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

Motorized cart

Motorized cart is known as an effective tool and timeless that help people carry heavy loads. For farmers, it has an especially vital tool for moving goods. Oil palm farmers typically uses the wheelbarrow to move the oil palm fruit (Figure 10.1). However, there is a lack of equipment that should be further enhanced in capabilities. Motorized carts that seek to add automation to wheelbarrow as it is to help people save manpower while using it. At present, oil palm plantation industry is among the largest in Malaysia. However, in an effort to increase the prestige of the industry to a higher level there are challenges to be faced. Shortage of workers willing to work the farm for harvesting oil palm has given pain to manage oil palm plantations. Many have complained about the difficulty of hiring foreign workers and a high cost. Although there are tools that can be used to collect or transfer the proceeds of oil palm fruits such as carts available. However, these tools still have the disadvantage that requires high manpower to operate. Moreover, it is not suitable for all land surfaces and limited cargo space. Workload and manpower dependence has an impact on farmers' income

Quality of service aspect for BRAIN architecture

Session 4.1International audienceIn this paper, we present different aspects of Quality of Service that should be adapted to the BRAIN architecture. Several parameters and policies of QoS are depicted. Also, the paper shows the dynamic adaptation of these parameters in the context of BRAIN

Fuzzy Based Vertical Handoff Decision Controller for Future Networks

— In Next generation wireless Networks, the received signals (RSS) from different networks do not have a same meaning since each network is composed of its specific characteristics and there is no common pilot signal. Then, RSS comparisons are insufficient for handoff decision and may be inefficient and impractical. A more complex decision criterion that combines a large number of parameters or factors such as monetary cost, bandwidth, and power consumption and user profile is necessary. Though there are a lot works available for vertical handoff decision (VHD) for wireless networks, the selection of best network is still challenging problem. In this paper we propose a Fuzzy based vertical handoff decision controller (FVHDC) Which performs handover decision based on the output of fuzzy based rules

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