Data Optimization in Cloud-IOT Environment with Enhanced SVM Technique
Souvik Pal, Noor Zaman Jhanjhi, D. Akila, Mehedi Masud, Saira Muzzaffar, Gaurav Kumar, Rajan Verma · 2024
The number of people using smart devices is growing exponentially, and this is resulting in a rise in the volume of data being generated from different smart devices. This data is different from big data in terms of all the key classification approaches. The massive amount of data that several connected devices generate causes major performance problems for an Internet of Things system. Edge-cloud computing and networking function virtualization (NFV) approaches are two potential ways to improve resource usage and the flexibility of responsive services in an IoT system. A data optimization technique in a cloud environment is proposed in this paper and also to access the data with state-of -art methodologies. The proposed method in evaluated by terms of performance ratios, reliability percentage, coverage ratios, and sensing error. And the proposed model outperforms the state-of art method with mean performance ratio of 79.2