Mobility-based predictive call admission control and resource reservation for next-generation mobile communications networks.

Recently, the need for wireless and mobile communications has grown tremendously and it is expected that the number of users to be supported will increase with high rates in the next few years. Not only the number of users, but also the required bandwidth to support each user is supposed to increase especially with the deploying of the multimedia and the real time applications. This makes the researchers in the filed of mobile and wireless communications more interested in finding efficient solutions to solve the limitations of the available natural radio resources. One of the important things to be considered in the wireless mobile environment is that the user can move from one location to another when there is an ingoing call. Resource reservation ( RR ) schemes are used to reserve the bandwidth ( BW ) required for the handoff calls. This will enable the user to continue his/her call while he/she is moving. Also, call admission control ( CAC ) schemes are used as a provisioning strategy to limit the number of call connections into the network in order to reduce the network congestion and the call dropping. The problem of CAC and RR is one of the most challenging problems in the wireless mobile networks. Also, in the fourth generation ( 4G ) of mobile communication networks, many types of different mobile systems such as wireless local area networks ( WLAN s) and cellular networks will be integrated. The 4G mobile networks will support a broad range of multimedia services with high quality of service.New Call demission control and resource reservation techniques are needed to support the new 4G systems. Our research aims to solve the problems of Call Admission Control (CAC), and resource reservation (RR) in next-generation cellular networks and in the fourth generation (4G) wireless heterogeneous networks. In this dissertation, the problem of CAC and RR in wireless mobile networks is addressed in detail for two different architectures of mobile networks: (1) cellular networks, and (2) wireless heterogeneous networks (WHNs) which integrate cellular networks and wireless local area networks (WLANs). We have designed, implemented, and evaluated new mobility-based predictive call admission control and resource reservation techniques for the next-generation cellular networks and for the 4G wireless heterogeneous networks. These techniques are based on generating the mobility models of the mobile users using one-dimensional and multidimensional sequence mining techniques that have been designed for the wireless mobile environment. The main goal of our techniques is to reduce the call dropping probability and the call blocking probability, and to maximize the bandwidth utilization n the mobile networks. By analyzing the previous movements of the mobile users, we generate local and global mobility profiles for the mobile users, which are utilized effectively in prediction of the future path of the mobile user. Extensive simulation was used to analyze and study the performance of these techniques and to compare its performance with other techniques. Simulation results show that the proposed techniques have a significantly enhanced performance which is comparable to the benchmark techniques

Predictability of Wlan Mobility and Its Effects on Bandwidth Provisioning

Wireless local area networks (WLANs) are emerging as a popular technology for access to the Internet and enterprise networks. In the long term, the success of WLANs depends on services that support mobile network clients. \par Although other researchers have explored mobility prediction in hypothetical scenarios, evaluating their predictors analytically or with synthetic data, few studies have been able to evaluate their predictors with real user mobility data. As a first step towards filling this fundamental gap, we work with a large data set collected from the Dartmouth College campus-wide wireless network that hosts more than 500 access points and 6,000 users. Extending our earlier work that focuses on predicting the next-visited access point (i.e., location), in this work we explore the predictability of the time of user mobility. Indeed, our contributions are two-fold. First, we evaluate a series of predictors that reflect possible dependencies across time and space while benefiting from either individual or group mobility behaviors. Second, as a case study we examine voice applications and the use of handoff prediction for advance bandwidth reservation. Using application-specific performance metrics such as call drop and call block rates, we provide a picture of the potential gains of prediction. \par Our results indicate that it is difficult to predict handoff time accurately, when applied to real campus WLAN data. However, the findings of our case study also suggest that application performance can be improved significantly even with predictors that are only moderately accurate. The gains depend on the applications\u27 ability to use predictions and tolerate inaccurate predictions. In the case study, we combine the real mobility data with synthesized traffic data. The results show that intelligent prediction can lead to significant reductions in the rate at which active calls are dropped due to handoffs with marginal increments in the rate at which new calls are blocked

