Seamless vertical handoff using modified weed optimization algorithm for heterogeneous wireless networks

Abstract

In the global scenario, a variety of wireless access networks are available. Different types of applications such as real time, nonreal time, and high bandwidth availability are used for heterogeneous wireless networks. Therefore, it is necessary for a service provider to make an appropriate connection support. For better performance, connections are to be exchanged among the different networks using seamless vertical handoff (VHO). The proposed algorithm shows the effect of optimization technique, which involves handoff decision process using vertical handoff triggering and selection of the network. The handoff triggering is initiated by using the received signal strength (RSS). In traditional method, handoff triggering is initiated by using RSS only. This method, modified weed optimization (M-WO) algorithm, reduces the unnecessary handoff by considering both RSS and velocity of the mobile node in handoff triggering. The parameters such as battery lifetime, handoff call dropping rate, load, dynamic weights adaptation and so on are to be considered individually or combined to make an effective network selection process. This paper highlights a novel effect ofM-WOalgorithm for decision making during the VHO. Our effort is to essentially optimize the system load, so that it reduces the handoff call dropping rate and the battery power consumption of the mobile node (MN). Weight of each QoS metrics is adjusted along with the networks changing conditions to trace the M-WO. Therefore, the novel VHO decision-making algorithm is superior to the existing SSF and OPTG methods. The simulation results show that the performance ofM-WOalgorithm is far better than SSF andOPTGmethods in terms of load, handoff call dropping rate and battery lifetime of MN.