Method оf Load Balancing іn Distributed Three-Layer IoТ Architecture
DOI:
https://doi.org/10.20535/2786-8729.4.2024.311595Keywords:
load balancing, Internet of Things, Edge computing, ZabbixAbstract
Due to the growing number of IoT devices and the need for fast data processing with minimal delays, traditional cloud computing is becoming less efficient. To solve this problem, the concept of edge computing is used, which, although it increases performance, complicates system management and requires effective load distribution to ensure a balance between the use of edge nodes and the speed of computation. The purpose of this work was to develop a method of load balancing in the three-layer architecture of the IoT system, taking into account the actual loading of nodes.
A review of the literature was conducted and an architectural concept was chosen that corresponds to new trends and consists of three layers: devices that generate data, edge nodes that process information, and the cloud that stores data and provides it to users. A system prototype was created, which includes several Edge nodes based on the Ubuntu Server 24.04 operating system and data servers based on Raspberry Pi Desktop. A mathematical model has been developed that allows you to estimate the load on nodes depending on the type of tasks performed. On the created prototype, the efficiency of the method was checked using a mathematical model.
The research results showed that the developed method successfully distributes the load between Edge-nodes with the help of special scripts and elements of the monitoring system, which is reflected in the server load graph. The proposed method can improve system performance due to automatic load distribution among nodes. This approach can become part of a more comprehensive strategy to improve the performance and reliability of IoT systems using edge computing. Using components of the monitoring system for different platforms with different power allows to reduce the cost of the system by using cheaper and less powerful computing devices.
References
I. Klymenko, A. Gaidai, S. Nikolskyi, V. Tkachenko, "The Architectural Concept Of The Monitoring System On The Basis On A Neuron Module IoT Data Analytics", Adaptive systems of automatic control, p. 111-123, 2022, https://doi.org/10.20535/1560-8956.41.2022.271355
M. Shuaib, S. Bhatia, S. Alam, R. K. Masih, N. Alqahtani, S. Basheer, and M. S. Alam, "An Optimized, Dynamic, and Efficient Load-Balancing Framework for Resource Management in the Internet of Things (IoT) Environment," Electronics, vol. 12, no. 5, pp. 1104, 2023. https://doi.org/10.3390/electronics12051104.
N. Shivaraman, J. Fittler, S. Ramanathan, A. Easwaran and S. Steinhorst, "WiP Abstract: Mobility-based Load Balancing for IoT-enabled Devices in Smart Grids," 2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS), Sydney, NSW, Australia, 2020, pp. 192-193, https://doi.org/10.1109/ICCPS48487.2020.00029.
H. Tseng, "Multipath Load Balancing Routing for Internet of Things," Journal of Sensors, vol. 2016, pp. 1-8, 2016. https://doi.org/10.1155/2016/4250746.
D. Kanellopoulos and V. K. Sharma, "Dynamic Load Balancing Techniques in the IoT: A Review," Symmetry, vol. 14, no. 12, p. 2554, 2022. https://doi.org/10.3390/sym14122554.
K. Devi, D. Sumathi, V. Venkataraman, A. Chunduru, K. Kataraki, and S. Balakrishnan, "CLOUD load balancing for storing the internet of things using deep load balancer with enhanced security," Measurement: Sensors, vol. 28, p. 100818, 2023. https://doi.org/10.1016/j.measen.2023.100818.
Z. Eghbali and M. Zolfy Lighvan, "A hierarchical approach for accelerating IoT data management process based on SDN principles," Journal of Network and Computer Applications, vol. 181, p. 103027, 2021. https://doi.org/10.1016/j.jnca.2021.103027.
E. Hajian, M. R. Khayyambashi and N. Movahhedinia, "A Mechanism for Load Balancing Routing and Virtualization Based on SDWSN for IoT Applications," in IEEE Access, vol. 10, pp. 37457-37476, 2022, https://doi.org/10.1109/ACCESS.2022.3164693.
M. R. Belgaum, S. Musa, M. M. Alam and M. M. Su’ud, "A Systematic Review of Load Balancing Techniques in Software-Defined Networking," in IEEE Access, vol. 8, pp. 98612-98636, 2020, https://doi.org/10.1109/ACCESS.2020.2995849.
N. Hassan, S. Gilani, E. Ahmed, I. Yaqoob, and M. Imran, "The Role of Edge Computing in Internet of Things," IEEE Communications Magazine, vol. PP, 2018. https://doi.org/10.1109/MCOM.2018.1700906.
Zabbix Documentation, Zabbix, 2023. [Online]. Available: https://www.zabbix.com/documentation/current/en/manual. [Accessed: Sep. 4, 2024].
