Gossip and Epidemic Protocols

Montresor, Alberto

doi:10.1002/047134608x.w8353

Cited by 12 publications

(4 citation statements)

References 28 publications

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“…In biology, nodes are distributed in space, lack unique identifiers, and often lack mechanisms to provide precise, node-to-node feedback [ 84 ]. These constraints introduce new challenges for optimization that are reminiscent of those faced in stone-age computing protocols [ 85 ] and gossip protocols (also known as epidemic protocols) [ 86 , 87 ], where information is passed between users in a decentralized manner. Understanding how to deal with outdated, missing or erroneous feedback under these protocols is an area of active research.…”

Section: Discussionmentioning

confidence: 99%

A feedback control principle common to several biological and engineered systems

Suen

Navlakha

2022

J. R. Soc. Interface.

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Feedback control is used by many distributed systems to optimize behaviour. Traditional feedback control algorithms spend significant resources to constantly sense and stabilize a continuous control variable of interest, such as vehicle speed for implementing cruise control, or body temperature for maintaining homeostasis. By contrast, discrete-event feedback (e.g. a server acknowledging when data are successfully transmitted, or a brief antennal interaction when an ant returns to the nest after successful foraging) can reduce costs associated with monitoring a continuous variable; however, optimizing behaviour in this setting requires alternative strategies. Here, we studied parallels between discrete-event feedback control strategies in biological and engineered systems. We found that two common engineering rules—additive-increase, upon positive feedback, and multiplicative-decrease, upon negative feedback, and multiplicative-increase multiplicative-decrease—are used by diverse biological systems, including for regulating foraging by harvester ant colonies, for maintaining cell-size homeostasis, and for synaptic learning and adaptation in neural circuits. These rules support several goals of these systems, including optimizing efficiency (i.e. using all available resources); splitting resources fairly among cooperating agents, or conversely, acquiring resources quickly among competing agents; and minimizing the latency of responses, especially when conditions change. We hypothesize that theoretical frameworks from distributed computing may offer new ways to analyse adaptation behaviour of biology systems, and in return, biological strategies may inspire new algorithms for discrete-event feedback control in engineering.

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Section: Discussionmentioning

confidence: 99%

A feedback control principle common to several biological and engineered systems

Suen

Navlakha

2022

J. R. Soc. Interface.

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“…The Stellar protocol [95] is a well-known representative of this class of protocols. With Stellar, each node independently selects a set of trusted nodes (e.g., trusted because of neighboring relationships) sets its own quorum threshold, then, applying a recursive principle of message passing and quorum overlapping, consensus can be achieved with a gossip protocol [96] in the whole federated network. Gossip protocols normally require to work in cycles to guarantee convergence, introducing once more the problem of asynchronous networks.…”

Section: Voting Based Protocolsmentioning

confidence: 99%

What is a Blockchain? A Definition to Clarify the Role of the Blockchain in the Internet of Things

Ghiro¹,

Restuccia²,

Basagni³

et al. 2021

Preprint

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The use of the term blockchain is documented for disparate projects, from cryptocurrencies to applications for the Internet of Things (IoT), and many more. The concept of blockchain appears therefore blurred, as it is hard to believe that the same technology can empower applications that have extremely different requirements and exhibit dissimilar performance and security. This position paper elaborates on the theory of distributed systems to advance a clear definition of blockchain that allows us to clarify its role in the IoT. This definition inextricably binds together three elements that, as a whole, provide the blockchain with those unique features that distinguish it from other distributed ledger technologies: immutability, transparency and anonimity. We note however that immutability comes at the expense of remarkable resource consumption, transparency demands no confidentiality and anonymity prevents user identification and registration. This is in stark contrast to the requirements of most IoT applications that are made up of resource constrained devices, whose data need to be kept confidential and users to be clearly known. Building on the proposed definition, we derive new guidelines for selecting the proper distributed ledger technology depending on application requirements and trust models, identifying common pitfalls leading to improper applications of the blockchain. We finally indicate a feasible role of the blockchain for the IoT: myriads of local, IoT transactions can be aggregated off-chain and then be successfully recorded on an external blockchain as a means of public accountability when required.

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“…Originally introduced by Ormándi et al [1], gossip learning is an asynchronous protocol designed to train a global model over decentralized data using a gossip communication approach [4]. Its simplicity, flexibility and efficiency make it an interesting starting point for the development of nextgeneration decentralized machine learning systems.…”

Section: The Gossip Learning Protocolmentioning

confidence: 99%

“…To deal with data-dependent heterogeneous speeds, pullbased gossip communications [4] represent an alternative to the protocol extension presented in this paper. In pull-based gossip, nodes do not push messages to their neighbours.…”

Section: Related Workmentioning

confidence: 99%

Gossip Learning: Off the Beaten Path

Giaretta

Girdzijauskas

2019

2019 IEEE International Conference on Big Data (Big Data)

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The growing computational demands of model training tasks and the increased privacy awareness of consumers call for the development of new techniques in the area of machine learning. Fully decentralized approaches have been proposed, but are still in early research stages. This study analyses gossip learning, one of these state-of-the-art decentralized machine learning protocols, which promises high scalability and privacy preservation, with the goal of assessing its applicability to realworld scenarios.Previous research on gossip learning presents strong and often unrealistic assumptions on the distribution of the data, the communication speeds of the devices and the connectivity among them. Our results show that lifting these requirements can, in certain scenarios, lead to slow convergence of the protocol or even unfair bias in the produced models. This paper identifies the conditions in which gossip learning can and cannot be applied, and introduces extensions that mitigate some of its limitations.

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Gossip and Epidemic Protocols

Cited by 12 publications

References 28 publications

A feedback control principle common to several biological and engineered systems

A feedback control principle common to several biological and engineered systems

What is a Blockchain? A Definition to Clarify the Role of the Blockchain in the Internet of Things

Gossip Learning: Off the Beaten Path

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