Efficient Network Resource Allocation Technique for Dynamic IoT Environment using Reinforcement Learning and CAT Optimization

  • K. Maithili, G. Karthi, K. Thinakaran, M. Sureshkumar, S. Sathya
Keywords: IoT, Surveillance system, Network Resource Management, Sensor, Effective Storage system.

Abstract

To utilize the effeteness of digital, Internet of Things (IoT) has been adopted almost all purposes to quickly complete computable task in compact manner. The applications of IoT purposes are majorly health sector, traffic surveillance, crime detection surveillance, kid’s activity monitoring surveillance, border security monitoring surveillance, and agriculture surveillance. Usually, IoT application is sensing data and transmitting data to processing area remotely in distributed manner. For this activity, IoT based resources allocation is an important task in dynamic environments. These resources even for completing intended task, sometime resources are utilized without rational and hence precise resources are wasted and lose the connectivity also. Thus, in this work, proposed reinforcement learning with CAT Swarm Optimization (RL +CSO) method for effectively allocate the resource in the dynamic environments to direct the application in rational way. The proposed work experiment conducted in different iteration using different resources with the help various parameters such as resource number, allocation time, trail success rate and running time. The proposed work experimental results showed that resources are allocated intended purpose and efficiency has been improved.

Published
2021-09-15
How to Cite
M. Sureshkumar, S. Sathya , K. M. G. K. K. T. (2021). Efficient Network Resource Allocation Technique for Dynamic IoT Environment using Reinforcement Learning and CAT Optimization. Design Engineering, 11799-11815. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/4335
Section
Articles