Performance Analyze of Fog Computing Against Topology Using YAFS Fog Simulator
DOI:
10.33395/sinkron.v8i3.12659Keywords:
Fog Computing; YAFS; Star Topology; Mesh Topology; Ring TopologyAbstract
This research focuses on the analysis of fog computing performance on mesh, star, and ring topologies using the YAFS Fog Simulator. The reason YAFS (Yet Another Fog Simulator) was chosen was based on the consideration that this fog computing simulator, among other things, was designed to analyze topology and load balancing as well as include processing time for data transfer between devices into the fog layer. In addition, YAFS has a better level of time processing accuracy than other fog simulators. There are three test scenarios with additional load which includes 4, 8, and 12 fog nodes in each topology. Each scenario also has an additional load which includes 4, 8, and 12 devices in the form of sensors and actuators, respectively. The experimental results from the three scenarios show that the greater the load from the fog node and equipment, the longer the processing time will be. In addition, the results of the three scenarios also show that the mesh topology has the best time processing accuracy among the three tested topologies.
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Margariti, S., Dimakopoulos, V. and Tsoumanis, G. (2020). Menjaga Kerahasiaan Data dengan Steganografi Modeling and Simulation Tools for Fog Computing—A Comprehensive Survey from a Cost Perspective. Future Internet, 12(5), p.89. https://doi.org/10.3390/fi12050089
Neware, R. (2019). Fog Computing Architecture, Applications and Security Issues: A Survei. https://doi.org/10.20944/preprints201903.0145.v1
Singh, J., Singh, P. and Gill, S. (2021). Fog computing: A taxonomy, systematic review, current trends and research challenges. Journal of Parallel and Distributed Computing, 157, pp.56-85. https://doi.org/10.1016/j.jpdc.2021.06.005
Abdali, T., Hassan, R., Aman, A. and Nguyen, Q. (2021). Fog Computing Advancement: Concept, Architecture, Applications, Advantages, and Open Issues. IEEE Access, 9, pp.75961-75980.
H., S. and V., N. (2021). A Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges. ICT Express, 7(2), pp.162-176. https://doi.org/10.1016/j.icte.2021.05.004
Rabay’a, A., Schleicher, E. and Graff, K., 2019. Fog computing with P2P: enhancing fog computing bandwidth for IoT scenarios. 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber,
Physical and Social Computing (CPSCom) andIEEE Smart Data (SmartData), pp.82-89. https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00036
Shahzad, M., Panneerselvam, J., Liu, L. and Zhai, X. (2020). Data Aggregation Challenges in Fog Computing. 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation, pp.1717-1721. https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00306
Goudarzi, M., Wu, H., Palaniswami, M. and Buyya, R. (2021). An Application Placement Technique for Concurrent IoT Applications in Edge and Fog Computing Environments. IEEE Transactions on Mobile Computing, 20(4), pp.1298-1311.
Dlamini, S. and Ventura, N. (2019). Resource Management in Fog Computing: Review. IEEE.
Lera, I., Guerrero, C. and Juiz, C. (2019). YAFS: A Simulator for IoT Scenarios in Fog Computing. IEEE Access, 7, pp.91745-91758.
Nurlan, Z., Kokenovna, T., Othman, M. and Adamova, A. (2021). Resource Allocation Approach for Optimal Routing in IoT Wireless Mesh Networks. IEEE Access, 9, pp.153926-153942.
Brandao, A., Lima, M., Abbas, C. and Villalba, L. (2020). An Energy Balanced Flooding Algorithm for a BLE Mesh Network. IEEE Access, 8, 24 pp.97946-97958.
Permana, I., Abdurohman, M. and Putrada, A. (2020). Comparative Analysis of Mesh and Star Topologies in Improving Smart Fire Alarms. IEEE.
Rokhayah, R. and Syambas, N. (2020). A Heuristic Algorithm for Ring Topology Optimization Rokhayah School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung, Indonesia. IEEE.
Fahimullah, M., Phillippe, G., Ahvar, S. and Trocan, M., 2023. Simulation Tools for Fog Computing: A Comparative Analysis. Sensors, 23. https://doi.org/10.3390/s23073492
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