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Greening emerging IT technologies: techniques and practices
2017
Journal of Internet Services and Applications
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"Green Computing" paradigm advocates the energy-proportional and efficient usage of computing resources in all emerging technologies, such as Big Data and Internet of Things (IoT). ...
Further, we discuss the imminent challenges facing the efficient green operations of emerging IT technologies. ...
transfer Power
source
Life-time Greening strategies
RFID
Active tags
Two ways
Low
Battery
≤ 5
Energy-efficient algorithms and protocols
Passive tags
One way
Very low
Harvested ∞
Sensing ...
doi:10.1186/s13174-017-0060-5
fatcat:q7y7e4ypojconoajznoii3ngna
Energy-Efficient Big Data Analytics in Datacenters
[chapter]
2016
Advances in Computers
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We later discuss the techniques for improving energy efficiency in the cloud-based datacenters for big data analytics. ...
Highly virtualized cloud-based datacenters are currently considered for big data analytics. ...
Complexity: Big data complexity needs to use many algorithms to process data quickly and efficiently. ...
doi:10.1016/bs.adcom.2015.10.002
fatcat:xpecmdmje5avvphkdrdnyv4fqi
Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study
2018
Complexity
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Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. ...
The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. ...
A traditional power system database is designed to store structured data files using tables; thus, the size of storage is limited and the data operation efficiency is low. ...
doi:10.1155/2018/8496187
fatcat:2esxs54ixjbx7ijvct7hbffyji
Rethinking Abstractions for Big Data: Why, Where, How, and What
[article]
2013
arXiv
pre-print
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either oversimplify or require low-level management of details. ...
Big data refers to large and complex data sets that, under existing approaches, exceed the capacity and capability of current compute platforms, systems software, analytical tools and human understanding ...
The clear conclusion is that, regardless of the specific application-level abstractions used for computation on big data, there will be common needs for both resiliency and power efficiency; this points ...
arXiv:1306.3295v1
fatcat:oevth47mszev3jm7nd2nxxhrda
Big Data Analytics for Dynamic Energy Management in Smart Grids
2015
Big Data Research
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Hence, robust data analytics, high performance computing, efficient data network management, and cloud computing techniques are critical towards the optimized operation of SGs. ...
The smart electricity grid enables a two-way flow of power and data between suppliers and consumers in order to facilitate the power flow optimization in terms of economic efficiency, reliability and sustainability ...
Acknowledgement This work was supported by the project of "Scalable Real-Time Load Forecasting in Smart Grid" under a grant from the Khalifa University Internal Research Fund (KUIRF-Level 2; Fund # 210063 ...
doi:10.1016/j.bdr.2015.03.003
fatcat:2rz5wct5djfjhcec6xic5rnd3i
A survey on comparative study of solar energy on Improving the performance of solar power plants through IOT and predictive data analytics
2016
IOSR Journal of Computer Engineering
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In this paper we present a comparative study to improve the performance of solar power plants through IOT and predictive analytics. ...
In order to enhance and improve the performance, we need to do preventive maintenance of solar power plant by implementing Operation & Maintenance (O&M) activities using predictive analytics and supervisory ...
If the good analytic system is setup then a very efficient Solar analytics system could be built at a very low cost and at a very high efficiency rate. ...
doi:10.9790/0661-1805025860
fatcat:dyz4wdjafvaupgozajx6a6z4uq
Big data analytics in smart grids: a review
2018
Energy Informatics
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This paper introduces the big data analytics and corresponding applications in smart grids. ...
data analytics in smart grids. ...
The secure and efficient power system operation relays on the data assessment and state estimation. ...
doi:10.1186/s42162-018-0007-5
fatcat:j3hrytmzzfbmjnqh5msybplhc4
Exascale computing and big data
2015
Communications of the ACM
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The developer writes the application using high-level primitives a compiler will transform into efficient low-level code to optimize the performance on the underlying platform. ...
Software and algorithmic challenges. Many of the software and algorithmic challenges for advanced computing and big-data analytics are themselves consequences of extreme system scale. ...
