Energy Efficient Scheduling and Management for Large-Scale Services Computing Systems

Chen, Ying; Chen, Lin; Huang, Jiwei; Xiang, Xudong; Shen, Xuemin

doi:10.1109/tsc.2015.2444845

Cited by 35 publications

(7 citation statements)

References 32 publications

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“…Applied at the hardware level, DPM technology seeks to dynamically reconfigure devices for developing techniques to fulfil the required facilities with a limited count of active components or a minimal load [111][112][113][114][115][116]. The hardware-level DPM strategies [20] can selectively disable idle device components or reduce the output of slightly unexploited components.…”

Section: Hardware-level Solutionsmentioning

confidence: 99%

“…The primary threats to our SMS's validity originate from the unintentional contradictions involved while reviewing the literature [1-111], selecting the primary study, evaluating the quality assessment, and extracting data from the selected studies. Including the conclusion and internal and external threats, we followed the threat description given by [112] to discuss those constraints and the steps taken to mitigate these threats [113][114][115][116][117][118][119][120][121].…”

Section: Threats To Validitymentioning

confidence: 99%

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A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing

et al. 2022

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Global warming is one of the most compelling environmental threats today, as the rise in energy consumption and CO2 emission caused a dreadful impact on our environment. The data centers, computing devices, network equipment, etc., consume vast amounts of energy that the thermal power plants mainly generate. Primarily fossil fuels like coal and oils are used for energy generation in these power plants that induce various environmental problems such as global warming ozone layer depletion, which can even become the cause of premature deaths of living beings. The recent research trend has shifted towards optimizing energy consumption and green fields since the world recognized the importance of these concepts. This paper aims to conduct a complete systematic mapping analysis on the impact of high energy consumption in cloud data centers and its effect on the environment. To answer the research questions identified in this paper, one hundred nineteen primary studies published until February 2022 were considered and further categorized. Some new developments in green cloud computing and the taxonomy of various energy efficiency techniques used in data centers have also been discussed. It includes techniques like VM Virtualization and Consolidation, Power-aware, Bio-inspired methods, Thermal-management techniques, and an effort to evaluate the cloud data center’s role in reducing energy consumption and CO2 footprints. Most of the researchers proposed software level techniques as with these techniques, massive infrastructures are not required as compared with hardware techniques, and it is less prone to failure and faults. Also, we disclose some dominant problems and provide suggestions for future enhancements in green computing.

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Section: Hardware-level Solutionsmentioning

confidence: 99%

Section: Threats To Validitymentioning

confidence: 99%

A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing

et al. 2022

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“…In the study [11] the three approaches including DVFS, request dispatching, and dynamic service management are joined so as to reduce the energy consumption. Yet, the limitation is that these researchers have admitted that the servers providing different services are active all the time.…”

Section: Related Work On Green Cloud Computingmentioning

confidence: 99%

Green Cloud Computing: Efficient Energy-Aware and Dynamic Resources Management in Data Centers

Diouani¹,

Medromi²

2018

ijacsa

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Abstract-The users of Cloud computing over the last years are constantly increasing since it has become a very important technology in the computing landscape. It provides client decentralized services and a pay-as-you-go model for consuming resources. The growing need for the cloud services oblige the providers to adopt an enlarged sized data center infrastructure which runs thousands of hosts and servers to store and process data. As a result, these large servers engender a lot of heat with visual carbon emission in the air, as well as important energy consumption and higher operating cost. This is why researches in energy economics continue to progress including energy saving techniques in servers, in the network, cooling, and renewable energies, etc. In this paper, we tackled the existing energy efficient methods in the green cloud computing fields and we put forward our green cloud solution for data center dynamic resource management. Our proposed approach aims to reduce the infrastructure energy consumption and maintain the required performances.

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“…Chen and Lin [13] describe service computing system as a group of interacting IT services that not only focus on the technology of service computing and IT infrastructures but also pay attention to the performance of the IT services (such as QoS, service discovery). Moreover, Ye et al [14] describe service computing system as a complex system that consists of various services that can be consumed by users by integrating individual services into composite services to meet the complex requirements of users. Based on the definitions above, it can be summarized that service computing system is a service system enabled by service computing technology, meaning this system focuses on the enablement of the concept of service systems through the model, technology, architecture and optimization & analysis.…”

Section: Service Computing Systemsmentioning

confidence: 99%

“…Complex systems, Service composition, Requirements [14] Encapsulation of IT service systems and services (in a welldefined architecture) with largescale computing infrastructures…”

Section: Scs (Its)mentioning

confidence: 99%

Service Computing System Engineering Life Cycle

Suhardi

Kurniawan

Sembiring

2017

EECSI

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The development of service computing technology has triggered the need for organizations to build a service computing system. This system is able to deliver IT services that can meet the challenges and needs of business services. An understanding of the service computing systems engineering life cycle is necessary to model and build the systems. This paper conducts the study of the service computing systems concepts and proposes the life cycle of service computing system engineering. First, some publications relevant to the service computing systems are reviewed systematically in order to develop fundamental concepts and elements of the systems. Second, a metamodel of service computing systems is built based on those concepts. Third, the life cycle model of service computing systems engineering is proposed based on the metamodel. Finally, the verification of the life cycle is conducted by comparing the proposed life cycle to the life cycle of software engineering, service engineering, and service system engineering. The contribution of this paper is to provide a coincise understanding of the components that are needed to build such systems and show the interaction and collaboration between the components in the service computing systems.

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Energy Efficient Scheduling and Management for Large-Scale Services Computing Systems

Cited by 35 publications

References 32 publications

A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing

A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing

Green Cloud Computing: Efficient Energy-Aware and Dynamic Resources Management in Data Centers

Service Computing System Engineering Life Cycle

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