IEEE Organizations related to Energy-efficient Fog Computing

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Conferences related to Energy-efficient Fog Computing

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No conferences are currently tagged "Energy-efficient Fog Computing"


Periodicals related to Energy-efficient Fog Computing

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Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Selected Areas in Communications, IEEE Journal on

All telecommunications, including telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space, and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; communication theory; and wireless communications.



Most published Xplore authors for Energy-efficient Fog Computing

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Xplore Articles related to Energy-efficient Fog Computing

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Distributed Optimization for Energy-Efficient Fog Computing in the Tactile Internet

IEEE Journal on Selected Areas in Communications, 2018

Tactile Internet is an emerging concept that focuses on supporting high- fidelity, ultra-responsive, and widely available human-to-machine interactions. To reduce the transmission latency and alleviate Internet congestion, fog computing has been advocated as an important component of the Tactile Internet. In this paper, we focus on an energy-efficient design of fog computing networks that support low-latency Tactile Internet applications. We ...



Educational Resources on Energy-efficient Fog Computing

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IEEE.tv Videos

An Energy-efficient Reconfigurable Nanophotonic Computing Architecture Design: Optical Lookup Table - IEEE Rebooting Computing 2017
Energy Efficient Single Flux Quantum Based Neuromorphic Computing - IEEE Rebooting Computing 2017
An Energy-Efficient Mixed-Signal Neuron for Inherently Error Resilient Neuromorphic Systems - IEEE Rebooting Computing 2017
Synchronised 4-Phase Resonant Power Clock Supply for Energy Efficient Adiabatic Logic: IEEE Rebooting Computing 2017
Fog Computing in Energy and Environment Panel - Fog World Congress 2017
Fog Computing Design Principles for Industrial IoT Applications - Sudhanshu Gaur, Fog World Congress 2017
Steep Slope Devices: Advanced Nanodevices - Nicolo Oliva at INC 2019
IoT: Next 20 Years Panel - Igor Stolichnov for Adrian Ionescu at INC 2019
This is Fog - Mung Chiang - Fog World Congress 2018
Standards In Fog Computing - Tao Zhang and John Zao, Fog World Congress 2018
Cisco's Anuj Jain on Fog Computing
Superconductive Energy-Efficient Computing - ASC-2014 Plenary-series - 6 of 13 - Wednesday 2014/8/13
FinSAL: A Novel FinFET Based Secure Adiabatic Logic for Energy-Efficient and DPA Resistant IoT Devices - Himanshu Thapliyal: 2016 International Conference on Rebooting Computing
Take It To the Fog Tank: Fog World Congress 2018
Fog Computing on the Horizon - Fog World Congress
Fog Computing Test Bed: Cutting Costs and Latency in Data Transmission - Fog World Congress
Vertical Markets of Fog Computing - Fog World Congress 2018
Opportunities in Physical Computing driven by Analog Realization - Jennifer Hasler: 2016 International Conference on Rebooting Computing
NGD Systems Pitch: Fog Tank - Fog World Congress
Building IoT Projects Faster - Ed Hemphill at Fog World Congress 2018

IEEE-USA E-Books

  • Distributed Optimization for Energy-Efficient Fog Computing in the Tactile Internet

    Tactile Internet is an emerging concept that focuses on supporting high- fidelity, ultra-responsive, and widely available human-to-machine interactions. To reduce the transmission latency and alleviate Internet congestion, fog computing has been advocated as an important component of the Tactile Internet. In this paper, we focus on an energy-efficient design of fog computing networks that support low-latency Tactile Internet applications. We investigate two performance metrics: Service response time of end-users and power usage efficiency of fog nodes. We quantify the fundamental tradeoff between these two metrics and then extend our analysis to fog computing networks involving cooperation between fog nodes. We introduce a novel cooperative fog computing concept, referred to as offload forwarding, in which a set of fog nodes with different computing and energy resources can cooperate with each other. The objective of this cooperation is to balance the workload processed by different fog nodes, further reduce the service response time, and improve the efficiency of power usage. We develop a distributed optimization framework based on dual decomposition to achieve the optimal tradeoff. Our framework does not require fog nodes to disclose their private information nor conduct back-and-forth negotiations with each other. Two distributed optimization algorithms are proposed. One is based on the subgradient method with dual decomposition and the other is based on distributed alternating direction method of multipliers via variable splitting. We prove that both algorithms can achieve the optimal workload allocation that minimizes the response time under the given power efficiency constraints of fog nodes. Finally, to evaluate the performance of our proposed concept, we simulate a possible implementation of a city-wide self-driving bus system supported by fog computing in the city of Dublin. The fog computing network topology is set based on a real cellular network infrastructure involving 200 base stations deployed by a major cellular operator in Ireland. Numerical results show that our proposed framework can balance the power usage efficiency among fog nodes and reduce the service latency for users by around 50% in urban scenarios.



Standards related to Energy-efficient Fog Computing

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No standards are currently tagged "Energy-efficient Fog Computing"


Jobs related to Energy-efficient Fog Computing

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