Automatic IP Configuration and Duplicate Node Detection Using Improved Extreme Learning Machine Based Hunger Games Search

Abstract

One of the challenging issues in mobile ad hoc networks (MANET) is IP address auto reconfiguration thereby ensuring best routing. Generally, the stateful and stateless are two classes of IP address reconfiguration protocols. Addresses must be unique, and address conflicts must be avoided. In this study, we have proposed Hunger Games Search (HGS) algorithm based Improved Extreme Learning Machine (IELM) named as HGS-IELM framework for IP address auto reconfiguration in MANET. The fresh read based on each access is ensured using HGS-IELM voting enforces. The cooperation among both data consistency and message overhead is made. There is no involvement of the central server and the proposed HGS-IELM method is scalable. Based on the experimental studies, the proposed HGS-IELM framework accomplished less message overhead as well as lower latency. By keeping suitable redundancy, the proposed HGS-IELM method demonstrated improved availability of address.