Analysis of swarm intelligence based approaches to vertical handoff in heterogeneous wireless networks

Abstract

One of the emerging fields of telemedicine is telecardiology, the modern advanced telecommunication systems that supports remote monitoring and diagnosis of symptoms in cardiac patients by medical experts to improve the Quality of Life. The telecommunication system allows transmission of medical data remotely. Such type of system needs the next generation wireless networks involving diverse wireless access technologies to support multimedia services for roaming users. It can support different Quality of Service constraints at anytime and anywhere. One of the challenging issues in heterogeneous wireless environment is the provision of seamless services. Such always-best connected services are offered by seamless vertical handoff process. Therefore, it requires designing an optimal vertical handoff decision algorithm to select an optimal network among the available alternatives to ensure the seamless services. The research thesis is focused in designing and implementing vertical handoff algorithms employing Intuitionistic Fuzzy Technique for Order Preferences by Similarity to an Ideal Solution Multi-Attribute Decision Making algorithm along with optimization algorithms. The weight values of the criteria play a crucial role in handoff decision. Hence, Hybrid Particle Swarm Optimization, Improved Particle Swarm Optimization and Hybrid Genetic-Cuckoo Search algorithms have been employed for calculating the weight values of the criteria. These algorithms overcome the drawbacks of manual assignment of weight values. The goal of the proposed methodologies is to reduce the number of handoff events, blocking rate and processing delay. These approaches enhance throughput and ensure secure transmission over the selected network. The proposed vertical handoff decision algorithms have been implemented and analysed in telecardiology system to monitor the patient health condition in the selection of optimal network. newline