actual deployment phase. In most cases, current evaluation approaches are based on the emulation techniques that imitate and replicate the behavior of the entire network. Evidently, it requires a significant amount of computational, storage, and communications resources [28, 29]. Little attention is also given to deploying real testnets driven by the community, but it requires significant incentivization activities to get the users involved [30, 31]. Consequently, the emulation entails a massive problem of scalability for real-world deployments’ evaluation [32]. Moreover, such an evaluation requires considerable engineering efforts to modify complicated open-source solutions or production systems to test out continually evolving systems in a timely manner. In this case, modeling approaches, for instance, analytical and simulation methods, can be considered as an alternative trading precision for the evaluation speed.
This paper also aims at future prospects of blockchain simulation/modeling approaches, as well as at surveying existing solutions utilized for blockchain systems’ performance evaluation. It aims to provide an overview of existing strategies found in the literature, as well as in open access sources in order to provide the linkage between the approach and solved task or its general area.
Big Industries Blockchain Could Transform
The rest of the paper is organized as follows. The next section provides the applied critical review methodology. Section 3 highlights the main background information, as well as the motivation of this paper. Section 4 outlines the examples of the most widely used approaches applicable to blockchain evaluation and related classification. Next, Section 5 covers the main analytical and simulation tools used for blockchain evaluation. Section 6 outlines the main emulation-based approaches used by industry and integrators. Next, Section 7 lists the main challenges related to the blockchain evaluation from both execution and legal perspectives. It also provides recommendations on the future improvement of the modeling process. The last section concludes the paper.
In order to identify the key publications on the evaluation of blockchain technology, we performed a literature search in scientific databases following PRISMA guidelines [33] with minor modifications. The analysis covered leading computer science journals and conferences: IEEE Xplore, ACM Digital Library, ScienceDirect, SAGE Journals Online, Springer Link, etc. To find relevant articles and papers for our research, we applied the following search string: (Blockchain OR “Distributed Ledger”) AND (Simulation
As a result of the deep blockchain systems’ penetration into our everyday lives, the number of distributed node interactions is expected to increase significantly [21], bringing more load to the energy grid [22], as well as infrastructure and peer-to-peer (P2P) networks and storage volumes [23]. While the field of conventional infrastructure-like (cloud) communication analysis and predictability is already a well-studied topic, the impact of new networking paradigms, such as fog and edge [24, 25], is expected to bring a new level of system complexity both from communications and computing perspectives. Therefore, blockchains provide some unique differences from everything that has come before. A blockchain survives faults and attacks by the use of redundant checking of multiple nodes. This resiliency goes far beyond replication since it happens across the network without any central coordinator or intermediary [26]. Generally, the design of said distributed systems requires careful planning and performance evaluation, while conventional approaches may face numerous challenges due to the increase in the complexity.
To date, there is still a lack of unified tools and instruments for the performance evaluation and behavior observation of blockchains, while the number of related applications is already sky high [27]. Blind development of blockchain-based extraordinarily complex and dynamic systems without any preliminary performance evaluation may have a tremendous negative impact during the actual deployment phase. In most cases, current evaluation approaches are based on the emulation techniques that imitate and replicate the behavior of the entire network. Evidently, it requires a significant amount of computational, storage, and communications resources [28, 29]. Little attention is also given to deploying real testnets driven by the community, but it requires significant incentivization activities to get the users involved [30, 31]. Consequently, the emulation entails a massive problem of scalability for real-world deployments’ evaluation [32]. Moreover, such an evaluation requires considerable engineering efforts to modify complicated open-source solutions or production systems to test out continually evolving systems in a timely manner. In this case, modeling approaches, for instance, analytical and simulation methods, can be considered as an alternative trading precision for the evaluation speed.
This paper also aims at future prospects of blockchain simulation/modeling approaches, as well as at surveying existing solutions utilized for blockchain systems’ performance evaluation. It aims to provide an overview of existing strategies found in the literature, as well as in open access sources in order to provide the linkage between the approach and solved task or its general area.
Big Industries Blockchain Could Transform
The rest of the paper is organized as follows. The next section provides the applied critical review methodology. Section 3 highlights the main background information, as well as the motivation of this paper. Section 4 outlines the examples of the most widely used approaches applicable to blockchain evaluation and related classification. Next, Section 5 covers the main analytical and simulation tools used for blockchain evaluation. Section 6 outlines the main emulation-based approaches used by industry and integrators. Next, Section 7 lists the main challenges related to the blockchain evaluation from both execution and legal perspectives. It also provides recommendations on the future improvement of the modeling process. The last section concludes the paper.
In order to identify the key publications on the evaluation of blockchain technology, we performed a literature search in scientific databases following PRISMA guidelines [33] with minor modifications. The analysis covered leading computer science journals and conferences: IEEE Xplore, ACM Digital Library, ScienceDirect, SAGE Journals Online, Springer Link, etc. To find relevant articles and papers for our research, we applied the following search string: (Blockchain OR “Distributed Ledger”) AND (Simulation
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