A novel evolutionary algorithm (MFO) with rate monotonic scheduling for load balancing in LTE advanced networks

Abstract

In recent days, long term evolution (LTE)-advanced is the newest 4G technology. In this cellular network, the femto cells offered a viable and cost-effective method of enhancing the cellular reporting and capability for each WLAN and WiMAX. However, network allocates resource dissimilar to each and every users. To overcome this difficulty, moth flame optimisation (MFO) technique is used to provide equal resource allocation to user. Using this MFO method to balance the load for routing process. Rate-monotonic scheduling (RMS) algorithm is applied to share the load equally to available user, which increases the throughput and control the overload during communication time instance. The simulation results show that the proposed MFO technique has achieved improved network performance than existing hybrid multilevel feedback queue with round robin (HMFQ-RR) and hybrid weighted round robin with shortest job first (HWRR-SJF) in terms to reduce packet loss rate, packet delay and end to end delay.