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Fog computing technologies for patient sensor networks – trends, issues and future directions

Abstract

Advances in sensors and internet of things promise broad opportunities in many areas and one of them is health care. There are many solutions to manage health care data based on cloud computing. However, high response latency, large volumes of data transferred and security are the main issues of such approach. Fog computing provides immediate response and ways to process large amounts of data using real time analytics which includes machine learning and AI. Fog computing has not yet fully matured and there are still many challenges when managing health care data. It was chosen to investigate the most relevant e­health fog computing topics by analyzing review articles to explain the fog computing model and present the current trends – fog computing e­health technology application environments, deployment cases, infrastructure technologies, data processing challenges, problems and future directions. 38 scientific review articles published in the last 5 years were selected for analysis, filtering the most significant works with Web of Science article search tool.


Article in Lithuanian.


Rūko kompiuterijos technologijos pacientų jutiklių tinklams – tendencijos, problemos ir ateities kryptys


Santrauka


Jutiklių ir daiktų interneto pažanga žada plačias galimybes daugelyje sričių, viena iš jų – sveikatos priežiūra. Sukurta daugybė sprendimų, kaip valdyti sveikatos priežiūros duomenis, pagrįstus debesų kompiuterija, tačiau didelė delsa, didelis perduodamų duomenų kiekis ir jų saugumas yra pagrindinės nutolusių duomenų centrų problemos norint perduoti sveikatos duomenis. Rūko kompiuterija pasižymi greitu atsaku ir leidžia apdoroti didelius duomenų kiekius atliekant realaus laiko analizę, apimančią mašininį mokymąsi ir dirbtinį intelektą. Rūko kompiuterija dar nėra visiškai įsitvirtinusi, o tvarkant sveikatos duomenis vis dar kyla daug problemų. Šiame straipsnyje pateikiama rūko kompiuterijos sveikatos priežiūros srityje apžvalga. Pasirinkta ištirti aktualiausias e. sveikatos rūko kompiuterijos tematikos kryptis išanalizuojant apžvalginius straipsnius, paaiškinti rūko kompiuterijos architektūros modelį ir pateikti dabartines tendencijas – rūko kompiuterijos e. sveikatos technologijų taikymo aplinkas, diegimo atvejus, infrastruktūros technologijas, duomenų apdorojimo uždavinius, problemas ir ateities kryptis. Atrinkti 38 per pastaruosius 5 metus publikuoti mokslinės apžvalgos straipsniai darbų analizei, filtruojant reikšmingiausius darbus taikant Web of Science straipsnių paieškos įrankį.


Reikšminiai žodžiai: rūko kompiuterija, daiktų internetas, sveikatos priežiūra, apžvalga.

Keyword : fog computing, internet of things, health care, review

How to Cite
Kazlauskas, M. (2021). Fog computing technologies for patient sensor networks – trends, issues and future directions. Mokslas – Lietuvos Ateitis / Science – Future of Lithuania, 13. https://doi.org/10.3846/mla.2021.15174
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Aug 20, 2021
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References

Aceto, G., Persico, V., & Pescapé, A. (2018). The role of Information and Communication Technologies in healthcare: taxonomies, perspectives, and challenges. Journal of Network and Computer Applications, 107, 125–154.
https://doi.org/10.1016/j.jnca.2018.02.008

Aceto, G., Persico, V., & Pescapé, A. (2020). Industry 4.0 and Health: Internet of Things, Big Data, and Cloud Computing for Healthcare 4.0. Journal of Industrial Information Integration, 18, 100129. https://doi.org/10.1016/j.jii.2020.100129

Anawar, M. R., Wang, S. G., Zia, M. A., Jadoon, A. K., Akram, U., & Raza, S. (2018). Fog computing: an overview of Big IoT data analytics. Wireless Communications and Mobile Computing, 2018, 7157192. https://doi.org/10.1155/2018/7157192

Badidi, E., Mahrez, Z., & Sabir, E. (2020). Fog computing for smart cities’ big data management and analytics: a review. Future Internet, 12(11), 190. https://doi.org/10.3390/fi12110190

Basir, R., Qaisar, S., Ali, M., Aldwairi, M., Ashraf, M. I., Mahmood, A., & Gidlund, M. (2019). Fog computing enabling Industrial Internet of Things: state­of­the­art and research challenges. Sensors, 19(21), 4807.
https://doi.org/10.3390/s19214807

Behmanesh, A., Sayfouri, N., & Sadoughi, F. (2020). Technological features of Internet of Things in medicine: a systematic mapping study. Wireless Communications and Mobile Computing, 2020, 9238614.
https://doi.org/10.1155/2020/9238614

