Data Management in Fog Computing

Nikoui, Tina Samizadeh; Rahmani, Amir Masoud; Tabarsaied, Hooman

doi:10.1002/9781119525080.ch8

Cited by 16 publications

(9 citation statements)

References 24 publications

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“…IoT and cloud-based healthcare systems have enabled easy communication between patients and clinicians, leading to increased patient participation and satisfaction [ 7 ]. Additionally, remote monitoring systems can reduce hospital stays and prevent readmissions, which in turn lowers healthcare expenditures while improving treatment outcomes [ 42 ]. As a result, there has been a surge in the number of IoT and cloud-based healthcare applications in recent years.…”

Section: Motivationmentioning

confidence: 99%

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Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions

et al. 2023

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This paper proposes a novel approach that uses a spectral clustering method to cluster patients with e-health IoT devices based on their similarity and distance and connect each cluster to an SDN edge node for efficient caching. The proposed MFO-Edge Caching algorithm is considered for selecting the near-optimal data options for caching based on considered criteria and improving QoS. Experimental results demonstrate that the proposed approach outperforms other methods in terms of performance, achieving decrease in average time between data retrieval delays and the cache hit rate of 76%. Emergency and on-demand requests are prioritized for caching response packets, while periodic requests have a lower cache hit ratio of 35%. The approach shows improvement in performance compared to other methods, highlighting the effectiveness of SDN-Edge caching and clustering for optimizing e-health network resources.

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Section: Motivationmentioning

confidence: 99%

“…1 . It includes the device layer, edge layer and cloud layer as explained in the following [ 13 , 42 , 43 ].…”

Section: Proposed Architecturementioning

confidence: 99%

Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions

et al. 2023

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“…We have seen that existing grid and cloud approaches for data management are a poor fit for the unique characteristics of fog environments. Hence, numerous fog-native data management solutions have been proposed [39]. Hourglass [56] introduces circuits, an abstraction for data flow from sensor networks to data consumers and in-network services.…”

Section: Fog-nativementioning

confidence: 99%

Managing Data Replication and Distribution in the Fog with FReD

Pfandzelter¹,

Nils²,

Schirmer³

et al. 2023

Preprint

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The heterogeneous, geographically distributed infrastructure of fog computing poses challenges in data replication, data distribution, and data mobility for fog applications. Fog computing is still missing the necessary abstractions to manage application data, and fog application developers need to re-implement data management for every new piece of software. Proposed solutions are limited to certain application domains, such as the IoT, are not flexible in regard to network topology, or do not provide the means for applications to control the movement of their data.In this paper, we present FReD, a data replication middleware for the fog. FReD serves as a building block for configurable fog data distribution and enables low-latency, high-bandwidth, and privacy-sensitive applications. FReD is a common data access interface across heterogeneous infrastructure and network topologies, provides transparent and controllable data distribution, and can be integrated with applications from different domains. To evaluate our approach, we present a prototype implementation of FReD and show the benefits of developing with FReD using three case studies of fog computing applications.

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“…[ 10 ] This is especially due to the use of data centers (the hosting cloud and a prime part of cloud computing), which consumes huge amounts of energy, and is therefore a high carbon footprint contributor. [ 10,11 ] Data centers have been estimated to consume between 1% and 1.5% of global energy in 2010. [ 9 ] In a Nature publication, Jones [ 8 ] claims data centers alone use 1% of global electricity demand and are responsible for 0.3% of carbon emissions.…”

Section: Electronics Assisting With Environmental and Energy Related ...mentioning

confidence: 99%

Eco‐Friendly Electronics—A Comprehensive Review

Cenci

Scarazzato

München

et al. 2021

Adv Materials Technologies

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these two phenomena and it is now understood that EEE are both part of the environmental cure and the environmental disease: while the increasing production and disposal of EEE have harmful consequences to the planet, [1] the use of EEE can assist in saving energy and natural resources. The research concerning ecofriendly electronics increased greatly in recent decades due to environmental legislations becoming increasingly rigorous and because of the increase in eco-friendly sought devices, which required business models to adapt in order to participate in this new market share. The concepts of eco-friendly electronics or green electronics comprehends several dimensions of this electronic-environment relationship and has been used loosely for a myriad of initiatives. Hu and Ismail [2] explain that the concept may be used to refer to the i) manufacturing process, through the employment of environmentally friendly processes and the avoidance of hazardous components or chemicals; ii) waste generation (avoidance), via reducing the e-waste impacts through the use of cleaner materials, longer product life, introducing programs to raise awareness and promote reuse/recycling; iii) use of sustainable practice (green computing), through the responsible use of computer resources, for example, by powering down and up devices according to need, reducing energy consumption during inactivity; iv) design, through the development of more efficient components that required less energy to perform, reduce carbon emissions, produce less heat, etc. Yet eco-friendly electronics can also refer to electronics whose purpose is to assist the environment or that do so as a consequence of its main function. Both these groups may be understood as an overlap between the aforementioned categories, and are equipment that optimize energy usage, minimize carbon footprint, detect pollutant concentration, monitor oil spillage, generate renewable energy, etc. There are many and diverse examples of these, such as power electronics, smart grids, and photovoltaic systems. [3] This review is intended to discuss these interactions, define important concepts, and provide an extensive list of ways in which EEE can be eco-friendly, primarily focusing on information and communication technology (ICT) devices, but also addressing items that fall outside of this category such as washing machines and lighting equipment. Initially, the use of electronics in aiding with energy and pollution related Eco-friendliness is becoming an indispensable feature for electrical and electronic equipment to thrive in the competitive market. This comprehensive review is the first to define eco-friendly electronics in its multiple meanings: power saving devices, end-of-life impact attenuators, equipment whose manufacturing uses green processing, electronics that use materials that minimize environmental and health risks, designs that improve lifespan, reparability, etc. More specifically, this review discusses eco-friendly technologies and materials that are being introduced to ...

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Data Management in Fog Computing

Cited by 16 publications

References 24 publications

Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions

Composition of caching and classification in edge computing based on quality optimization for SDN-based IoT healthcare solutions

Managing Data Replication and Distribution in the Fog with FReD

Eco‐Friendly Electronics—A Comprehensive Review

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