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review-article

FogBus: : A Blockchain-based Lightweight Framework for Edge and Fog Computing

Published: 01 August 2019 Publication History

Highlights

A platform-independent framework for integrating Smart things, Fog and Cloud environment.
A Blockchain-enabled Platform-as-a-Service model to ensure data integrity.
A simplified prototype for Fog computing-based Sleep Apnea analysis.

Abstract

Recently much emphasize is given on integrating Edge, Fog and Cloud infrastructures to support the execution of various latency sensitive and computing intensive Internet of Things (IoT) applications. Although different real-world frameworks attempt to assist such integration, they have limitations in respect of platform independence, security, resource management and multi-application execution. To address these limitations, we propose a framework, named FogBus that facilitates end-to-end IoT-Fog(Edge)-Cloud integration. FogBus offers platform independent interfaces to IoT applications and computing instances for execution and interaction. It not only assists developers to build applications but also helps users to run multiple applications at a time and service providers to manage their resources. Moreover, FogBus applies Blockchain, authentication and encryption techniques to secure operations on sensitive data. Due to its simplified and cross platform software systems, it is easy to deploy, scalable and cost efficient. We demonstrate the effectiveness of FogBus by creating a computing environment with it that integrates finger pulse oximeters as IoT devices with Smartphone-based gateway and Raspberry Pi-based Fog nodes for Sleep Apnea analysis. We also evaluate the characteristics of FogBus in respect of other existing frameworks and the impact of various FogBus settings on system parameters through deployment of a real-world IoT application. The experimental results show that FogBus is comparatively lightweight and responsive, and different FogBus settings can tune the computing environment as per the situation demands.