Bonomi, F. (2019). The edge – fog movement: a paradigm shift with many names. https://web.archive.org/web/20210117034005/https://www.nebbiolo.tech/2019/08/14/the-edge-fog-movement-a-paradigm-shift-with-many-names/

Cisco. (2015). Cisco fog computing solutions: unleash the power of the Internet of Things [White paper]. https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf

da Silva, C. A., & de Aquino, G. S. (2018). Fog computing in healthcare: a review. In IEEE Symposium on Computers and Communications (ISCC) (pp. 1131–1136). Institute of Electrical and Electronics Engineers.
https://doi.org/10.1109/iscc.2018.8538671

Dang, L. M., Piran, M. J., Han, D., Min, K., & Moon, H. (2019). A survey on Internet of Things and cloud computing for healthcare. Electronics, 8(7), 768.
https://doi.org/10.3390/electronics8070768

Dash, S., Biswas, S., Banerjee, D., & Atta­Ur­Rahman. (2019). Edge and fog computing in healthcare − a review. Scalable Computing: Practice and Experience, 20(2), 191–205.
https://doi.org/10.12694/scpe.v20i2.1504

de Moura Costa, H. J., da Costa, C. A., da Rosa Righi, R., & Antunes, R. S. (2020). Fog computing in health: A systematic literature review. Health and Technology, 10(5), 1025–1044. https://doi.org/10.1007/s12553-020-00431-8

de Prado, R. P., Garcia­Galan, S., Munoz­Exposito, J. E., Marchewka, A., & Ruiz­Reyes, N. (2020). Smart containers schedulers for microservices provision in cloud­fog­IoT networks. Challenges and opportunities. Sensors, 20(6), 1714. https://doi.org/10.3390/s20061714

Dong, Y. D., & Yao, Y. D. (2021). IoT platform for COVID­19 prevention and control: a survey. IEEE Access, 9, 49929–
49941. https://doi.org/10.1109/access.2021.3068276

Erhan, L., Ndubuaku, M., Di Mauro, M., Song, W., Chen, M., Fortino, G., Bagdasar, O., & Liotta, A. (2021). Smart anomaly detection in sensor systems: A multi­perspective review. Information Fusion, 67, 64–79.
https://doi.org/10.1016/j.inffus.2020.10.001

Escamilla-­Ambrosio, P. J., Rodriguez-­Mota, A., Aguirre­-Anaya, E., Acosta-­Bermejo, R., & Salinas­-Rosales, M. (2018). Distributing computing in the Internet of Things: cloud, fog and edge computing overview. In Neo 2016. Studies in Computational Intelligence (Vol. 731, pp. 87–115). Springer. https://doi.org/10.1007/978-3-319-64063-1_4

Forster, K. (2021). Conversation with Flavio Bonomi. Podcast #139 Fog Man. https://www.momenta.one/insights/fog-man-flavio-bonomi

Fu, C., Lv, Q., & Badrnejad, R. G. (2020). Fog computing in health management processing systems. Kybernetes, 49(12), 2893–2917. https://doi.org/10.1108/K-09-2019-0621

Gaber, M. M., Aneiba, A., Basurra, S., Batty, O., Elmisery, A. M., Kovalchuk, Y., & Rehman, M. H. U. (2019). Internet of Things and data mining: From applications to techniques and systems. WIREs Data Mining and Knowledge Discovery, 9(3), e1292. https://doi.org/10.1002/widm.1292

Haouari, F., Faraj, R., & AlJa’am, J. M. (2018). Fog computing potentials, applications, and challenges. In 2018 International Conference on Computer and Applications (ICCA) (pp. 399– 406). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/comapp.2018.8460182

Hartmann, M., Hashmi, U. S., & Imran, A. (2019). Edge computing in smart health care systems: Review, challenges, and research directions. Transactions on Emerging Telecommunications Technologies, 1–25.
https://doi.org/10.1002/ett.3710

Hu, P. F., Dhelim, S., Ning, H. S., & Qiu, T. (2017). Survey on fog computing: architecture, key technologies, applications and open issues. Journal of Network and Computer Applications, 98, 27–42. https://doi.org/10.1016/j.jnca.2017.09.002

Ibrahim, W. N. H., Selamat, A., Krejcar, O., & Chaudhry, J. (2018). Recent advances on fog health – a systematic literature review. In New trends in intelligent software methodologies, tools and techniques (Vol. 303, pp. 157–170).
https://doi.org/10.3233/978-1-61499-900-3-157

Younan, M., Houssein, E. H., Elhoseny, M., & Ali, A. A. (2020). Challenges and recommended technologies for the industrial internet of things: A comprehensive review. Measurement, 151, 107198. https://doi.org/10.1016/j.measurement.2019.107198

