A Survey on Auction based Approaches for Resource Allocation and Pricing in Emerging Edge Technologies

Kumar, Dinesh; Baranwal, Gaurav; Vidyarthi, Deo Prakash

doi:10.1007/s10723-021-09593-9

Cited by 10 publications

(3 citation statements)

References 166 publications

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“…Agents can cooperate with each other. For example, if the existing computing platform is overloaded, the overloaded tasks can be migrated to the idle platform [39]. Definition The agent is a triple tuple: AGENT = ( TASK , MS , sess ), where: TASK ( execT , rR , relations , transParents ) is the set of tasks, which is the deployed by agent for microservice; MS = ( type , tR , BW , ratio ).…”

Section: Reliability Requirement Of Cloud Computingmentioning

confidence: 99%

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Reliability modelling and optimization for microservice‐based cloud application using multi‐agent system

Liu

Fan

et al. 2022

IET Communications

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In the process of the continuous development of the Internet of Things, cloud computing has been applied in many fields, how to guarantee the quality of service, such as low latency, high bandwidth, high reliability etc., has become a challenging problem. This paper proposes a method to model and optimize reliability for microservice‐based cloud applications using multi‐agent system (MAS), thus maximizing the reliability of cloud computing and dynamically scheduling microservices to minimize the delay within the budget. Firstly, a dynamic microservice scheduling scheme is proposed to provide efficient computing services by using MAS. A hierarchical cloud computing model is formed by predicated Petri net (PrT net) and the properties of constructed model are analysed. Secondly, agents have been utilized to describe the essential characteristics of microservice scheduling process in the cloud applications. The partial critical path (PCP) aims to maximize the reliability of cloud applications under the limitation of budget and meet the user‐defined deadline. Finally, the proposed PCPRO algorithm has been applied to cloud environment, which is suitable for different scientific workflows in the cloud computing environment. The effectiveness of this method is verified by simulation, the experiment results show the effectiveness of the proposed method.

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Section: Reliability Requirement Of Cloud Computingmentioning

confidence: 99%

“…Agents can cooperate with each other. For example, if the existing computing platform is overloaded, the overloaded tasks can be migrated to the idle platform [39]. Definition 3.…”

Section: Reliability Requirement Of Cloud Computingmentioning

confidence: 99%

Reliability modelling and optimization for microservice‐based cloud application using multi‐agent system

Liu

Fan

et al. 2022

IET Communications

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“…Other survey works on blockchain-based auctioning for trading energy include [12], [13]. Furthermore, resource allocation in edge computing has been surveyed [14], [15]. However, as far as we are aware, no surveys have been conducted on non-blockchain decentralized auctioning systems for physical assets.…”

Section: Introductionmentioning

confidence: 99%

Survey on Decentralized Auctioning Systems

2023

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An electronic auction (e-auction) is an efficient negotiation model that allows multiple sellers or buyers to compete for assets or rights. Such systems have become increasingly popular with the evolution of the internet for commerce. In centralized auctioning systems, the presence of a governing third party has been a major trust concern, as such a party may not always be trustworthy or create transaction fees for the hosted auctions. Distributed and decentralized systems based on blockchain for auctions of nonphysical assets have been suggested as a means to distribute and establish trust among peers, and manage disputes and concurrent entries. Although a blockchain system provides attractive features such as decentralized trust management and fraud prevention, it cannot alone support dispute resolutions and adjudications for physical assets. In this paper, we compare blockchain and non-blockchain decentralized auctioning systems based on the identified functional needs and quality attributes. We contrast these needs and attributes with the stateof-the-art models and other implementations of auctioning systems, and discuss the associated trade-offs. We further analyze the gaps in the existing decentralized approaches and propose design approaches for decentralized auctioning systems, for both physical and nonphysical assets, that support dispute resolution and adjudication based on collected evidence, and dispute prevention based on distributed consensus algorithms.

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