P2P Techniques for Decentralized Applications

Pacitti, Esther; Akbarinia, Reza; El-Dick, Manal

doi:10.1007/978-3-031-01888-6

Cited by 3 publications

(1 citation statement)

References 129 publications

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“…Decentralized Applications (dApps): dApps are applications that run on a P2P network of computers rather than a single computer [36]. They interact with the blockchain and smart contracts to perform their functions.…”

Section: Understanding Decentralization and Large Language Modelsmentioning

confidence: 99%

Decentralised Autonomous Society Through Large Language Models’ Based Agents: A Pathway to Empower Small Communities

Braga

2023

J. Eng. Sci.

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This paper explores the concept of Decentralized Autonomous Society through the lens of Large Language Models focusing on the transformative potential of integrating these technologies. The paper on the role of Large Language Models based agents in providing a versatile, responsive, and contextually intelligent resource within a Decentralized Autonomous Society, fostering intellectual exploration, assisting in complex tasks, and aiding real-time problem solving. One delves into their integration with Decentralized Autonomous Society infrastructures, including robotic and automated systems. While promising, the integration of Large Language Models and their agents into a Decentralized Autonomous Society poses several challenges, including infrastructure and connectivity limitations, information accuracy, artificial intelligence bias, privacy and data security, and ethical concerns. This paper critically discusses these issues and proposes potential solutions. Through the lens of the Decentralized Autonomous Society construct, the paper considers the future possibilities and implications of artificial intelligence, where self-sustaining, digitally-empowered communities leverage artificial intelligence as a cornerstone of their collective intelligence.

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Section: Understanding Decentralization and Large Language Modelsmentioning

confidence: 99%

Decentralised Autonomous Society Through Large Language Models’ Based Agents: A Pathway to Empower Small Communities

Braga

2023

J. Eng. Sci.

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Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud

Liu

Pacitti

Valduriez

et al. 2017

Transactions on Large-Scale Data- And Knowledge-Centered Systems XXXIII

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Abstract. Recently, some Scientific Workflow Management Systems (SWfMSs) with provenance support (e.g. Chiron) have been deployed in the cloud. However, they typically use a single cloud site. In this paper, we consider a multisite cloud, where the data and computing resources are distributed at different sites (possibly in different regions). Based on a multisite architecture of SWfMS, i.e. multisite Chiron, and its provenance model, we propose a multisite task scheduling algorithm that considers the time to generate provenance data. We performed an extensive experimental evaluation of our algorithm using Microsoft Azure multisite cloud and two real-life scientific workflows (Buzz and Montage). The results show that our scheduling algorithm is up to 49.6% better than baseline algorithms in terms of total execution time.

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Bonus Points Alliance Based on the Block Chain

Chen

Sun

et al. 2018

2018 14th International Conference on Semantics, Knowledge and Grids (SKG)

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P2P Techniques for Decentralized Applications

Cited by 3 publications

References 129 publications

Decentralised Autonomous Society Through Large Language Models’ Based Agents: A Pathway to Empower Small Communities

Decentralised Autonomous Society Through Large Language Models’ Based Agents: A Pathway to Empower Small Communities

Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud

Bonus Points Alliance Based on the Block Chain

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