Providing Virtual Cloud for Special Purposes on Demand in JointCloud Computing Environment

Cao, Donggang; An, Bo; Shi, Peichang; Wang, Huaimin

doi:10.1007/s11390-017-1715-1

Cited by 16 publications

(3 citation statements)

References 17 publications

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“…To overcome the issues associated with multiple clouds, Cao et al 19 deployed a Joint Cloud Computing (JCC). The main aim of the JCC is to minimize the issues associated with multiple clouds by providing the users with virtual cloud resources.…”

Section: Review Of Related Workmentioning

confidence: 99%

H2RUN: An efficient vendor lock‐in solution for multi‐cloud environment using horse herd Runge Kutta based data placement optimization

Kumar

Mala

2022

Trans Emerging Tel Tech

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Vendor lock‐in is a scenario where the cost of switching to another vendor is mainly high and for this reason, the consumer is mainly struck with a single cloud vendor. The vendor lock‐in mainly implies the situation of an organization where it is locked into a service or product of a single Cloud Service Providers (CSP) to prevent the disruption of the business operation or due to an insufficient workforce. Due to its high availability, portability, and other benefits, various researchers frequently adopt the multi‐cloud strategy to prevent vendor lock‐in. However, the multi‐cloud architecture also comes with major drawbacks such as cost, multiple CSP management, and the tradeoff between cost and availability. The organizations are mainly considerate about achieving the tradeoff between the cost and availability. To overcome this problem, we have proposed an H2RUN (Horse Herd Runge Kutta) optimization algorithm to achieve a tradeoff between the cost and availability using erasure coding. The proposed H2RUN optimization algorithm selects the optimal CSP and erasure coding parameters that enhance the availability of the CSP with minimal cost. The efficiency of the proposed methodology can be evaluated using the experiments conducted on different real‐time CSPs using various metrics. Based on the results achieved, the H2RUN optimizer minimizes the cost up to 48% and availability up to 58%.

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Section: Review Of Related Workmentioning

confidence: 99%

H2RUN: An efficient vendor lock‐in solution for multi‐cloud environment using horse herd Runge Kutta based data placement optimization

Kumar

Mala

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…More and more convenient and intelligent applications based on data science techniques such as big data analytics also catch people's attention 1 . At the same time, the development of cloud computing has attracted interest by enabling ICV to use the reliable and accurate applications provided by cloud server 2 . In ICVs, massive sensors data need to be processed with the cooperation of central server to provide comfortable driving experience for drivers 3 .…”

Section: Introductionmentioning

confidence: 99%

“…1 At the same time, the development of cloud computing has attracted interest by enabling ICV to use the reliable and accurate applications provided by cloud server. 2 In ICVs, massive sensors data need to be processed with the cooperation of central server to provide comfortable driving experience for drivers. 3 However, security and privacy issues are raised during the transmission of sensor data to central server.…”

Section: Introductionmentioning

confidence: 99%

A participant selection based vehicle platoon asynchronous federated learning framework

Liang

Feng

Zhao

et al. 2023

Trans Emerging Tel Tech

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In the vehicular network, federated learning is an emerging paradigm to train deep learning models safely. However, the non‐identically independent distributed data collected by intelligent connected vehicles, expensive training overhead, and the existence of malicious participants significantly affect the efficiency of training and constrain the development of federated learning in the vehicular network. To address the above issues, this paper proposes a participant selection‐based asynchronous federated learning framework for an intelligent connected vehicle platoon. We proposed a platoon‐based asynchronous federated learning framework that effectively improves training efficiency through data share and asynchronous optimization. Also, We designed a signaling game‐based participant selection strategy that accurately identifies the potentially malicious participants by analyzing the Perfect Bayesian Equilibrium. The comparison experiment result shows the training model using our proposed scheme converges faster than the baseline scheme and gains approximately 10% higher accuracy.

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TZ-Container: protecting container from untrusted OS with ARM TrustZone

Hua

Yu²,

et al. 2021

Sci. China Inf. Sci.

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Providing Virtual Cloud for Special Purposes on Demand in JointCloud Computing Environment

Cited by 16 publications

References 17 publications

H2RUN: An efficient vendor lock‐in solution for multi‐cloud environment using horse herd Runge Kutta based data placement optimization

H2RUN: An efficient vendor lock‐in solution for multi‐cloud environment using horse herd Runge Kutta based data placement optimization

A participant selection based vehicle platoon asynchronous federated learning framework

TZ-Container: protecting container from untrusted OS with ARM TrustZone

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