Energy-aware and Reliable Service Placement of IoT applications on Fog Computing Platforms by Utilizing Whale Optimization Algorithm

Subject Areas : Cloud, Cluster, Grid and P2P Computing

Yaser Ramzanpoor ¹ (Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran)
Mirsaeid Hosseini Shirvani ² (Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran)
Mehdi GolSorkhTabar ³ (Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran)

Received: 2021-03-12 Accepted : 2021-07-27 Published : 2021-02-01

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References:

[1] Azimi Sh, Pahl C, Hosseini Shirvani M. Particle Swarm Optimization for Performance Management in Multi-cluster IoT Edge Architectures. International cloud computing conference CLOSER. 2020; 328-337. http://dx.doi.org/10.5220/0009391203280337.
[2] Karimi M. B, Isazadeh A,  Rahmani A. M. QoS-aware service composition in cloud computing using data mining techniques and genetic algorithm. The Journal of Supercomputing. 2017; 73(4):1387–1415. https://doi.org/10.1007/s11227-016-1814-8.
[3] Hosseini Shirvani M. Bi-objective web service composition problem in multi-cloud environment: a bi-objective time-varying particle swarm optimisation algorithm. J Exp Theor Artif Intell. 2020; 33(2):179-202.  https://doi.org/10.1080/0952813X.2020.1725652.
[4] Hosseini Shirvani M, Babazadeh Gorji A.  Optimisation of automatic web services composition using genetic algorithm. Int J Cloud Comput. 2020; 9(4):397–411. https://dx.doi.org/10.1504/IJCC.2020.112313
[5] Ramzanpoor Y, Hosseini Shirvani M. Multi-objective QoS-aware Optimization for Deployment of IoT Applications on Cloud and Fog Computing Infrastructure. Cluster Computing. 2021; Under Review.
[6] Ramzanpoor, Y., Hosseini Shirvani, M. & Golsorkhtabaramiri, M. Multi-objective fault-tolerant optimization algorithm for deployment of IoT applications on fog computing infrastructure. Complex Intell. Syst. (2021). https://doi.org/10.1007/s40747-021-00368-z.
[7] Farzai S, Hosseini Shirvani M, Rabbani M, Multi-Objective Communication-Aware Optimization for Virtual Machine Placement in Cloud Datacenters. Sustainable Computing: Informatics and Systems. 2020; 28. https://doi.org/10.1016/j.suscom.2020.100374.
[8] Foukalas F. Cognitive IoT platform for fog computing industrial applications. Computers and Electrical Engineering. 2020; 87: 1-13. https://doi.org/10.1016/j.compeleceng.2020.106770
[9] OpenFog. An OpenFog Architecture Overview. https://www.iiconsortium.org/pdf/OpenFog_ Reference_Architecture_2_09_17.pdf.  Accessed February, 2017.
[10] Brogi A, Forti A. QoS-aware Deployment of IoT Applications Through the Fog. IEEE Internet of Things Journal. 2017; 4:1185-1192. https://doi.org/10.1109/JIOT.2017.2701408.
[11] Taneja M, Davy A. Resource-aware Placement of IoT Application Modules in Fog-Cloud Computing Paradigm. in Proc. of the IFIP/IEEE Symposium on Integrated Network and Service Management. IM ’15. IEEE. 2017; 1222–1228. https://doi.org/10.23919/INM.2017.7987464.
[12] Li F, V ̈ogler M, Claeßens M, Dustdar S. Towards automated iot application deployment by a cloud-based approach. in 6th International Conference on Service-Oriented Computing and Applications. IEEE. 2013; 61–68. https://doi.org/10.1109/SOCA.2013.12.
[13] Mahmud R, Ramamohanarao K, Buyya R. Latency-aware application module Management for fog Computing Environments. ACM Transactions on Internet Technology. 2018; 1–21. https://doi.org/10.1145/3186592.