References

[1]
M. Afrin, M.R. Mahmud, M.A. Razzaque, Real time detection of speed breakers and warning system for on-road drivers, Proc. of the IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2015, pp. 495–498.
[2]
O. Akrivopoulos, I. Chatzigiannakis, C. Tselios, A. Antoniou, On the deployment of healthcare applications over fog computing infrastructure, Computer Software and Applications Conference (COMPSAC), 2017 IEEE 41st Annual, 2, IEEE, 2017, pp. 288–293.
[3]
I. Azimi, A. Anzanpour, A.M. Rahmani, T. Pahikkala, M. Levorato, P. Liljeberg, N. Dutt, Hich: hierarchical fog-assisted computing architecture for healthcare IoT, ACM Trans. Embed. Comput. Syst.(TECS) 16 (5s) (2017) 174.
[4]
F. Bonomi, R. Milito, J. Zhu, S. Addepalli, Fog computing and its role in the internet of things, Proc. of the First Edition of the MCC Workshop on Mobile Cloud Computing, ACM, 2012, pp. 13–16.
[5]
M. Bravo, N. Diegues, J. Zeng, P. Romano, L.E. Rodrigues, On the use of clocks to enforce consistency in the cloud, IEEE Data Eng. Bull. 38 (1) (2015) 18–31.
[6]
Brownworth, A., 2017. How Blockchain Works. http://blockchain.mit.edu/how-blockchain-works. [Online; accessed 28-August-2018].
[7]
D. Bruneo, S. Distefano, F. Longo, G. Merlino, A. Puliafito, V. D’Amico, M. Sapienza, G. Torrisi, Stack4Things as a fog computing platform for Smart City applications, Computer Communications Workshops (INFOCOM WKSHPS), 2016 IEEE Conference on, IEEE, 2016, pp. 848–853.
[8]
R.N. Calheiros, A.N. Toosi, C. Vecchiola, R. Buyya, A coordinator for scaling elastic applications across multiple clouds, Future Gener. Comput. Syst. 28 (8) (2012) 1350–1362.
[9]
R.N. Calheiros, C. Vecchiola, D. Karunamoorthy, R. Buyya, The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid clouds, Future Gener. Comput. Syst. 28 (6) (2012) 861–870.
[10]
C. Chang, S.N. Srirama, R. Buyya, Indie fog: an efficient fog-computing infrastructure for the internet of things, Computer 50 (9) (2017) 92–98.
[11]
C. Chang, S.N. Srirama, R. Buyya, Internet of things (IoT) and new computing paradigms, Fog Edge Comput. (2019) 1–23.
[12]
N. Chen, Y. Chen, X. Ye, H. Ling, S. Song, C.-T. Huang, Smart city surveillance in fog computing, Advances in Mobile Cloud Computing and Big Data in the 5G Era, Springer, 2017, pp. 203–226.
[13]
R. Craciunescu, A. Mihovska, M. Mihaylov, S. Kyriazakos, R. Prasad, S. Halunga, Implementation of Fog computing for reliable E-health applications, Signals, Systems and Computers, 2015 49th Asilomar Conference on, IEEE, 2015, pp. 459–463.
[14]
H. Dubey, A. Monteiro, N. Constant, M. Abtahi, D. Borthakur, L. Mahler, Y. Sun, Q. Yang, U. Akbar, K. Mankodiya, Fog computing in medical internet-of-things: architecture, implementation, and applications, Handbook of Large-Scale Distributed Computing in Smart Healthcare, Springer, 2017, pp. 281–321.
[15]
T.N. Gia, M. Jiang, V.K. Sarker, A.M. Rahmani, T. Westerlund, P. Liljeberg, H. Tenhunen, Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes, Wireless Communications and Mobile Computing Conference (IWCMC), 2017 13th International, IEEE, 2017, pp. 1765–1770.
[16]
H. Gupta, A. Vahid Dastjerdi, S.K. Ghosh, R. Buyya, iFogSim: a toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments, Software: Practice and Experience 47 (9) (2017) 1275–1296.
[17]
J. He, M.H. Kryger, F.J. Zorick, W. Conway, T. Roth, Mortality and apnea index in obstructive sleep apnea: experience in 385 male patients, Chest 94 (1) (1988) 9–14.
[18]
P. Hu, H. Ning, T. Qiu, Y. Zhang, X. Luo, Fog computing based face identification and resolution scheme in internet of things, IEEE Trans. Ind. Inf. 13 (4) (2017) 1910–1920.
[19]
Initiative, M., 2017. Sleep apnea clustering. https://github.com/monarch-initiative/sleep-apnea-clustering. [Online; accessed 28-August-2018].
[20]
Jayavardhana Gubbi and Rajkumar Buyya and Slaven Marusic and Marimuthu Palaniswami, Internet of things (IoT): a vision, architectural elements, and future directions, Future Gener. Comput. Syst. 29 (7) (2013) 1645–1660.
[21]
Lab, M. M., 2015. App inventor. http://appinventor.mit.edu/appinventor-sources/. [Online; accessed 28-August-2018].
[22]
R. Mahmud, F.L. Koch, R. Buyya, Cloud-fog interoperability in IoT-enabled healthcare solutions, Proceedings of the 19th International Conference on Distributed Computing and Networking, ACM, New York, NY, USA, 2018, pp. 32:1–32:10.
[23]
R. Mahmud, K. Ramamohanarao, R. Buyya, Latency-aware application module management for fog computing environments, ACM Trans. Internet Technol. (TOIT) (2018) in press https://www.sciencedirect.com/science/article/pii/S0743731518301771.
[24]
R. Mahmud, S.N. Srirama, K. Ramamohanarao, R. Buyya, Quality of experience (qoe)-aware placement of applications in fog computing environments, J. Parallel Distrib. Comput. (2018),.
[25]
Manigadde, S., 2018. Sleep Apnea. https://github.com/subrahmanyamanigadde/sleepapnea. [Online; accessed 28-August-2018].
[27]
Microsoft, 2017. Windows performance toolkit. https://docs.microsoft.com/en-us/windows-hardware/test/wpt/.[Online; accessed 28-August-2018].
[28]
N. Mohamed, J. Al-Jaroodi, S. Lazarova-Molnar, I. Jawhar, S. Mahmoud, A service-oriented middleware for cloud of things and fog computing supporting smart city applications, 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), IEEE, 2017.
[29]
G. Muhammad, S.M.M. Rahman, A. Alelaiwi, A. Alamri, Smart health solution integrating IoT and cloud: a case study of voice pathology monitoring, IEEE Commun. Mag. 55 (1) (2017) 69–73.
[30]
C.A. Nigro, E. Dibur, E. Rhodius, Pulse oximetry for the detection of obstructive sleep apnea syndrome: can the memory capacity of oxygen saturation influence their diagnostic accuracy?, Sleep Disorders, Hindawi 2011 (2011).
[31]
A.M. Rahmani, T.N. Gia, B. Negash, A. Anzanpour, I. Azimi, M. Jiang, P. Liljeberg, Exploiting smart e-Health gateways at the edge of healthcare internet-of-Things: a fog computing approach, Future Gener. Comput. Syst. 78 (2018) 641–658.
[32]
M. Slabicki, K. Grochla, Performance evaluation of CoAP, SNMP and netconf protocols in fog computing architecture, NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium, 2016, pp. 1315–1319.
[33]
Splunkbase, 2018. Nigel’s performance monitor. https://splunkbase.splunk.com/app/1753/. [Online; accessed 28-August-2018].
[34]
M. Swan, Blockchain: Blueprint for a New Economy, O’Reilly Media, Inc, United States, 2015.
[35]
K. Vatanparvar, A. Faruque, M. Abdullah, Energy management as a service over fog computing platform, Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems, ACM, 2015, pp. 248–249.
[36]
N. Verba, K.-M. Chao, A. James, D. Goldsmith, X. Fei, S.-D. Stan, Platform as a service gateway for the fog of things, Adv. Eng. Inf. 33 (2017) 243–257.
[37]
S. Yangui, P. Ravindran, O. Bibani, R.H. Glitho, N.B. Hadj-Alouane, M.J. Morrow, P.A. Polakos, A platform as-a-service for hybrid cloud/fog environments, Local and Metropolitan Area Networks (LANMAN), 2016 IEEE International Symposium on, IEEE, 2016, pp. 1–7.
[38]
S. Yi, Z. Hao, Z. Qin, Q. Li, Fog computing: platform and applications, 2015 Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb), IEEE, 2015, pp. 73–78.
[39]
S. Yi, Z. Qin, Q. Li, Security and privacy issues of fog computing: asurvey, International conference on wireless algorithms, systems, and applications, Springer, 2015, pp. 685–695.
[40]
G. Zyskind, O. Nathan, et al., Decentralizing privacy: using Blockchain to protect personal data, Security and Privacy Workshops (SPW), 2015 IEEE, IEEE, 2015, pp. 180–184.

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      Information & Contributors

      Information

      Published In

      cover image Journal of Systems and Software
      Journal of Systems and Software  Volume 154, Issue C
      Aug 2019
      255 pages

      Publisher

      Elsevier Science Inc.

      United States

      Publication History

      Published: 01 August 2019

      Author Tags

      1. Fog computing
      2. Edge computing
      3. Cloud computing
      4. Internet of Things(IoT)
      5. Blockchain

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