Mobility management is one of the most important challenges in Next Generation Wireless Networks (NGWNs) as it enables users to move across geographic boundaries of wireless networks. Nowadays, mobile communications has heterogeneous wireless networks offering variable coverage and Quality of Service (QoS). The availability of alternatives generates a problem of occurrence of unnecessary handoff that results in wastage of network resources. To avoid this, an efficient algorithm needs to be developed to minimize the unnecessary handoffs. Conventionally, whenever a Wireless Local Area Network (WLAN) connectivity is available, the mobile node switch from the cellular network to wireless local area network to gain maximum use of high bandwidth and low cost of wireless local area network as much as possible. But to maintain call quality and minimum number of call failure, a considerable proportion of these handovers should be determined. Our algorithm makes the handoff to wireless local area network only when the Predicted Received Signal Strength (PRSS) falls below a threshold value and travelling distance inside the wireless local area networkis larger than a threshold distance. Through MATLAB simulation, we show that our algorithm minimizes the probability of unnecessary handoff, and probability of handoff failure. Hence, the proposed algorithm is able to improve handover performance.

In the real world, most of the applications are inherently dynamic in nature i.e. their underlying data distribution changes with time. As a result, the concept drifts occur very frequently in the data stream. Concept drifts in data stream increase the challenges in learning as well, it also significantly decreases the accuracy of the classifier. However, recently many algorithms have been proposed that exclusively designed for data stream mining while considering drifting concept in the data stream.This paper presents an empirical evaluation of these algorithms on datasets having four possible types of concept drifts namely; sudden, gradual, incremental, and recurring drifts.

Since the last few decades, tremendous innovations and inventions have been observed in every field, but especially in wireless network technology. The prevailing demand curves and trends in this particular area of communication show the importance of real-time multimedia applications over several networks with guaranteed quality of service (QoS). The Next Generation Wireless Network (NGWN) consists of heterogeneous wireless networks that will grant high data rate and bandwidth to mobile users. The primary aim of Next Generation Wireless Network (NGWN) is to conceal heterogeneities and to achieve convergence of diverse networks to provide seamless mobility. So that mobile user can move freely between networks without losing the connection or changing the setting at any moment. When the mobile user moves between different networks, there is a requirement to handover the channel, from one network to another by considering its services, features and user preferences. Channel handover between two different networks is done with the help of vertical handoff (VHO). In a heterogeneous environment, numerous technologies co-exist with their unique characteristics. Therefore, it is very difficult to design efficient handoff decision algorithm. The poorly designed handoff algorithm tends to increase the traffic load and, thereby tend to dramatic decrease in quality of service. A mobile node equipped with multiple network interfaces will be able to access heterogeneous wireless access network. But the availability of alternatives give rise to a problem of unnecessary handoff. To avoid this, we have proposed a decision algorithm based on predictive received signal strength, hysteresis margin and dwell time to select an optimum target network. The handoff policies are designed using received signal strength (RSS), available bandwidth, service cost, user preference, type of application and network condition to reduce the number of handoffs, decision delay, probability of handoff failure and probability of unnecessary handoff. We have also made a comparative analysis of various vertical handoff decision algorithms in this paper.

Next generation wireless network (NGWN) is a mixture of various heterogeneous technology. It allows the global information access to the user while moving from one network to another. The challenging issue in NGWNs to design an intelligent vertical handoff decision algorithm beyond traditional one. The traditional algo-rithms are based on signal strength only to determine the right time and right network. But, these algorithms have a large number of unnecessary handoff due to fluctuating RSS. Although, the number of unnecessary handoffs can be reduced by an RSS with hysteresis margin scheme. But these algorithms increases the risk of high dropping and low utilization. Therefore, the aim of our research is to develop a vertical handoff decision algorithm that can select an optimum target network based on bandwidth requirement, battery power, cost of service, network per-formance and network condition. By the implementation of our algorithm, we can provide a mechanism that can select the best network at the appropriate time and pro-vides the uninterrupted services to mobile users, that al-lows connectivity between universal mobile telecommu-nication system (UMTS) and wireless local area network (WLAN). The inclusion of hysteresis margin and dwell time in predicted RSS helps in reducing the early handoff, ping pong effect, decision delay and utilization rate.