research-article

Fog Data: Enhancing Telehealth Big Data Through Fog Computing

Authors:

Harishchandra Dubey,

Amir Mohammad Amiri,

Kunal MakodiyaAuthors Info & Claims

ASE BD&SI '15: Proceedings of the ASE BigData & SocialInformatics 2015

Article No.: 14, Pages 1 - 6

https://doi.org/10.1145/2818869.2818889

Published: 07 October 2015 Publication History

Abstract

The size of multi-modal, heterogeneous data collected through various sensors is growing exponentially. It demands intelligent data reduction, data mining and analytics at edge devices. Data compression can reduce the network bandwidth and transmission power consumed by edge devices. This paper proposes, validates and evaluates Fog Data, a service-oriented architecture for Fog computing. The center piece of the proposed architecture is a low power embedded computer that carries out data mining and data analytics on raw data collected from various wearable sensors used for telehealth applications. The embedded computer collects the sensed data as time series, analyzes it, and finds similar patterns present. Patterns are stored, and unique patterns are transmited. Also, the embedded computer extracts clinically relevant information that is sent to the cloud. A working prototype of the proposed architecture was built and used to carry out case studies on telehealth big data applications. Specifically, our case studies used the data from the sensors worn by patients with either speech motor disorders or cardiovascular problems. We implemented and evaluated both generic and application specific data mining techniques to show orders of magnitude data reduction and hence transmission power savings. Quantitative evaluations were conducted for comparing various data mining techniques and standard data compression techniques. The obtained results showed substantial improvement in system efficiency using the Fog Data architecture.

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Cited By

Sworna NIslam AShatabda SIslam S(2021)Towards development of IoT-ML driven healthcare systemsJournal of Network and Computer Applications10.1016/j.jnca.2021.103244196:COnline publication date: 15-Dec-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103244
Laroui MNour BMoungla HCherif MAfifi HGuizani M(2021)Edge and fog computing for IoTComputer Communications10.1016/j.comcom.2021.09.003180:C(210-231)Online publication date: 30-Dec-2021
https://dl.acm.org/doi/10.1016/j.comcom.2021.09.003
Barik RMankodiya KPriyadarshini RLenka RDubey H(2020)Fog Computing Architecture for Scalable Processing of Geospatial Big DataInternational Journal of Applied Geospatial Research10.4018/IJAGR.202001010111:1(1-20)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.4018/IJAGR.2020010101
Show More Cited By

Index Terms

Fog Data: Enhancing Telehealth Big Data Through Fog Computing
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications
    1. Data mining

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cover image ACM Other conferences

ASE BD&SI '15: Proceedings of the ASE BigData & SocialInformatics 2015

October 2015

381 pages

ISBN:9781450337359

DOI:10.1145/2818869

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 October 2015

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ASE BD&SI '15

ASE BD&SI '15: ASE BigData & SocialInformatics 2015

October 7 - 9, 2015

Kaohsiung, Taiwan

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Cited By

Sworna NIslam AShatabda SIslam S(2021)Towards development of IoT-ML driven healthcare systemsJournal of Network and Computer Applications10.1016/j.jnca.2021.103244196:COnline publication date: 15-Dec-2021
https://dl.acm.org/doi/10.1016/j.jnca.2021.103244
Laroui MNour BMoungla HCherif MAfifi HGuizani M(2021)Edge and fog computing for IoTComputer Communications10.1016/j.comcom.2021.09.003180:C(210-231)Online publication date: 30-Dec-2021
https://dl.acm.org/doi/10.1016/j.comcom.2021.09.003
Barik RMankodiya KPriyadarshini RLenka RDubey H(2020)Fog Computing Architecture for Scalable Processing of Geospatial Big DataInternational Journal of Applied Geospatial Research10.4018/IJAGR.202001010111:1(1-20)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.4018/IJAGR.2020010101
Aggarwal HSharma M(2019)Applying Belief Rule-Based Inference Methodology Using Evidential Reasoning Approach to Clinical Reporting SystemInternational Journal of Computers in Clinical Practice10.4018/IJCCP.20190701024:2(13-32)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.4018/IJCCP.2019070102
Zhang LLi CWang PLiu YHu YChen QGuo M(2019)Characterizing and orchestrating NFV-ready servers for efficient edge data processingProceedings of the International Symposium on Quality of Service10.1145/3326285.3329057(1-10)Online publication date: 24-Jun-2019
https://dl.acm.org/doi/10.1145/3326285.3329057
Kamran KYeh EMa Q(2019)DECOProceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing10.1145/3323679.3326509(111-120)Online publication date: 2-Jul-2019
https://dl.acm.org/doi/10.1145/3323679.3326509
Anawar MWang SAzam Zia MJadoon AAkram URaza S(2018)Fog ComputingWireless Communications & Mobile Computing10.1155/2018/71571922018Online publication date: 7-May-2018
https://dl.acm.org/doi/10.1155/2018/7157192
Al-khafajiy MWebster LBaker TWaraich AAbuarqoub AAdebisi BHammoudeh MMurad SArioua M(2018)Towards fog driven IoT healthcareProceedings of the 2nd International Conference on Future Networks and Distributed Systems10.1145/3231053.3231062(1-7)Online publication date: 26-Jun-2018
https://dl.acm.org/doi/10.1145/3231053.3231062
Li CXue YWang JZhang WLi T(2018)Edge-Oriented Computing ParadigmsACM Computing Surveys10.1145/315481551:2(1-34)Online publication date: 17-Apr-2018
https://dl.acm.org/doi/10.1145/3154815
Mahmud RKoch FBuyya R(2018)Cloud-Fog Interoperability in IoT-enabled Healthcare SolutionsProceedings of the 19th International Conference on Distributed Computing and Networking10.1145/3154273.3154347(1-10)Online publication date: 4-Jan-2018
https://dl.acm.org/doi/10.1145/3154273.3154347
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