Volume 8, Issue 4 (April 2021), Pages: 82-88
----------------------------------------------
Original Research Paper
Title: Dependability in fog computing: Challenges and solutions
Author(s): Sara Alraddady 1, *, Alice Li 1, Ben Soh 1, Mohammed AlZain 2
Affiliation(s):
1La Trobe University, Melbourne, Australia
2College of Computers and Information Technology, Taif University, Taif, Saudi Arabia
Full Text - PDF XML
* Corresponding Author.
Corresponding author's ORCID profile: https://orcid.org/0000-0001-6228-9696
Digital Object Identifier:
https://doi.org/10.21833/ijaas.2021.04.010
Abstract:
The tremendous increase in IoT devices and the amount of data they produced is very expensive to be processed at cloud data centers. Therefore, fog computing was introduced in 2012 by Cisco as a decentralized computing environment that is considered to be more efficient in handling such a plethora in the number of requests. Fog computing is a distributed computing paradigm that focuses on bringing data processing at the network peripheral to reduce response time and increase the quality of service. Dependability challenges of such distributed and heterogeneous computing environments are considered in this paper. Because fog computing is a new computing paradigm, several studies have been presented to tackle its challenges and issues. However, dependability in specific did not receive much attention. In the paper, we explore several solutions to increase dependability in fog computing such as fault tolerance techniques, placement policies, middleware, and data management mechanisms aiming to help system designers choose the most appropriate solution.
© 2021 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Fog computing, Fault tolerance, Availability, Placement policy
Article History: Received 4 October 2020, Received in revised form 20 December 2020, Accepted 23 December 2020
Acknowledgment:
No Acknowledgment.
Compliance with ethical standards
Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Citation:
Alraddady S, Li A, and Soh B et al. (2021). Dependability in fog computing: Challenges and solutions. International Journal of Advanced and Applied Sciences, 8(4): 82-88
Permanent Link to this page
Figures
Fig. 1
Tables
No Table
----------------------------------------------
References (28)
- Ahmed W and Wu YW (2013). A survey on reliability in distributed systems. Journal of Computer and System Sciences, 79(8): 1243-1255. https://doi.org/10.1016/j.jcss.2013.02.006 [Google Scholar]
- Arivazhagan C and Natarajan V (2020). A survey on fog computing paradigms, challenges and opportunities in IoT. In the International Conference on Communication and Signal Processing, IEEE, Chennai, India: 0385-0389. https://doi.org/10.1109/ICCSP48568.2020.9182229 [Google Scholar]
- Bansal S and Kumar D (2020). IoT ecosystem: A survey on devices, gateways, operating systems, middleware and communication. International Journal of Wireless Information Networks, 27: 340-364. https://doi.org/10.1007/s10776-020-00483-7 [Google Scholar]
- Bittencourt LF, Diaz-Montes J, Buyya R, Rana OF, and Parashar M (2017). Mobility-aware application scheduling in fog computing. IEEE Cloud Computing, 4(2): 26-35. https://doi.org/10.1109/MCC.2017.27 [Google Scholar]
- Choudhury B, Choudhury S, and Dutta A (2019). A proactive context-aware service replication scheme for Adhoc IoT scenarios. IEEE Transactions on Network and Service Management, 16(4): 1797-1811. https://doi.org/10.1109/TNSM.2019.2928698 [Google Scholar]
- Clemente J, Valero M, Mohammadpour J, Li X, and Song W (2017). Fog computing middleware for distributed cooperative data analytics. In 2017 IEEE Fog World Congress, IEEE, Santa Clara, USA: 1-6. https://doi.org/10.1109/FWC.2017.8368520 [Google Scholar]
- CS (2015). Fog computing and the internet of things: Extend the cloud to where the things are. Cisco Systems, San Jose, USA. [Google Scholar]
- Dong WE, Nan W, and Xu L (2013). QoS-oriented monitoring model of cloud computing resources availability. In the International Conference on Computational and Information Sciences, IEEE, Shiyang, China: 1537-1540. https://doi.org/10.1109/ICCIS.2013.404 [Google Scholar] PMid:23614461
- Grover J and Garimella RM (2018). Reliable and fault-tolerant IoT-edge architecture. In the IEEE Sensors, IEEE, New Delhi, India: 1-4. https://doi.org/10.1109/ICSENS.2018.8589624 [Google Scholar]
- Guerrero-Contreras G, Garrido JL, Balderas-Diaz S, and Rodriguez-Dominguez C (2017). A context-aware architecture supporting service availability in mobile cloud computing. IEEE Transactions on Services Computing, 10(6): 956-968. https://doi.org/10.1109/TSC.2016.2540629 [Google Scholar]
