A novel optimized resource management model for software defined future mobile networks

Abstract

Extreme densities are an important factor in future mobile networks that can provide very high data rate to mobile users. It also increases complexity in handover decisions and resource management. However, SDNs (softwaredefined networks) and mobility models can provide seamless mobility and efficient resource management in heterogeneous mobile environment, and ensure QoS (quality of service) is achieved. The paper proposes SDN based on GMM (Group Mobility Model) called MoMo, and resource management using MLOAs (mutation lion optimization algorithms) are used to alleviate handover and addressing issues in network congestion. The proposed method is based on SDN controllers working in global perspectives for achieving required network conditions and end user QoSs. SDN with GMM-MoMo-MLOA offer transparent and dynamic support for sessions during handoffs and thus eliminates congestion overheads and packet losses related to mobile traffic, resulting in improved QoS for mobile users. The performance analysis through experiments depicts that the proposed model gives enhanced performance when compared to that of the other conventional methods and also has proven efficiency in terms of other parameters such as handover latency, signaling cost, throughput, and packet loss. The results from the simulation show that the proposed method SDN-GMM-MoMo-MLOA greatly improves the performance of network and also maintains optimum resource utilization and efficiency. K E Y W O R D Sfuture mobile networks, group mobility management (GMM), handover, MoMo model, mutation lion optimization algorithm (MLOA), quality of service (QoS), software defined network (SDN)