A hybrid approach for fault-tolerance aware load balancing in fog computing

被引:5
作者
Kashyap, Vijaita [1 ]
Ahuja, Rakesh [1 ]
Kumar, Ashok [2 ]
机构
[1] Chitkara Univ, Chitkara Univ Inst Engn & Technol, Rajpura, Punjab, India
[2] Lovely Profess Univ, Sch Comp Applicat, Phagwara, Punjab, India
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2024年 / 27卷 / 04期
关键词
Fog computing; Fault tolerance; Modified Harris-hawks optimization; Ant colony optimization; JOB MIGRATION; OPTIMIZATION; ALGORITHM; CLOUD;
D O I
10.1007/s10586-023-04219-z
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fog computing has grown in popularity in recent years because to its potential to deliver real-time processing, low latency, and reduce network congestion. However, the implementation of Internet of Things (IoT) enabled smart devices in environments using fog computing may lead to resource limitations and higher computational demands. Load balancing and fault tolerance strategies are necessary to tackle these difficulties for optimal resource usage and system availability. In order to accomplish fault tolerance aware load balancing in fog computing, a hybrid meta-heuristic approach that combines the Modified Harris-Hawks Optimization (MHHO) and Ant Colony Optimization (ACO) is proposed through this paper. The MHHO algorithm is utilized for load balancing, whereas the ACO algorithm is used for fault tolerance. By employing the proposed technique, the load on fog nodes is balanced, the makespan time is minimized, energy consumption and execution costs are minimized, and fault tolerance in fog computing environments is ensured. It is evaluated using a simulation framework built on the iFogSim toolkit. In terms of load balancing, fault tolerance, and other factors, the results of the experiments show that the suggested hybrid algorithm performs better than earlier state-of-the-art methods.
引用
收藏
页码:5217 / 5233
页数:17
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