An Effective Handoff Algorithm Using Modified Cat Swarm Behavior Based Optimization in Heterogeneous Wireless Mobile Networks

In wireless system environment, optimal vertical handoff is a challenging issue. In this paper, a Modified Cat Swarm Behavior based Optimization (MCSBO) based handoff algorithm is proposed in heterogeneous wireless mobile network to reduce handoff. Initially, resource-poor mobile nodes, and resource-rich mobile nodes are clustered using Modified Expectation Maximization (MEM) to reduce the handoffs efficiently. Here, parameters like packet loss rate, dynamic new calls blocking probability, Bandwidth, and Cost along with the velocity of the Mobile Terminal (MT) are considered for the design of the Handoff algorithm. The Membership Functions (MFs) for each of the parameter are determined and corresponding Membership Degrees are evaluated from their concerned MFs. The optimized fuzzification of the parameters is obtained via developing the appropriate weight vector. The weight vector is optimized using MCSBO algorithm. Experimental results show that the proposed algorithms attained best performance bandwidth utilization, handoff dropping rate and handoff rate compared to existing handoff decision vector algorithms.