Permanent URI for this collection
Browse
Recent Submissions
Item Intelligent metaheuristic-based handover algorithm for vehicular ad hoc networks.(Oxford University Press (OUP), 2023-09-09) Oladosu, Gbenga O.; Tu, Chunling; Owolawi, Pius A.; Mathonsi, Topside E.Recently, 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%.Item Enhanced resource allocation algorithm for heterogeneous wireless networks.(Fuji Technology Press Ltd., 2020-09-14) Mathonsi, Topside E.; Tshilongamulenzhe, Tshimangadzo Mavin; Buthelezi, Bongisizwe ErasmusIn 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 sItem Intelligent metaheuristic-based handover algorithm for vehicular ad hoc networks.(Oxford University Press (OUP), 2023-09-09) Oladosu, Gbenga O.; Tu, Chunling; Owolawi, Pius A.; Mathonsi, Topside E.Recently, 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%.