International Journal of Computer Applications (0975 – 8887) Volume 51– No.1, August 2012 22 Probability Modeling of Multi Node Wireless Networks Suresh R. Halhalli Associate Professor M.S Bidve Engineering College, Latur (MS)-India Subhash Kulkarni Principal, J.P.N College of Engineering Mahabubnagar (AP)-India K.S.R Anjaneyulu Director i/c, R & D Cell JNTUA Anantapur (AP)-India S. Akhila Associate Professor, BMS College of Engineering, Bangalore (KS)-India ABSTRACT In this work, probability equations are derived for the five node networks and the probabilities are computed for unnecessary handover, missing handover and wrong decisions. Wrong decision probability is the summation of unnecessary and missing handover probabilities. Also, the handover probability is computed for the bandwidths up to 20. The modeling is based on the five state Morkov chain model. Simulations are carried out for the different decision times from D=1 to D=5 ms. The simulation results for the five node network model is compared with the two node and three node network models. Keywords Wrong Decision Probability, Missing Handovers, Unnecessary handovers. 1. INTRODUCTION Vertical handover is very popular in the field of wireless communication due to the versatility it provides. Connectivity switching from a serving network to a candidate network [1] may be called as a vertical handover. Usually the parameters like received Signal Strength (RSS) [1], link-layer parameters such as bandwidth, delay, signal-to-noise ratio [2], as well as quality of service (QoS) [3] are used in the decision making of vertical handover. An overview of main decision metrics is described in [4]. The number of vertical handovers is another performance issue [5] and is a big limitation in this case. Mobile terminal’s battery life and the quality of service level is affected due to “ping pong effect” which may described as the switch over of mobile terminal repeatedly between two access network. There are several techniques available to limit vertical handovers, and hence the ping-pong effect [6, 7]. Handover probability modeling is gaining popularity and vertical handover analytical methods based on handover probability are explained in [8-9]. Wrong decision probability modeling for vertical handover decision is presented in [10]. In ref [10] authors adopted the wrong decision probability as a metric for vertical handover decision based on network parameters and one such metric used in this case was bandwidth. Wrong decision probability is also assumed as a performance metric for the proposed algorithms. The wrong decision probability is based on maximum capacity and available bandwidth from a candidate network. Wrong decision probabilities are evaluated for a sample capacity and available bandwidth and it is not the scope of the present work how wrong decision probability affects mobile terminal’s performances in terms of Quality of Service. In [11], wrong decision probability, unnecessary handover probability and missing handover probability models are used to predict the probabilities for different decision times and large bandwidth channels. The probability equations are derived in [11] was based on a two node network model. The traffic load of each network was varied based on the maximum band width available in the network node located in busy areas of cities and the probabilities of the handover, missing handover and unnecessary handovers are computed. Simulated results are presented for large bandwidth cases as well as for different decision times and important conclusions are drawn. In [12] wrong decision probability modeling has been used to predict the probabilities of missing handovers and unnecessary handovers for different decision times, different bandwidths and larger number of available networks for performing handover leading to an increase in the throughput. The focus is laid on minimization of wrong decision probability. There is significant improvement in the reduction of wrong decision making when two network models is replaced by a three network model and also the ping-pong effect caused due to unnecessary handoff has been reduced which indicates that with increase in choice of neighboring networks effect of wrong decision probability can be minimized but with an obvious tradeoff between cost and number of networks. Further, parameters like Signal Strength and Mobility is considered for analyzing the effect of wrong decision probability on handover decision algorithms. In [13] the performance of a bandwidth, signal strength and bandwidth plus signal strength based handover algorithms for wrong decisions were studied. The simulated results show that considering both signal strength and network bandwidth is more advantageous to the network operator due to the reduction in the number of wrong decisions. Making handover decisions based on the predication method called wrong decision probability can provide better performance of the algorithm. In this work, Wrong Decision Probability models are used to predict the probabilities for five node networks. Additionally, Handover Probability, Missing Handover Probabilities and Unnecessary Handover Probabilities are computed for a general algorithm based on the performance criteria “bandwidth”. In this work, wrong decision probability models are used to predict the probabilities of missing handovers and unnecessary handovers for different decision times. The results of the five node network model are compared with the two and three node network models presented in [11-13]. Next section present the mathematical models used in the analytical formulations. Section III describes the general algorithms used and section IV, V and VI explains the simulated results based on MATLAB coding. Finally important conclusions are drawn in section VII.