Resource-utilization-aware energy efficient server consolidation algorithm for green computing in IIOT

Han, Guangjie; Que, Wenhui; Jia, Gangyong; Zhang, Wenbo

doi:10.1016/j.jnca.2017.07.011

Cited by 42 publications

(27 citation statements)

References 21 publications

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“…14) Energy Management: Energy management for the IIoT and WSANs has naturally received significant attention, as in many cases the devices operate on limited battery supplies (Table VIII). On the IIoT part, there have been energy efficient improvements on QoS-aware services composition [372] (similarly for the ICPS [386]), robust authentication protocols [392], routing and data collection [393], [394], as well as resource allocation and utilization [395] (similarly for the ICPS [398]). On the backbone of the IIoT networks, in the cases where Ethernet is used as an enabler, energy efficiency has also been a timely topic [375].…”

Section: Computation and Data Analytics Articlesmentioning

confidence: 99%

“…IIoT / ICPS [372], [386], [392], [393], [366], [367], [375], [394], [395], [398] WSAN [369]- [371], [377], [396], [373], [374], [376], [378], [379], [381] NCS -Industrial Robots [384] Assembly Line [62], [364], [365], [383], [385], [387], [6], [388]- [391], [399] M2M Communication [368], [397] whole toward minimizing energy consumption is proposed in [384]. Dynamic low-power reconfiguration [364] and machine energy consumption minimization [365] are key objectives of novel assembly lines.…”

Section: Data Enabling Technology Articles On Energy Managementmentioning

confidence: 99%

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Data Management in Industry 4.0: State of the Art and Open Challenges

2019

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Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Secondly, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances on industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this article thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field as well as the industrial, manufacturing and automation field. The article can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.

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Section: Computation and Data Analytics Articlesmentioning

confidence: 99%

Section: Data Enabling Technology Articles On Energy Managementmentioning

confidence: 99%

Data Management in Industry 4.0: State of the Art and Open Challenges

2019

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“…An unbalanced PM is more sensitive to workload changes in such a way that with the increase in the workload, the chances of PM moving to overload state increases. Based on this, Han et al considered computing the average difference of utilized RAM and utilized CPU and comparing them with a static threshold as a solution for detection of unbalanced PM focusing on CPU and RAM resources.…”

Section: Review Of Server Consolidation Techniquesmentioning

confidence: 99%

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

2018

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Summary At the virtualized data centers, services are presented by active virtual machines (VMs) in physical machines (PMs). The manner in which VMs are mapped to PMs affects the performance of data centers and the energy efficiency. By employing the server consolidation technique, it is possible to configure the VMs on a smaller number of PMs, while the quality of service is guaranteed. In this way, the rate of active PM utilization increases and fewer active PMs would be required. Moreover, the server consolidation technique reacts to the management of underloaded and overloaded PMs by using the VM migration technology. Considering the capabilities of the server consolidation technique and its role in developing the cloud computing infrastructure, many researches have been conducted in this context. Still, a comprehensive and systematic study has not yet been performed on various consolidation techniques to check the capabilities, advantages, and disadvantages of current approaches. In this paper, a systematic study is conducted on a number of credible researches related to server consolidation techniques. In order to do so and by studying the selected works, proposed solutions are categorized based on the type of decision for running the consolidation algorithm in 4 groups of static method, dynamic method, prediction‐based dynamic method, and hybrid method. Thereafter, the advantages and disadvantages of suggested approaches are studied and compared in each research by specifying the technique and idea applied therein. In addition, by categorizing aims of researches and specifying assessment parameters, optimization approaches and type of architecture, a possibility has been provided to get familiarized with the views of the researchers.

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“…For verification, the verifier will simply check the equality of the equation (ℎ( ), V)? ( , ) [24][25][26][27][28][29]. If the equation holds, the verifier will believe that the BLS-based homomorphic authenticator is valid; otherwise, the validity of the authenticator cannot be proved.…”

Section: Preliminariesmentioning

confidence: 99%

Cloud Based Data Protection in Anonymously Controlled SDN

Shen

Lai

et al. 2018

Security and Communication Networks

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Nowadays, Software Defined Network (SDN) develops rapidly for its novel structure which separates the control plane and the data plane of network devices. Many researchers devoted themselves to the study of such a special network. However, some limitations restrict the development of SDN. On the one hand, the single controller in the conventional model bears all threats, and the corruption of it will result in network paralysis. On the other hand, the data will be increasing more in SDN switches in the data plane, while the storage space of these switches is limited. In order to solve the mentioned issues, we propose two corresponding protocols in this paper. Specifically, one is an anonymous protocol in the control plane, and the other is a verifiable outsourcing protocol in the data plane. The evaluation indicates that our protocol is correct, secure, and efficient.

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Resource-utilization-aware energy efficient server consolidation algorithm for green computing in IIOT

Cited by 42 publications

References 21 publications

Data Management in Industry 4.0: State of the Art and Open Challenges

Data Management in Industry 4.0: State of the Art and Open Challenges

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

Cloud Based Data Protection in Anonymously Controlled SDN

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