Mobility and handover technique in heterogeneous wireless networks

The management techniques for Mobile IPv6 between different wireless technologies are very important to complete the handover process with the least possible delay. In the fast handover, when a mobile node moves to another network, it needs to do handover operations. These operations have a severe impact on the handover latency. This paper proposes an Enhanced Advanced Duplicate Address Detection (EA-DAD) method in a heterogeneous mobile environment with the support of the MIH services. The proposed method quickly provides a unique Ipv6 address for MNs. At the same time, the binding updates to home agent and correspondent node are to be performed from old access router. We can see through results that by optimizing network layer, EA-DAD quickly presents unique Ipv6 addresses for MNs with a minimum handover latency and packet loss even at high speed movements

An efficient wireless network discovery method for vertical handover between WiMAX and WLAN

One of the most difficult tasks for coordination the vertical handover is the discovering currently available radio access networks. Although the mobile nodes (MN) is easily can access to Worldwide Interoperability for Microwave Access (WiMAX) network, but continually it would have to discover available wireless local area network (WLAN) networks, which provide high data rates but have limited coverage area. This process discovers has a significant effect on the discovery time and power consumption for MNs. this article introduce a new technique to enhance access router discovery (EARD) method to solve this problems. Our proposal EARD method, previous access router provides information about the neighbouring networks for MN to discover available networks as soon as possible. We can see through simulation results that by enabling the EARD method has improved power consumption and the discover time of networks in the performance of MNs compared to the conventional network discovery techniques

Improved fast handover method for multiple node by using mobile nodes guide

The fast mobile internet protocol version 6 (FMIPv6) was suggested as a fast handover mechanism over the mobile wireless Internets in order to reduce the handover latency of a mobile node (MN). However, FMIPv6 was originally designed to deal with single MN’s. In mobile wireless Internet, a multiple MNs may do a handover at the same time as a consequence of its movement from one network to another new one. This will therefore lead to the bandwidth waste and low handover performance. This paper intends to propose a multiple handover-based mobile node (MHB-MN) control method and an enhanced FMIPv6 mechanism in order to resolve the abovementioned problem. The proposal of such an MHB-MN method aims at having one mobile node work as a guide for a group of neighboring MNs. This means that the guide of MN prepares itself for a handover before actually taking the initial steps of the actual handover operation. Based on obtained results, it is plainly observable that by MHB-MN method, the handover initiation time, handover latency and handover control messages can be reduced compared to those of FMIPv6. Furthermore, the contention of the wireless channel for multiple MNs can be improved by the use of fewer control messages. Finally, the paper introduces an analytical model to show that by enabling the MHB-MN method and enhancing the FMIPv6 method, a multiple of nodes can perform rapid handover processes with low handover latency compared to that of the FMIPv6 technique

Algorithm for enhancing the QoS of video traffic over wireless mesh networks

One of the major issues in a wireless mesh networks (WMNs) which needs to be solved is the lack of a viable protocol for medium access control (MAC). In fact, the main concern is to expand the application of limited wireless resources while simultaneously retaining the quality of service (QoS) of all types of traffic. In particular, the video service for real-time variable bit rate (rt-VBR). As such, this study attempts to enhance QoS with regard to packet loss, average delay, and throughput by controlling the transmitted video packets. The packet loss and average delay of QoS for video traffic can be controlled. Results of simulation show that Optimum Dynamic Reservation-Time Division Multiplexing Access (ODR-TDMA) has achieved excellent utilization of resource that improvised the QoS meant for video packets. This study has also proven the adequacy of the proposed algorithm to minimize packet delay and packet loss, in addition to enhancing throughput in comparison to those reported in previous studies

A network selection algorithm based on enhanced access router discovery in heterogeneous wireless networks

The management process between different wireless technologies for mobile devices is very important to complete the handover operations. The handover operation needs to determine the delay and packet loss in order to be the quality of service within a certain level. Selecting the best available network at the appropriate time is very significant in the direction of realizing ubiquitous networks. In this paper a network selection approach named enhanced access router discovery (EARD) is proposed. The approach is developed to work in a heterogeneous environment including of WiMAX and WLAN networks. The EARD method utilizes the prioritized rating for multiple criteria (PRMC) proposed for selecting the target network. The proposed approach is evaluated with respect to various conditions with different traffic types. The simulation results show that our proposed approach outperform the traditional network selection methods is selecting the most appropriate network