[14] Vögler M, Schleicher J. M, Inzinger C, Dustdar S. DIANE - Dynamic IoT Application Deployment. IEEE International Conference on Mobile Services. 2015; 298-305. https://doi.org/10.1109/MobServ.2015.49.
[15] Yousefpour A, Patil A, Ishigaki G, Kim I, Wang X, Cankaya H. C, Zhang Q, Xie W, Jue J. P. Fogplan: A lightweight qos-aware dynamic fog service provisioning framework. IEEE Internet of Things Journal. 2019; 6(3): 5080 – 5096. https://doi.org/10.1109/JIOT.2019.2896311.
[16] Canali C, Lancellotti R. Gasp: Genetic algorithms for service placement in fog computing systems. Algorithms. 2019; 12(10): 201. https://doi.org/10.3390/a12100201.
[17] Azizi S, Khosroabadi F, Shojafar M. A priority-based service placement policy for fog-cloud computing systems. Computational Methods for Differential Equations. 2019; 7(4):521–534. 
[18] Guerrero C, Lera I, Juiz C. Evaluation and efficiency comparison of evolutionary algorithms for service placement optimization in fog architectures. Future Generation Computer Systems. 2019; 97: 131–144. https://doi.org/10.1016/j.future.2019.02.056.
[19] Hosseini Shirvani M. Web service composition in multi-cloud environment: a bi-objective genetic optimization algorithm. In 2018 innovations in intelligent systems and applications (INISTA). IEEE. 2018; pp 1–6. https://doi.org/10.1109/INISTA.2018.8466267.
[20] Arcangeli J. P, Boujbel R, Leriche S. Automatic deployment of distributed software systems: Definitions and state of the art. The Journal of Systems and Software. January 2015; 3:198-218. https://doi.org/10.1016/j.jss.2015.01.040.
[21] Dorigo M. Optimization, Learning and Natural Algorithms. PhD thesis, Politecnico di Milano. Italy. 1992.
[22] Teodorović D. Bee Colony Optimization (BCO). In: Lim C.P., Jain L.C., Dehuri S. (eds) Innovations in Swarm Intelligence. Studies in Computational Intelligence. Springer. 2009; 248, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04225-6_3.
[23] Yang X. S. A New Metaheuristic Bat-Inspired Algorithm, in: Nature Inspired Cooperative Strategies for Optimization.  Studies in Computational Intelligence. 2010; 284: 65–74. https://doi.org/10.1007/978-3-642-12538-6_6.
[24] Mirjalili S, Mirjalili S. M, Lewis A. Grey wolf optimizer. Advances in Engineering Software. 2014; 69: 46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007.
[25] Mirjalili S, Lewis A. The whale optimization algorithm. Advances in Engineering Software. 2016; 95: 51-67. https://doi.org/10.1016/j.advengsoft.2016.01.008.
[26] Saeedi, P, Hosseini Shirvani M. An improved thermodynamic simulated annealing-based approach for resource-skewness-aware and power-efficient virtual machine consolidation in cloud datacenters. Soft Comput. 2021. https://doi.org/10.1007/s00500-020-05523-1.
[27] Hosseini Shirvani M. A hybrid meta-heuristic algorithm for scientific workflow scheduling in heterogeneous distributed computing systems. Engineering Applications of Artificial Intelligence. 2020; 90:1–20. https://doi.org/10.1016/j.engappai.2020.103501.
[28] Javadian Kootanaee, A, Poor Aghajan A, Hosseini Shirvani M. A hybrid model based on machine learning and genetic algorithm for detecting fraud in financial statements. Journal of Optimization in Industrial Engineering. 2021; 14(2):183-201. doi: 10.22094/joie.2020.1877455.1685.
[29] Azimi, S., Pahl, C., Hosseijni Shirvani, M.: Performance Management in Clustered Edge Architectures Using Particle swarm optimization. In: Cloud Computing and Services Science. 2021; 1399: 233–257.