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Enregistrement W3047761112 · doi:10.1002/nem.2133

Editorial for special issue on “challenges and opportunities of Blockchain and Cryptocurrency”

2020· article· en· W3047761112 sur OpenAlex
Hongtaek Ju, Raouf Boutaba, Myung‐Sup Kim, Burkhard Stiller

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Notice bibliographique

RevueInternational Journal of Network Management · 2020
Typearticle
Langueen
DomaineComputer Science
ThématiqueBlockchain Technology Applications and Security
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésCryptocurrencyBlockchainComputer scienceData scienceComputer security

Résumé

récupéré en direct d'OpenAlex

Even though several blockchain and cryptocurrency analytic and processing systems have been introduced with various design and network architectures, we are still lacking a deeper understanding of the characteristics and the performance of each of the various design architectures. There exists a crucial need to conduct fundamental research with a comprehensive performance evaluation for the various blockchain and cryptocurrency systems and architectures. This special issue showcases original results and achievements by researchers, designers, and developers working on various issues and challenges related to blockchains and cryptocurrencies. For this special issue, the best papers of the 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC, 2019, https://icbc2019.ieee-icbc.org/) were invited and extended before submission to this special issue. After a rigorous peer-review process, we decided to accept five papers. These papers cover a wide range of topics, including blockchain distributed network property analysis, blockchain-based applications, blockchain performance, and scalability issues. In the first contribution entitled “Bitcoin's Dynamic Peer-To-Peer Topology,” Essaid et al introduce a new topology discovery system that performs a real-time data collection and analysis for Bitcoin P2P links, which assembles incoming nodes information for deeper graph analysis processing. Their results show that the Bitcoin P2P topology stands firmly on Super-Nodes (17.8% of the Bitcoin nodes) and the network has more community structures compared with what should be expected from a random graph network. They also show how the use of sophisticated internet filtering and censorship systems affect the propagation time and nodes' connectivity within the Bitcoin network. In the second contribution entitled “Incentives in Ethereum's Hybrid Casper Protocol,” Buterin et al analyze the hybrid Casper FFG contract. The authors describe the Casper FFG core mechanism and show that its incentives scheme ensures liveness while providing security against the finalization of conflicting histories focusing on checkpoints. Their study and implementation of the Casper FFG contract highlighted two main issues: (a) the “finder's fee” for detecting a violator of slashing conditions may create conflicting incentives and competition between validators; (b) in the case that the network experiences a large partition or fork, honest validators who have voted and finalized on the noncanonical chain will sustain heavy losses to return to the main chain. In the third paper entitled “Weighted Voting on the Blockchain: Improving Consensus in Proof of Stake Protocols,” Leonardos et al presents a modified version of the Ethereum PoS consensus protocol. The PoS protocol proposes to weight the consensus power of nodes not just by their staked deposits but also by their voting history. For example, if nodes regularly fail to vote for blocks on the main chain in a timely manner, these nodes' voting power is reduced. This increases the throughput, because offline nodes are less likely to be elected as block proposers, which means that less time is wasted. In contrast, no new data is added to these blocks and the processing power required for clients to update these voting profiles is negligible. Furthermore, attack resistance is improved as attackers, who seek to harm liveness by not voting (correctly), rapidly lose consensus power. In the subsequent contribution entitled “Blockchain-Based Access Control for Enterprise Blockchain Applications,” Xu et al propose a decentralized ledger-based access control (DAcc), which mitigates data confidentiality and privacy issues when adopting decentralized ledger technology for enterprise applications through a novel combination of cryptographic tools and Smart Contracts to make it compatible with the decentralized environment. The authors implement a prototype on top of Hyperledger Fabric that uses HDFS as the storage system to demonstrate the efficiency of the DAcc design. Experimental results show that with optimization techniques, the underlying decentralized ledger platform can support more than 2,000 transactions per second compared to the default setup of Hyperledger Fabric. In the fifth paper entitled “FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second,” Gorenflo et al also show how Hyperledger can be optimized for high transaction throughput. The authors suggest the following four main optimizations: (1) to remove from the ordering service transaction data and only keep metadata that is relevant for a transaction validation, (2) parallelization and caching of endorsement and validation peers, (3) caching of the state database using an in-memory approach, and (4) splitting of endorser and committer roles to different peers. By adopting these additional optimizations, the authors achieve an increase in transaction throughput, which is seven times higher than a default Hyperledger setup. The team of guest editors would like to take this opportunity to thank Professor James Won-Ki Hong (Editor-in-Chief of the International Journal on Network Management) for providing the opportunity to publish this special issue. We would also like to thank the reviewers who devoted much of their precious time and expertise evaluating the submitted papers. Finally, we hope that the readers will enjoy this selection of papers as we did and find them informative and helpful in keeping themselves up to date in the fast-changing area of blockchain and cryptocurrency.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,831
Score d'incertitude au seuil0,267

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,035
Tête enseignante GPT0,266
Écart entre enseignants0,231 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle