Adaptive Optimized Open Shortest Path First Algorithm using Enhanced Moth Flame Algorithm

Abstract

Objective: To builds up a versatile algorithm in view of Open Shortest Path First (OSPF) algorithm by using improved moth flame optimization. The designed algorithm gives the upgraded performance even with dynamic topology. Methods/Statistical Analysis: The optimized OSPF algorithm utilizes the directing conduct of moth to exchange the information from source to destination. The optimized OSPF algorithm performs well however the execution debases with frequently change in topology. This work upgrades the optimized OSPF by changing the path of moth based on the delay parameter. Additionally, the neighbor determination criteria have been changed to diminish the delay. Findings: The analysis of the adaptive optimized OSPF algorithm for the dynamic network has been finished by utilizing delay and energy consumption. The performance of the outlined algorithm is done with existing OSPF, modified OSPF and the optimized OSPF algorithm. The reduced delay and energy consumption as contrasted with optimized OSPF and OSPF based algorithms demonstrates the significance of algorithm. Application/Improvements: The adaptive optimized OSPF can be used for routing for the dynamic networks. The algorithm can be utilized where dependable information conveyance is required with least deferral.