Segmented Network Architecture for Promoting High Availability in Fog Computing through Middleware

Mohd Hariz Naim, Jasni Mohamad Zain, Kamarularifin Abd Jalil, Lizawati Salahuddin


This paper proposes an architecture for deploying applications on a fog computing environment by adding another layer of fog nodes in a network segment that gains high software application availability. The conventional fog computing architecture would permanently shift the storage, applications, and data from cloud servers to fog nodes, thus reducing the dependency on the cloud. As a result, fog nodes are burdened with the task previously done by cloud servers and have become “mini cloud servers.” Instead of permanently shifting the tasks from cloud servers to fog nodes, the proposed architecture would only do the shifting, when necessary, like if an internet outage. Additionally, this research also introduced the middleware application that acts as a detector and replacement if service outage so that the availability of the services is not interrupted, especially during the internet outage, by adding another layer of fog node in a network segment. The computational process occurs between end-users and the fog nodes without having to rely on cloud servers. An experiment was conducted to test the performance of the proposed architecture. From the experiment, it can be concluded that the deployment of fog nodes in a segmented network is possible and able to increase the availability of data and services if an internet outage.


Fog computing; high availability; deployment architecture; middleware.

Full Text:



P. Alves, L. Antônio, S. Barreto, and N. Paulo, “Data centers ’ services restoration based on the decision-making of distributed agents,” Telecommun. Syst., 2020, doi: 10.1007/s11235-020-00660-2.

Y. Jin and H. J. Lee, “On-demand computation offloading architecture in fog networks,” Electron., vol. 8, no. 10, 2019, doi: 10.3390/electronics8101076.

E. Hassan, Z. M. Yusof, and K. Ahmad, “Factors Affecting Information Quality in the Malaysian Public Sector,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 9, no. 1, pp. 32–38, 2019, doi: 10.18517/ijaseit.9.1.6385.

J. Eloff and M. Bihina Bella, Software Failure Investigation A Near-Miss Analysis Approach, 1st ed. Cham, Switzerland: Springer International Publishing, 2018.

J. Liu, F. Liu, X. Li, K. He, Y. Ma, and J. Wang, “Web Service Clustering Using Relational Database Approach,” Int. J. Softw. Eng. Knowl. Eng., vol. 25, no. 8, pp. 1365–1393, 2015, doi: 10.1142/S021819401550028X.

J. Rahme and H. Xu, “A software reliability model for cloud-based software rejuvenation using dynamic fault trees,” Int. J. Softw. Eng. Knowl. Eng., vol. 25, no. 9–10, pp. 1491–1513, 2015, doi: 10.1142/S021819401540029X.

M. H. Naim, M. K. A. Ghani, A. S. H. Basari, B. Aboobaider, L. Salahuddin, and W. N. A. Rashid, “Synchronization technique via raspbery Pi as middleware for hospital information system,” Adv. Intell. Syst. Comput., vol. 734, pp. 262–271, 2018, doi: 10.1007/978-3-319-76351-4_27.

M. R. Mesbahi, A. M. Rahmani, and M. Hosseinzadeh, “Highly reliable architecture using the 80/20 rule in cloud computing datacenters,” Futur. Gener. Comput. Syst., vol. 77, pp. 77–86, 2017, doi: 10.1016/j.future.2017.06.011.

K. Syed and K. Vijaya, “Cloud Computing: Review on Recent Research Progress and Issues,” Int. J. Adv. Trends Comput. Sci. Eng., vol. 8, no. 3, pp. 959–962, 2019, doi: 10.30534/ijatcse/2019/96832019.

M. R. Mesbahi, A. M. Rahmani, and M. Hosseinzadeh, “Reliability and high availability in cloud computing environments: a reference roadmap,” Human-centric Comput. Inf. Sci., vol. 8, no. 1, 2018, doi: 10.1186/s13673-018-0143-8.

I. Sittón-Candanedo, R. S. Alonso, J. M. Corchado, S. Rodríguez-González, and R. Casado-Vara, “A review of edge computing reference architectures and a new global edge proposal,” Futur. Gener. Comput. Syst., vol. 99, no. 2019, pp. 278–294, 2019, doi: 10.1016/j.future.2019.04.016.

P. Hu, S. Dhelim, H. Ning, and T. Qiu, “Survey on fog computing: architecture, key technologies, applications and open issues,” J. Netw. Comput. Appl., vol. 98, no. September, pp. 27–42, 2017, doi: 10.1016/j.jnca.2017.09.002.

K. Bilal, O. Khalid, A. Erbad, and S. U. Khan, “Potentials, trends, and prospects in edge technologies: Fog, cloudlet, mobile edge, and micro data centers,” Comput. Networks, vol. 130, no. 2018, pp. 94–120, 2018, doi: 10.1016/j.comnet.2017.10.002.

F. A. Kraemer, A. E. Braten, N. Tamkittikhun, and D. Palma, “Fog Computing in Healthcare-A Review and Discussion,” IEEE Access, vol. 5, no. 2169, pp. 9206–9222, 2017, doi: 10.1109/ACCESS.2017.2704100.

Y. Ren, R. Pazzi, and a Boukerche, “Monitoring patients via a secure and mobile healthcare system,” Wirel. Commun. IEEE, vol. 17, no. February, pp. 59–65, 2010, doi: 10.1109/MWC.2010.5416351.