OCA: Ordered Clustering-Based Algorithm for E-Commerce Recommendation System

The industry of e-commerce (EC) has become more popular and creates tremendous business opportunities for many firms. Modern societies are gradually shifting towards convenient online shopping as a result of the emergence of EC. The rapid growth in the volume of the data puts users in a big challenge when purchasing products that best meet their preferences. The reason for this is that people will be overwhelmed with many similar products with different brands, prices, and ratings. Consequently, they will be unable to make the best decision about what to purchase. Various studies on recommendation systems have been reported in the literature, concentrating on the issues of cold-start and data sparsity, which are among the most common challenges in recommendation systems. This study attempts to examine a new clustering technique named the Ordered Clustering-based Algorithm (OCA), with the aim of reducing the impact of the cold-start and the data sparsity problems in EC recommendation systems. A comprehensive review of data clustering techniques has been conducted, to discuss and examine these data clustering techniques. The OCA attempts to exploit the collaborative filtering strategy for e-commerce recommendation systems to cluster users based on their similarities in preferences. Several experiments have been conducted over a real-world e-commerce data set to evaluate the efficiency and the effectiveness of the proposed solution. The results of the experiments confirmed that OCA outperforms the previous approaches, achieving higher percentages of Precision (P), Recall (R), and F-measure (F)

OCA: Ordered Clustering-Based Algorithm for E-Commerce Recommendation System

The industry of e-commerce (EC) has become more popular and creates tremendous business opportunities for many firms. Modern societies are gradually shifting towards convenient online shopping as a result of the emergence of EC. The rapid growth in the volume of the data puts users in a big challenge when purchasing products that best meet their preferences. The reason for this is that people will be overwhelmed with many similar products with different brands, prices, and ratings. Consequently, they will be unable to make the best decision about what to purchase. Various studies on recommendation systems have been reported in the literature, concentrating on the issues of cold-start and data sparsity, which are among the most common challenges in recommendation systems. This study attempts to examine a new clustering technique named the Ordered Clustering-based Algorithm (OCA), with the aim of reducing the impact of the cold-start and the data sparsity problems in EC recommendation systems. A comprehensive review of data clustering techniques has been conducted, to discuss and examine these data clustering techniques. The OCA attempts to exploit the collaborative filtering strategy for e-commerce recommendation systems to cluster users based on their similarities in preferences. Several experiments have been conducted over a real-world e-commerce data set to evaluate the efficiency and the effectiveness of the proposed solution. The results of the experiments confirmed that OCA outperforms the previous approaches, achieving higher percentages of Precision (P), Recall (R), and F-measure (F)

Surface Integrity Evaluation on Aluminium-Epoxy Composite in Machining using Taguchi Method

The increasing needs of using aluminum epoxy composite as a replacement to solid metal rapid prototyping has opened to interests in optimizing its machining processes. This paper reported on the success of optimizing the surface roughness of aluminium epoxy composite using milling process along with a new finding on the best combination parameters. Taguchi method was used as the optimization method whereas spindle speed, feed rate, and depth of cut were set as input factors using an L9 Orthogonal Array. Analysis of Variance was used to identify the significant factors influencing the surface roughness. Experiment was conducted in dry condition using a vertical milling machine and the surface roughness after the machining was evaluated. Optimum combination of cutting parameters was identified after the finest surface roughness (response) based on the signal-to-noise ratio calculated. Cutting parameters selected after preliminary testing are cutting speeds of (2000, 3000 and 4000) rpm, feed rate (300, 400 and 500) mm/min, and cutting depth (0.15, 0.20, and 0.25) mm. The result showed that cutting speed had the largest percentage contribution to surface roughness with 69% and the second highest contribution was feed rate with 22% and depth of cut at 9%. The spindle speed was found as the most significant factor influencing the quality of surface roughness. The result is significant particularly in providing important guidelines for industries in selecting the right combination of parameters as well as to be cautious with the most significant factor affecting the milling process of metal epoxy composite