Increasing data availability and fault tolerance for decentralized collaborative data-sharing systems

Abstract

In order to realize collaboration on a global scale, academic research requires often large quantities of data to be shared between geographically dispersed organizations. The requirement to protect and govern data in a network of loosely coupled, autonomous institutions is an incentive for decentralized solutions, where the participants are in full control of their data without trusting a third-party provider to store and process the data. In order to increase data availability and fault tolerance in decentralized collaborative systems, we propose a layer, which is based on replication and decentralized authority over the data. The solution consists of an idea of peer-sets, which are groups of peers implementing collective data management, a consensus protocol which synchronizes a distributed ledger between peers, and an atomic commitment protocol used to implement optional two-way references between documents. This architecture may be utilized in various decentralized collaborative data-sharing systems, such as Onedata.

A Data Intrusion Tolerance Model Based on an Improved Evolutionary Game Theory for the Energy Internet

“…Khan et al [27] developed a Byzantine fault-tolerant system designed to provide "as-a-service" intrusion tolerance that ensures local data confidentiality. Jarosz et al [28] proposed a decentralized data management solution for institutional data autonomy by enhancing data availability and fault tolerance through peer sets and consensus mechanisms. Zhu et al [29] presented a fault-tolerant PDP protocol for cloud storage that detects and repairs data by using cuckoo filters and Reed-Solomon codes to ensure security and utility.…”