The Utility based AHP& TOPSIS Methods for Smooth Handover In Wireless Networks

1Maharaja Agrasen University, Student, Pin code: 174103, Baddi, India 2Maharaja Agrasen University, Assistant Professor, Pin code: 174103, Baddi, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract – The Utility based AHP & TOPSIS methods for smooth handover in wireless networks is presented in this paper. In the future, people have even more flexibility when true wireless internet and real-time multimedia are provided seamlessly over heterogeneous wireless network. Also, various applications demand different quality of service (QoS) parameters. The goal is to select the best network that can support the required service(s) and avoid excessive switching among different networks in order to minimize service interruptions and power consumption. The vertical handover scheme is proposed for conversational, streaming and interactive applications. In this multihierarchy decision making process the best suited Analytical Hierarchy Process(AHP) is applied for the decision making process in vertical handover. The proposed scheme of vertical handoff provides higher QoS than the earlier than the earlier algorithms. All the unnecessary vertical handover we controlled by proposed scheme. The results show that the proposed scheme provides low traffic applications and overall system throughput with a control of unnecessary handoffs for all kinds of services. Also, parameterized utility functions are used to model the different Quality of Service (QoS) attributes (data rate, delay, jitter, ) and user preferences (cost) for three different types of applications. Finally, scores are calculated exclusively for each network by two MADM (Multiple Attribute Decision Making) methods , TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) and AHP (Analytic hierarchy process). A single-criterion utility function that rates user satisfaction and captures sensitivity for each decision criterion. As well, an adaptive multi-criteria utility function is defined according to user preferences. Obtained results show that our strategy outperforms other handover decision schemes, which confirm the suitability and the efficiency of our solution.