The global information technology ecosystem is in flux, with the transition to a new generation of low-power mobile devices, cloud services, and rich data analytics; and Private and global research. ...
doi:10.1145/2699414
fatcat:d3lyhp4hyveefoq4y3ganonqiu
A Survey Work on Optimization Techniques Utilizing Map Reduce Framework in Hadoop Cluster
2017
International Journal of Intelligent Systems and Applications
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Data is one of the most important and vital aspect of different activities in today's world. Therefore vast amount of data is generated in each and every second. ...
Moderate
Moderate
Low
High
Big Data Application-Level Optimization Transfers
through Pipelining, Parallelism and Concurrency. ...
Big Data Application-Level Optimization Transfers through Pipelining, Parallelism and Concurrency. ...
doi:10.5815/ijisa.2017.04.07
fatcat:pf5wyatfyrcovkifjezaydhzxe
Enterprise Performance Management following Big Data Analysis Technology under Multisource Information Fusion
2021
Security and Communication Networks
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The study aims to explore the performance management of power enterprises based on multisource information fusion and big data. ...
The evaluation result is closer to the actual value than other algorithms, and the maximum acceleration ratio can reach 7, indicating that the algorithm is suitable for processing big data. ...
of the research is that a management fusion model is implemented through the multisource information fusion method and big data. ...
doi:10.1155/2021/7915670
fatcat:e3fzqjqzprb2rby7fi5hn6hfh4
A Review on Big Data Management and Decision-Making in Smart Grid
2019
Power Electronics and Drives
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Such useful information obtained by the so-called data analytics is an essential element for energy management and control decision towards improving energy security, efficiency, and decreasing costs of ...
Big Data process enables benefits that were never achieved for the SG application. ...
Predictive analytics have a great impact on SG through improving power distribution reliability by achieving continuity of the power and reducing power outages. ...
doi:10.2478/pead-2019-0011
fatcat:a7lp6yhatzgunjiyfy65vi536y
Parallel processing on Big Data in the context of Machine Learning and Hadoop Ecosystem: A Survey
2018
International Journal of Engineering & Technology
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Emergent Big Data applications have become gradually more essential. ...
It provides not only a worldwide sight of most important Big Data technologies but also relationship according to special organizational, classifications levels such as Information Storage Level, Information ...
Big Data has a complex nature that requires powerful technologies and advanced algorithms. ...
doi:10.14419/ijet.v7i2.7.10885
fatcat:goyvvzlwsbeifi62nrldkgp3yy
A Review on Big Data Analytics for Energy Efficiency, Conservation and Management in Energy Intensive Manufacturing Industries
2020
International Journal for Research in Applied Science and Engineering Technology
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The paper reviews on understanding of Energy Big Data; "5V" ...
The power of MapReduce using Apache Hadoop ecosystem tools to present an end-to-end Big Data analytics tool. ...
or through optimization of process and ensuring the use within the best operating zones. ...
doi:10.22214/ijraset.2020.31657
fatcat:wy3whmhxsnf63fmc3tt5ny3eqm
Big Data in the Energy and Transport Sectors
[chapter]
2016
New Horizons for a Data-Driven Economy
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A mere deployment of existing big data technologies as used by the big data natives will not be sufficient. ...
Domain-specific big data technologies are necessary in the cyber-physical systems for energy and transport. ...
The new market segments are diversified through big data energy start-ups like Next: Kraftwerke, who "merge data from various sources such as operational data from our virtual power plant, current weather ...
doi:10.1007/978-3-319-21569-3_13
fatcat:cdtbrbm2mngizalaagewxyayk4
Plug-in Electric Vehicle to Cloud Data Analytics for Charging Management
2017
International Journal of Engineering and Technology
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The heterogeneous data generated from these devices roots the use of efficient data management techniques to deliver a consistent, reliable and real time operation of the massive vehicle fleet [3] . ...
Smart grid technologies in collaboration with smart charging management strategies may circumvent the power load, thus enabling a reliable, efficient, consistent and flexible operation of the underlying ...
They also hire the development environment or platform through Platform as a Service (PaaS) servicing strategies and execute their data analytics algorithms. ...
doi:10.21817/ijet/2017/v9i3/170903s056
fatcat:6c3konyo6rb5rjofa54246smsq
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