17 research outputs found
A Review of Wireless Sensor Networks: Early Accident Detection Models for South African Mine Industries
No full textA Survey of Biometric Recognition Systems in E-Business Transactions
No full textThe global expansion of e-business applications has introduced novel challenges, with an escalating number of security issues linked to online transactions, such as phishing attacks and identity theft. E-business involves conducting buying and selling activities online, facilitated by the Internet. The application of biometrics has been proposed as a solution to mitigate security concerns in e- business transactions. Biometric recognition involves the use of automated techniques to validate an individual's identity based on both physiological and behavioural characteristics. This research focuses specifically on implementing a multimodal biometric recognition system that incorporates face and fingerprint data to enhance the security of e-business transactions. In contrast to unimodal systems relying on a single biometric modality, this approach addresses limitations such as noise, universality, and variations in both interclass and intraclass scenarios. The study emphasizes the advantages of multimodal biometric systems while shedding light on vulnerabilities in biometrics within the e- business context. This in-depth analysis serves as a valuable resource for those exploring the intersection of e-business and biometrics, providing insights into the strengths, challenges, and best practices for stakeholders in this domain. Finally, the paper concludes with a summary and outlines potential avenues for future research
Dynamic Bandwidth Allocation Algorithm to improve Quality of Service in Intelligent Home Networks
No full textEnhanced resource allocation algorithm for heterogeneous wireless networks.
No full textIn heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distribution of wireless channels, scarcity of wireless spectral resources, and dynamic behavior of generated traffic. Previously, resource allocation schemes have been proposed for HWNs. However, these schemes focus on resource allocation and management, whereas traffic class is not considered. Hence, these existing schemes significantly increase the end-to-end delay and packet loss, resulting in poor user QoS and network throughput in HWNs. Therefore, this study attempts to solve the identified problem by designing an enhanced resource allocation (ERA) algorithm to address the inefficient allocation of available resources vs. QoS challenges. Computer simulation was performed to evaluate the performance of the proposed ERA algorithm by comparing it with a joint power bandwidth allocation algorithm and a dynamic bandwidth allocation algorithm. On average, the proposed ERA algorithm demonstrates a 98.2% bandwidth allocation, 0.75 s end-to-end delay, 1.1% packet loss, and 98.9% improved throughput performance at a time interval of 100 s
Enhanced resource allocation algorithm for heterogeneous wireless networks.
No full textIn heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distribution of wireless channels, scarcity of wireless spectral resources, and dynamic behavior of generated traffic. Previously, resource allocation schemes have been proposed for HWNs. However, these schemes focus on resource allocation and management, whereas traffic class is not considered. Hence, these existing schemes significantly increase the end-to-end delay and packet loss, resulting in poor user QoS and network throughput in HWNs. Therefore, this study attempts to solve the identified problem by designing an enhanced resource allocation (ERA) algorithm to address the inefficient allocation of available resources vs. QoS challenges. Computer simulation was performed to evaluate the performance of the proposed ERA algorithm by comparing it with a joint power bandwidth allocation algorithm and a dynamic bandwidth allocation algorithm. On average, the proposed ERA algorithm demonstrates a 98.2% bandwidth allocation, 0.75 s end-to-end delay, 1.1% packet loss, and 98.9% improved throughput performance at a time interval of 100
Intelligent Metaheuristic-based Handover Algorithm for Vehicular Ad hoc Networks
No full textRecently, Vehicular Ad hoc Networks (VANETs) are becoming increasingly popular. VANETs are a subcategory of Mobile Ad hoc Networks (MANETs) in which nodes represent vehicles equipped with On-Board Units (OBUs). The fundamental reason is that VANETs improve safety for road users by providing vehicles with real-time road-related information. However, the increasing number of vehicles being introduced into these networks causes handover delays, and end-to-end delays, among other things. Therefore, the Quality of Service (QoS) is affected. This article proposes an Intelligent Metaheuristic-based Handover Algorithm (IMHA) to improve QoS in VANETs. The proposed IMHA is designed and implemented by integrating two of the most popular and recent optimization methods, namely disturbance Particle Swarm Optimization (d-PSO) and Ant Colony Optimization (ACO), wherein dPSO assigns different priority levels to vehicles on the road to ensure safety meanwhile ACO determines the most profitable routes from the source to the destination. Furthermore, the Congestion Problem Reduction (CPR) algorithm is implemented in the IMHA to define the requests to process in priority order. The ACO and d-PSO hybrid methods have been tested and evaluated in real-world VANETs, giving us more confidence in their performance and robustness. Network Simulator 2 (NS-2) is used to simulate the proposed algorithm. Based on the outcomes, IHMA reduces end-to-end, and handover delays and improves throughput at different vehicle velocities and network packet sizes. Consequently, this proposed solution guarantees improved QoS in VANETs. The experiment results show the proposed method outperforms existing handover algorithms, with a throughput of 92%, an end-to-end delay of 0.8 seconds, a handover delay and a computation time of less than 2.0 seconds, and an average memory usage of 60%