A. M. Rahmani et al., “Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach,” Futur. Gener. Comput. Syst., vol. 78, pp. 641–658, 2018, doi: 10.1016/j.future.2017.02.014.

B. Snyder, J. Ringenberg, R. Green, V. Devabhaktuni, and M. Alam, “Evaluation and design of highly reliable and highly utilized cloud computing systems,” J. Cloud Comput., vol. 4, no. 1, 2015, doi: 10.1186/s13677-015-0036-6.

R. Moreno-Vozmediano, R. S. Montero, E. Huedo, and I. M. Llorente, “Orchestrating the deployment of high availability services on multi-zone and multi-cloud scenarios,” J. Grid Comput., vol. 16, no. 1, pp. 39–53, 2017, doi: 10.1007/s10723-017-9417-z.

H. Shahzad, X. Li, and M. Irfan, “Review of data replication techniques for mobile computing environment,” Res. J. Appl. Sci. Eng. Technol., vol. 6, no. 9, pp. 1639–1648, 2013, doi: 10.19026/rjaset.6.3883.

R. K. Lomotey, S. Jamal, and R. Deters, “SOPHRA : A Mobile Web Services Hosting Infrastructure in mHealth,” 2012 IEEE First Int. Conf. Mob. Serv., pp. 88–95, 2012, doi: 10.1109/MobServ.2012.14.

L. Acquaviva et al., “NoMISHAP: A Novel Middleware Support for High Availability in Multicloud PaaS,” IEEE Cloud Comput., vol. 4, no. 4, pp. 60–72, Jul. 2017, doi: 10.1109/MCC.2017.3791011.

M. Singh and V. M. Srivastava, “Implementing architecture of fog computing for healthcare systems based on iot,” Int. J. Eng. Adv. Technol., vol. 8, no. 4C, pp. 23–27, 2019.

H. Zhang, Y. Xiao, S. Bu, D. Niyato, R. Yu, and Z. Han, “Fog computing in multi-tier data center networks: A hierarchical game approach,” 2016 IEEE Int. Conf. Commun. ICC 2016, pp. 1–6, 2016, doi: 10.1109/ICC.2016.7511146.

M. Tortonesi, M. Govoni, A. Morelli, G. Riberto, C. Stefanelli, and N. Suri, “Taming the IoT data deluge: An innovative information-centric service model for fog computing applications,” Futur. Gener. Comput. Syst., vol. 93, pp. 888–902, 2019, doi: 10.1016/j.future.2018.06.009.

C. Bahn, “IEEE Standard Computer Dictionary: IEEE Standard Computer Glossaries.” .

L. Cassandra et al., “Adopting an ISO / IEC 27005 : 2011-based Risk Treatment Plan to Prevent Patients from Data Theft,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 10, no. 3, pp. 914–919, 2020.

Y. Tang, H. Sun, X. Wang, and X. Liu, “Achieving convergent causal consistency and high availability for cloud storage,” Futur. Gener. Comput. Syst., vol. 74, pp. 20–31, 2017, doi: 10.1016/j.future.2017.04.016.

M. R.Kaseb, M. H. Khafaqy, I. A. Ali, and E. M.Saad, “An Improved Technique For Increasing Availability in Big Data Replication,” Futur. Gener. Comput. Syst., no. 91, pp. 493–505, 2019.

P. Alves Lima, A. Sá Barreto Neto, and P. Romero Martins MacIel, “Data Centers Service Restoration Based on Distributed Agents Decision,” Proc. - 2018 IEEE Int. Conf. Syst. Man, Cybern. SMC 2018, pp. 1611–1616, 2019, doi: 10.1109/SMC.2018.00279.

M. Stoicescu, J. C. Fabre, and M. Roy, “Architecting resilient computing systems: A component-based approach for adaptive fault tolerance,” J. Syst. Archit., vol. 73, pp. 6–16, 2017, doi: 10.1016/j.sysarc.2016.12.005.

M. Jammal, H. Hawilo, A. Kanso, and A. Shami, “Generic input template for cloud simulators: A case study of CloudSim,” Softw. - Pract. Exp., vol. 49, no. 5, pp. 720–747, 2019, doi: 10.1002/spe.2674.

A. Alelaiwi, “An efficient method of computation offloading in an edge cloud platform,” J. Parallel Distrib. Comput., vol. 127, pp. 58–64, 2019, doi: 10.1016/j.jpdc.2019.01.003.

Y. Aldwyan and R. O. Sinnott, “Latency-aware failover strategies for containerized web applications in distributed clouds Cloud Failover Techniques :,” Futur. Gener. Comput. Syst., vol. 101, pp. 1081–1095, 2019, doi: 10.1016/j.future.2019.07.032.

F. Tang, C. Liu, K. Li, Z. Tang, and K. Li, “Task Migration Optimization for Guaranteeing Delay Deadline with Mobility Consideration in Mobile Edge Computing,” J. Syst. Archit., p. 101849, 2020, doi: 10.1016/j.sysarc.2020.101849.

J. H. Lee and J. M. Gil, “Adaptive fault-tolerant scheduling strategies for mobile cloud computing,” J. Supercomput., vol. 75, no. 8, pp. 4472–4488, 2019, doi: 10.1007/s11227-019-02745-5.



  • There are currently no refbacks.

Published by INSIGHT - Indonesian Society for Knowledge and Human Development