Delivering Data Mining Services in Cloud Computing

Parra-Royon, Manuel; Benitez, Jose M.

doi:10.1109/services.2019.00121

Cited by 4 publications

(1 citation statement)

References 1 publication

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“…The power of cloud computing and the massive scale of big data have made the success of artificial intelligence (AI) [1], [2], in a manner of high performance computing and high power consumption. However, with the emergence of edge computing [3] and the rise of green Internet of Things (IoT) technology [4], the core of AI is gradually sinking from the cloud to the user's closer end [5].…”

Section: Introductionmentioning

confidence: 99%

A Novel Emotion Control System for Embedded Human–Computer Interaction in Green Iot

Gong

Lin

2019

IEEE Access

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The green Internet of Things (IoT) technology has increased the need for a more emotion-connected human-computer interaction. The lower network latency and longer battery life ensure the continuous and real-time work of human-computer interaction systems in embedded environments. However, the lack of emotional dynamics limits the empathy capability of human-computer interactions. In this paper, we propose a novel emotion control system for embedded human-computer interaction in green IoT. The Van Der Pol emotional dynamics with nonlinear resilience is proposed for the modeling of human emotional mechanisms. Moreover, respectively for the autonomous and stochastic-excitation situation, we analyze the stability of the solution, based on which four kinds of the emotional health status are defined. Finally, we obtain the steady-state solution and design its feedback controller. Results of the numerical simulation and prototype demonstrate the validity and practical operability of the theory.

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Section: Introductionmentioning

confidence: 99%

A Novel Emotion Control System for Embedded Human–Computer Interaction in Green Iot

Gong

Lin

2019

IEEE Access

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An Energy-Aware Multi-Target Service Composition Method in a Multi-Cloud Environment

Yin

Hao

2020

IEEE Access

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Service composition is always employed to enhance function by composing atomic services that reside in different clouds together. In a multi-cloud environment (MCE), the time and energy consumption of service composition may differ because of the dynamic of the network. The network varies between clouds, or even between composite requests and clouds. A cloud provides a limited variety of services, which makes a composite request that requires multiple clouds to jointly compose all atomic services together. All of this makes it more difficult than ever to implement energy-aware service composite in a MCE. In this paper, we model service composition in the MCE and propose an energy-aware multiple targets service composition method for executing atomic services in a composite request. Since the proposed method gets the scheduling by searching all possible mappings between service request blocks (a set of requests to multiple atomic services) and clouds, we call it "All-Search". To reduce the complexity of All-Search, we propose "Itersplit", a heuristics algorithm that can achieve multiple targets. The performance of All-Search, Cloud-SEnergy, and Itersplit is tested through simulations. The results in multiple aspects indicate that Itersplit performs better than other algorithms when we take Itersplit-20%.

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Improving Security and Sharing Management in Cloud Computing Using TPA

Ismail

Hasan

2019

2019 1st AL-Noor International Conference for Science and Technology (NICST)

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Delivering Data Mining Services in Cloud Computing

Cited by 4 publications

References 1 publication

A Novel Emotion Control System for Embedded Human–Computer Interaction in Green Iot

A Novel Emotion Control System for Embedded Human–Computer Interaction in Green Iot

An Energy-Aware Multi-Target Service Composition Method in a Multi-Cloud Environment

Improving Security and Sharing Management in Cloud Computing Using TPA

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