Javadzadeh, G., & Rahmani, A. M. (2020). Fog computing applications in smart cities: a systematic survey. Wireless Networks, 26(2), 1433–1457.
https://doi.org/10.1007/s11276-019-02208-y

Kaur, J., Agrawal, A., & Khan, R. A. (2020a). Security issues in fog environment: a systematic literature review. International Journal of Wireless Information Networks, 27(3), 467–483. https://doi.org/10.1007/s10776-020-00491-7

Kaur, R., Pasricha, R., & Kaur, B. (2020b). A study of wireless body area networks and its routing protocols for healthcare environment. Recent Advances in Electrical & Electronic Engineering, 13(2), 136–152.
https://doi.org/10.2174/2352096512666190305152857

Kraemer, F. A., Braten, A. E., Tamkittikhun, N., & Palma, D. (2017). Fog computing in healthcare − a review and discussion. IEEE Access, 5, 9206–9222.
https://doi.org/10.1109/access.2017.2704100

McCann, J., Quinn, L., McGrath, S., & O’Connell, E. (2018). Towards the distributed edge − an IoT review. In 2018 12th International Conference on Sensing Technology (ICST) (pp. 263–268). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/icsenst.2018.8603663

McLamore, E. S., Datta, S. P. A., Morgan, V., Cavallaro, N., Kiker, G., Jenkins, D. M., Rong, Y., Gomes, C., Claussen, J., Vanegas, D., & Alocilja, E. C. (2019). SNAPS: sensor analytics point solutions for detection and decision support systems. Sensors, 19(22), 4935. https://doi.org/10.3390/s19224935

Naresh, V. S., Pericherla, S. S., Murty, P. S. R., & Reddi, S. (2020). Internet of Things in healthcare: architecture, applications, challenges, and solutions. Computer Systems Science and Engineering, 35(6), 411–421. https://doi.org/10.32604/csse.2020.35.411

Nazir, S., Ali, Y., Ullah, N., & Garcia-­Magarino, I. (2019). Internet of Things for healthcare using effects of mobile computing: a systematic literature review. Wireless Communications and Mobile Computing, 2019, 5931315.
https://doi.org/10.1155/2019/5931315

Obaidat, M. A., Obeidat, S., Holst, J., Al Hayajneh, A., & Brown, J. (2020). A comprehensive and systematic survey on the Internet of Things: security and privacy challenges, security frameworks, enabling technologies, threats, vulnerabilities and countermeasures. Computers, 9(2), 44.
https://doi.org/10.3390/computers9020044

Sadri, A. A., Rahmani, A. M., Saberikamarposhti, M., & Hosseinzadeh, M. (2021). Fog data management: A vision, challenges, and future directions. Journal of Network and Computer Applications, 174, 102882.
https://doi.org/10.1016/j.jnca.2020.102882

Saheb, T., & Izadi, L. (2019). Paradigm of IoT big data analytics in the healthcare industry: A review of scientific literature and mapping of research trends. Telematics and Informatics, 41, 70–85. https://doi.org/10.1016/j.tele.2019.03.005

Silva, F. S. D., Silva, E., Neto, E. P., Lemos, M., Neto, A. J. V., & Esposito, F. (2020). A taxonomy of DDoS attack mitigation approaches featured by SDN technologies in IoT scenarios. Sensors, 20(11), 3078. https://doi.org/10.3390/s20113078

Swamy, S. N., & Kota, S. R. (2020). An empirical study on system level aspects of Internet of Things (IoT). IEEE Access, 8,
188082–188134. https://doi.org/10.1109/access.2020.3029847

Tayeb, S., Latifi, S., & Kim, Y. (2017). A survey on IoT communication and computation frameworks: an industrial perspective. In 2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 1–6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ccwc.2017.7868354

Thurston, K. H., & de Leon, D. C. (2018). The healthcare IoT ecosystem advantages of fog computing near the edge. In 2018 IEEE/ACM International Conferece on Connected Health: Applications, Systems and Engineering Technologies (CHASE) (pp. 51–56), Washington, DC, USA.
https://doi.org/10.1145/3278576.3278595

Vilela, P. H., Rodrigues, J. J. P. C., Righi, R. D., Kozlov, S., & Rodrigues, V. F. (2020). Looking at fog computing for e­health through the lens of deployment challenges and applications. Sensors, 20(9), 2553. https://doi.org/10.3390/s20092553

Wani, U. I., Batth, R. S., & Rashid, M. (2019). Fog computing challenges and future directions: a mirror review. In 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE’ 2019) (pp. 765–769). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/iccike47802.2019.9004428