- Heidari A, Jabraeil JMA, Jafari NN, and Akbarpour S (2020). Internet of Things offloading: Ongoing issues, opportunities, and future challenges. International Journal of Communication Systems, 33(14): e4474. https://doi.org/10.1002/dac.4474 [Google Scholar]
- Javed A, Heljanko K, Buda A, and Främling K (2018). Cefiot: A fault-tolerant IoT architecture for edge and cloud. In the IEEE 4th World Forum on Internet of Things, IEEE, Singapore, Singapore: 813-818. https://doi.org/10.1109/WF-IoT.2018.8355149 [Google Scholar]
- Johnson BW (1989). Design and analysis of fault-tolerant systems for industrial applications. In: Görke W and Sörensen H (Eds.), Fehlertolerierende rechensysteme/fault-tolerant computing systems: 57-73. Springer, Berlin, Germany. https://doi.org/10.1007/978-3-642-75002-1_5 [Google Scholar]
- Johnson BW (1996). An introduction to the design and analysis of fault-tolerant systems. In: Pradhan DK (Ed.), Fault-tolerant computer system design: 1-108. Prentice-Hall, Inc., Upper Saddle River, USA. [Google Scholar]
- Lera I, Guerrero C, and Juiz C (2018). Availability-aware service placement policy in fog computing based on graph partitions. IEEE Internet of Things Journal, 6(2): 3641-3651. https://doi.org/10.1109/JIOT.2018.2889511 [Google Scholar]
- Liu H, Lin Y, Chen P, Jin L, and Ding F (2010). A practical availability risk assessment framework in ITIL. In the 5th IEEE International Symposium on Service Oriented System Engineering, IEEE. Nanjing, China: 286-290. https://doi.org/10.1109/SOSE.2010.38 [Google Scholar]
- Mahmud R, Srirama SN, Ramamohanarao K, and Buyya R (2019). Quality of Experience (QoE)-aware placement of applications in Fog computing environments. Journal of Parallel and Distributed Computing, 132: 190-203. https://doi.org/10.1016/j.jpdc.2018.03.004 [Google Scholar]
- Maiti P, Apat HK, Sahoo B, and Turuk AK (2019). An effective approach of latency-aware fog smart gateways deployment for IoT services. Internet of Things, 8: 100091. https://doi.org/10.1016/j.iot.2019.100091 [Google Scholar]
- Mohamed N, Al-Jaroodi J, and Jawhar I (2019). Towards fault tolerant fog computing for IoT-based smart city applications. In the IEEE 9th Annual Computing and Communication Workshop and Conference, IEEE, Las Vegas, USA: 0752-0757. https://doi.org/10.1109/CCWC.2019.8666447 [Google Scholar]
- Mohamed N, Al-Jaroodi J, Lazarova-Molnar S, Jawhar I, and Mahmoud S (2017). A service-oriented middleware for cloud of things and fog computing supporting smart city applications. In the IEEE Smart World, Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, IEEE, San Francisco, USA: 1-7. https://doi.org/10.1109/UIC-ATC.2017.8397564 [Google Scholar]
- Moura CHJ, da Costa CA, da Rosa Righi R, and Antunes RS (2020). Fog computing in health: A systematic literature review. Health and Technology, 10: 1025–1044. https://doi.org/10.1007/s12553-020-00431-8 [Google Scholar]
- Neto AJP, Pianto DM, and Ralha CG (2018). A fault-tolerant agent-based architecture for transient servers in fog computing. In the 30th International Symposium on Computer Architecture and High Performance Computing, IEEE, Lyon, France, France: 282-289. https://doi.org/10.1109/CAHPC.2018.8645859 [Google Scholar]
- Nguyen TA, Min D, and Choi E (2020). A hierarchical modeling and analysis framework for availability and security quantification of IoT infrastructures. Electronics, 9(1): 155-184. https://doi.org/10.3390/electronics9010155 [Google Scholar]
- OFC (2017). Openfog reference architecture for fog computing. OpenFog Consortium, Fremont, USA. [Google Scholar]
- Pham VA and Karmouch A (1998). Mobile software agents: An overview. IEEE Communications Magazine, 36(7): 26-37. https://doi.org/10.1109/35.689628 [Google Scholar]
- Popentiu-Vladicescu F and Albeanu G (2017). Software reliability in the fog computing. In the International Conference on Innovations in Electrical Engineering and Computational Technologies, IEEE, Karachi, Pakistan: 1-4. https://doi.org/10.1109/ICIEECT.2017.7916578 [Google Scholar]
- Steffenel LA (2018). Improving the performance of fog computing through the use of data locality. In the 30th International Symposium on Computer Architecture and High Performance Computing, IEEE. Lyon, France: 217-224. https://doi.org/10.1109/CAHPC.2018.8645879 [Google Scholar]
- Wang K, Shao Y, Xie L, Wu J, and Guo S (2020). Adaptive and fault-tolerant data processing in healthcare IoT based on fog computing. IEEE Transactions on Network Science and Engineering, 7(1): 263-273. https://doi.org/10.1109/TNSE.2018.2859307 [Google Scholar]
|