ChainFL: A Simulation Platform for Joint Federated Learning and Blockchain in Edge/Cloud Computing Environments

Qu, Guanjin; Cui, Naichuan; Wu, Huaming; Li, Ruidong; Ding, Yuemin

doi:10.1109/tii.2021.3117481

Cited by 35 publications

(7 citation statements)

References 28 publications

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“…A simulation platform is proposed in Reference 137 which connects individual devices building an edge computing environment which also provides compatibility to Blockchain and Federated Learning algorithms and technologies. It is a five layer platform which is Infrastructure layer (contains the major infrastructure of the system such as IOT devices, edge base stations), Virtualization Layer (adaptability to virtual machines), Communication Layer (all kinds of communication between edge devices and server), Computing Layer (computations in the system such as aggregation of local parameters) and the Application Layer (accountable for edge computing deployed devices).…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence‐based blockchain solutions for intelligent healthcare: A comprehensive review on privacy preserving techniques

Gami,

Agrawal,

Mishra

et al. 2023

Trans Emerging Tel Tech

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While blockchain technology (BT) is considered secure, there are several vulnerabilities that can breach its security. The study in artificial intelligence (AI) and BT is widely popular due to its expanding importance in enhancing security and computational prowess. In this study, we present a comprehensive and meticulous comprehensive review of AI and BT‐based privacy‐preserving smart healthcare. The selection for this study was based on a holistic and integrated approach which involved examining not only individual studies but also their relationships, and trends. Through a systematic analysis of various phases, we identified 91 primary studies pertaining to information needed to stockpile directions called for retorting the research queries. We have undertaken a descriptive comparison of foundational manuscripts, taking into account an array of essential factors, including performance metrics, security protocols, and computational prowess. Our thorough discussions and debates have led to the identification of research gaps in the current manuscript, as well as the direction for future research. We also propose our constructive approach for the aforementioned integration, highlighting its potential benefits and implications.

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Section: Resultsmentioning

confidence: 99%

Artificial intelligence‐based blockchain solutions for intelligent healthcare: A comprehensive review on privacy preserving techniques

Gami,

Agrawal,

Mishra

et al. 2023

Trans Emerging Tel Tech

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“…This integration is particularly significant in applications where blockchain's decentralized and immutable nature can strengthen data integrity and trust in distributed IoT networks. Simulators such as ChainFL 41 and xFogSim, 42 can be adapted to simulate such scenarios, providing valuable insights into the resource management challenges and opportunities inherent in B‐IoT systems. Conversely, the key characteristic of the modeling toolkit is capturing the behaviors of the actual entities and modeling them as an object or agents, then simulating the actual interactions among different entities through events.…”

Section: Related Workmentioning

confidence: 99%

iQuantum: A toolkit for modeling and simulation of quantum computing environments

Nguyen,

Usman,

Buyya

2024

Softw Pract Exp

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SummaryQuantum computing resources are predominantly accessible through cloud services, with a potential future shift to edge networks. This paradigm and the increasing global interest in quantum computing have amplified the need for efficient, adaptable resource management strategies and service models for quantum systems. However, many limitations in the quantum resources' quantity, quality, availability, and cost pose significant challenges for conducting research in practical environments. To address these challenges, we proposed iQuantum, a holistic and lightweight discrete‐event simulation toolkit uniquely tailored to model hybrid quantum computing environments. We also present a detailed system model for prototyping and problem formulation in quantum resource management. Through rigorous empirical validation and evaluations using large‐scale quantum workload datasets, we demonstrate the flexibility and applicability of our toolkit in various use cases. iQuantum provides a versatile environment for designing and evaluating quantum resource management policies such as quantum task scheduling, backend selection, hybrid task offloading, and orchestration in the quantum cloud‐edge continuum. Our work endeavors to create substantial contributions to quantum computing modeling and simulation, empowering the creation of future resource management strategies and quantum computing's broader applications.

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“…Off-loading as a popular methodology to alleviate the stress of edge nodes is to move computation task to external machines, such as Edge Computing Service Provider (ESP) or Cloud Computing Service Provider (CSP) [134] . Those service providers that are qualified to conduct the off-loaded tasks may earn some profit or reward for providing computation service.…”

Section: Blockchain For Off-loading In Edge Computingmentioning

confidence: 99%

“…Jiang et al [134] designed a multi-leader multifollower Stackelberg game to address computing resource management and maximized profits of service providers and the rewards of miners in the network. Hu et al [136] detailed a blockchain-enabled edge computing system, and proposed a deep reinforcement learning algorithm to jointly optimize the computation offloading policy and block generation strategy to maximize the scalability.…”

Section: Blockchain For Off-loading In Edge Computingmentioning

confidence: 99%

Recent Advances of Blockchain and Its Applications

2022

J. Soc. Comput.

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Blockchain is an emerging decentralized data collection, sharing, and storage technology, which have provided abundant transparent, secure, tamper-proof, secure, and robust ledger services for various realworld use cases. Recent years have witnessed notable developments of blockchain technology itself as well as blockchain-enabled applications. Most existing surveys limit the scopes on several particular issues of blockchain or applications, which are hard to depict the general picture of current giant blockchain ecosystem.In this paper, we investigate recent advances of both blockchain technology and its most active research topics in real-world applications. We first review the recent developments of consensus and storage mechanisms and communication schema in general blockchain systems. Then extensive literature review is conducted on blockchain-enabled Internet of Things (IoT), edge computing, federated learning, and several emerging applications including healthcare, COVID-19 pandemic, online social network, and supply chain, where detailed specific research topics are discussed in each. Finally, we discuss the future directions, challenges, and opportunities in both academia and industry.

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ChainFL: A Simulation Platform for Joint Federated Learning and Blockchain in Edge/Cloud Computing Environments

Cited by 35 publications

References 28 publications

Artificial intelligence‐based blockchain solutions for intelligent healthcare: A comprehensive review on privacy preserving techniques

Artificial intelligence‐based blockchain solutions for intelligent healthcare: A comprehensive review on privacy preserving techniques

iQuantum: A toolkit for modeling and simulation of quantum computing environments

Recent Advances of Blockchain and Its Applications

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