Fog Computing May Help to Save Energy in Cloud Computing

By Fatemeh Jalali, Kerry Hinton, Robert W. A. Ayre, Tansu Alpcan, Rodney S. Tucker. IEEE Journal on Selected Areas in Communications, 2016

375 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/963a273144727fb1acec3c434ee00afbca9646f4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

In Information Systems

Citations in the corpus

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges (2017, background): “Oueis et al. [82], Nishio et al. [83], Sarkar et al. [105], [106], Jalali et al. [107], and Cao et al. [108] have analyzed and assessed energy consumption in the overall system.”
Fog computing security: a review of current applications and security solutions (2017, methodology): “Saving energy in Cloud computing As Cloud operations require large amount of continuous energy, different types of applications are investigated in [87] using Raspberry Pi based servers, which can be installed and configured as a Fog platform to reduce energy consumption.”
Edge Computing in the Industrial Internet of Things Environment: Software-Defined-Networks-Based Edge-Cloud Interplay (2018, background): “[7] presented a comparative study of energy consumption of nDCs and centralized DCs.”
Securing Fog Computing for Internet of Things Applications: Challenges and Solutions (2018, methodology): “The cloud receives data summaries from various fog nodes, and performs global analysis on the data submitted by fog nodes and the data from other sources to improve business insight in IoT applications [8], such as smart power distribution [54], health status monitoring [33] and network resource opt”
Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers (2018, background): “identified scenarios in which running applications n nano servers used in fog are more efficient than running the ame applications on centralized data centers [51,99] .”
All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey (2018, background): “identify applications that are more energy-efficient when implemented on nano data centers than centralized data centers [23].”
Survey on fog computing: architecture, key technologies, applications and open issues (2017, methodology): “Jalali et al. (2016) proposed and adopted flow-based and time-based energy consumption models to compared the energy consumption of a service provided by using nano data centers (nDCs) used in fog computing with using centralized data centers (DCs) in cloud computing.”
Survey of Fog Computing: Fundamental, Network Applications, and Research Challenges (2018, background): “1) Selection of Energy Efficient Applications: As suggested in [104], nDCs can be useful for fog computing, authors investigated what type of applications are more energy efficient while running in nDCs rather than centralized DCs.”
Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study (2017, methodology): “, 2016 [78] They compared the energy consumption of applications by using centralized clouds with applications that use nano data centers.”
IoT in the Fog: A Roadmap for Data-Centric IoT Development (2018, background): “On the other hand, recent research on the energy footprint of cloud architectures, especially as data centers are ever growing in their power demands [11], is offering new insights into the potential gain as we migrate IoT operation to the network edge under a broad view of fog networks.”
Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges (2019, methodology): “Software-level efficiency optimization techniques and algorithms (like Mobile Edge-Computing offloading in [77] ), backed by simulation models [78] have been developed.”
Fog Computing: A Taxonomy, Survey and Future Directions (2016, background): “As a consequence energy consumption in Cloud datacentres will be miniized that eventually ensures proper power management for Cloud datacentres (Jalali et al. [18]).”
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications (2017, methodology): “The energy consumption of applications using central data centers (DCs) in cloud computing and those using nano data centers in fog computing is compared in [49].”
Mobile Edge Computing: A Survey (2018, background): “In 2016, Jalali et al. [83] proposed a ﬂow-based and time-based energy consumption model.”