Izvorni znanstveni članak
https://doi.org/10.32985/ijeces.14.4.7
An Intelligent Server load balancing based on Multi-criteria decision-making in SDN
K. A. Vani
; Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Visveshwaraya Technological University, Bangalore, India
K. N. RamaMohanBabu
; Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Visveshwaraya Technological University, Bangalore, India
Sažetak
In an environment of rising internet usage, it is difficult to manage network traffic while maintaining a high quality of service. In highly trafficked networks, load balancers are crucial for ensuring the quality of service. Although different approaches to load-balancing have been proposed in traditional networks, some of them require manual reconfiguration of the device to accommodate new services due to a lack of programmability. These problems can be solved through the use of software-defined networks. This research paper presents a dynamic load-balancing algorithm for software-defined networks based on server response time and content mapping. The proposed technique dispatches requests to servers based on real-time server loads. This technique comprises three different modules, such as a request classification module, a server monitoring module, and an optimized dynamic load-balancing module using content-based routing. There are a variety of robust mathematical tools to address complex problems that have multiple objectives. Multi-Criteria Decision-Making is one of them. The performance of the proposed scheme has been validated by applying the Weighted Sum Method of the multi-criteria decision-making technique. The proposed method Server load balancing based on Multi-criteria Decision Making[SDLB-MCDM] is compared with different load-balancing schemes such as round robin, random, load-balancing scheme based on server response time [LBBSRT], and An SDN-aided mechanism for web load- balancing based on server statistics [SD-WLB]. The experimental results of SDLB-MCDM show a significant improvement of 58% when weights are equal and 50% when unequal weights are assigned to various QoS parameters in comparison with the ROUND ROBIN, RANDOM, LBBSRT and SD-WLB techniques.
Ključne riječi
Quality of Service; Software-Defined Networks; Load-Balancing; Open Flow;
Hrčak ID:
300947
URI
Datum izdavanja:
26.4.2023.
Posjeta: 605 *