QoS Provisioning for Multi-Class Traffic in Wireless Networks

Physical constraints, bandwidth constraints and host mobility all contribute to the difficulty of providing Quality of Service (QoS) guarantees in wireless networks. There is a growing demand for wireless networks to support all the services that are available on wired networks. These diverse services, such as email, instant messaging, web browsing, video conferencing, telephony and paging all place different demands on the network, making QoS provisioning for wireless networks that carry multiple classes of traffic a complex problem. We have developed a set of admission control and resource reservation schemes for QoS provisioning in multi-class wireless networks. We present three variations of a novel resource borrowing scheme for cellular networks that exploits the ability of some multimedia applications to adapt to transient fluctuations in the supplied resources. The first of the schemes is shown to be proportionally fair: the second scheme is max-min fair. The third scheme for cellular networks uses knowledge about the relationship between streams that together comprise a multimedia session in order to further improve performance. We also present a predictive resource reservation scheme for LEO satellite networks that exploits the regularity of the movement patterns of mobile hosts in LEO satellite networks. We have developed the cellular network simulator (CNS) for evaluating call-level QoS provisioning schemes. QoS at the call-level is concerned with call blocking probability (CBP), call dropping probability (CDP), and supplied bandwidth. We introduce two novel QoS parameters that relate to supplied bandwidth—the average percent of desired bandwidth supplied (DBS), and the percent of time spent operating at the desired bandwidth level (DBT)

Mobile Networks

The growth in the use of mobile networks has come mainly with the third generation systems and voice traffic. With the current third generation and the arrival of the 4G, the number of mobile users in the world will exceed the number of landlines users. Audio and video streaming have had a significant increase, parallel to the requirements of bandwidth and quality of service demanded by those applications. Mobile networks require that the applications and protocols that have worked successfully in fixed networks can be used with the same level of quality in mobile scenarios. Until the third generation of mobile networks, the need to ensure reliable handovers was still an important issue. On the eve of a new generation of access networks (4G) and increased connectivity between networks of different characteristics commonly called hybrid (satellite, ad-hoc, sensors, wired, WIMAX, LAN, etc.), it is necessary to transfer mechanisms of mobility to future generations of networks. In order to achieve this, it is essential to carry out a comprehensive evaluation of the performance of current protocols and the diverse topologies to suit the new mobility conditions

Regressive Prediction Approach to Vertical Handover in Fourth Generation Wireless Networks

The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A) environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS)/Access Points (APs) in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM) where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities) were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency

Evaluating Mobility Predictors in Wireless Networks for Improving Handoff and Opportunistic Routing

We evaluate mobility predictors in wireless networks. Handoff prediction in wireless networks has long been considered as a mechanism to improve the quality of service provided to mobile wireless users. Most prior studies, however, were based on theoretical analysis, simulation with synthetic mobility models, or small wireless network traces. We study the effect of mobility prediction for a large realistic wireless situation. We tackle the problem by using traces collected from a large production wireless network to evaluate several major families of handoff-location prediction techniques, a set of handoff-time predictors, and a predictor that jointly predicts handoff location and time. We also propose a fallback mechanism, which uses a lower-order predictor whenever a higher-order predictor fails to predict. We found that low-order Markov predictors, with our proposed fallback mechanisms, performed as well or better than the more complex and more space-consuming compression-based handoff-location predictors. Although our handoff-time predictor had modest prediction accuracy, in the context of mobile voice applications we found that bandwidth reservation strategies can benefit from the combined location and time handoff predictor, significantly reducing the call-drop rate without significantly increasing the call-block rate. We also developed a prediction-based routing protocol for mobile opportunistic networks. We evaluated and compared our protocol\u27s performance to five existing routing protocols, using simulations driven by real mobility traces. We found that the basic routing protocols are not practical for large-scale opportunistic networks. Prediction-based routing protocols trade off the message delivery ratio against resource usage and performed well and comparable to each other

Comparison of vertical handover decision-based techniques in heterogeneous networks

Industry leaders are currently setting out standards for 5G Networks projected for 2020 or even sooner. Future generation networks will be heterogeneous in nature because no single network type is capable of optimally meeting all the rapid changes in customer demands. Heterogeneous networks are typically characterized by some network architecture, base stations of varying transmission power, transmission solutions and the deployment of a mix of technologies (multiple radio access technologies). In heterogeneous networks, the processes involved when a mobile node successfully switches from one radio access technology to the other for the purpose of quality of service continuity is termed vertical handover or vertical handoff. Active calls that get dropped, or cases where there is discontinuity of service experienced by mobile users can be attributed to the phenomenon of delayed handover or an outright case of an unsuccessful handover procedure. This dissertation analyses the performance of a fuzzy-based VHO algorithm scheme in a Wi-Fi, WiMAX, UMTS and LTE integrated network using the OMNeT++ discrete event simulator. The loose coupling type network architecture is adopted and results of the simulation are analysed and compared for the two major categories of handover basis; multiple and single criteria based handover methods. The key performance indices from the simulations showed better overall throughput, better call dropped rate and shorter handover time duration for the multiple criteria based decision method compared to the single criteria based technique. This work also touches on current trends, challenges in area of seamless handover and initiatives for future Networks (Next Generation Heterogeneous Networks)