Normaliza Omar
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Preferred name
Normaliza Omar
Official Name
Normaliza, Omar
Alternative Name
Omar, N.
Normaliza, O.
Main Affiliation
Scopus Author ID
55384121300
Researcher ID
DLM-3239-2022

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Velocity Based Performance Analysis of GreedLea Routing Protocol in Internet of Vehicle (IoV)

2024-12-01 , Normaliza Omar , Naimah Yaakob , Mohamed Elshaikh Elobaid Said Ahmed , Zulkifli Husin , Iszaidy Ismail , Alaa KY Dafhalla

Intelligent routing protocols for IoV have also been made possible by the convergence of IoT and machine learning algorithm. In order to make informed routing decisions, these intelligent routing protocols examine data gathered from IoT devices like vehicle sensors and traffic monitoring systems using machine learning algorithms. Moreover, as the number of vehicles increases and road networks become more complex, traditional routing protocols for ad hoc networks are being replaced by more advanced and efficient protocols. The purpose of this study is to concentrate on these unique qualities of IoVs network scenario. A combined routing method has been developed to construct periodic connectivity and find routes on-demand in order to save route data as graphs. The simulation's findings show that GreedLea routing protocol outperforms GPSR and AODV routing protocols in terms of delay and packet delivery ratio (PDR). The results demonstrate that the average AODV latency is significantly higher when there are fewer vehicles on the network. This is due to the fact that connections are frequently lost at higher speeds and lower densities, and re-establishing new channels takes a lot of time. As the number of vehicles rises, efficiency improves and the wait gets shorter. The average latency, yet, keeps increasing as vehicle density increases due to the additional overheads related with routing.

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Publication

Design and development of scheduling algorithms for downlink transmission system of Long Term Evolution (LTE) network

2015 , Normaliza Omar

In today‟s technology development, people need internet access wherever they are, mobile broadband will grow up actively. Therefore, service providers gradually compete to produce the maximum internet speed for public uses. To enable high-speed data services to mobile users, scheduling technique gained significant attention in wireless access networks. A feature of the wireless environment is that the quality of the different channels of the user population due to a conflict path loss and effect of the attenuation. The best scheduler should provide high throughput, low latency system and the best coverage gains. In order to develop the best scheduling, the scheduler must be aware of the channel quality and scheduler should have associate of the channel quality for each sub carrier and each user. In order to exploit the diversity of multiuser in addition to deliver further compliance in resource allocation, an algorithm is proposed in this work where system latency is considered as the first priority in scheduling steps and followed by arrangement of user equipments (UEs) according to the Channel Quality Indicator (CQI) scheduler for Long Term Evolution (LTE) structure. The analysis and the comparison of these scheduling algorithms were prepared over simulations done by a MATLAB-based downlink system level simulator from the Vienna University. The main target in this thesis is to propose a new scheduling for resources allocation that may be compromise between throughput and fairness to avoid useless space in a scheduler. Useless space may cause the latency that may cause of delay in transmission. The Round Robin (RR) scheduler and best CQI scheduler are considered in this research work. There are two (2) enhanced scheduling algorithms proposed in this research work which are Resource Fairness (RF) and Maximum Throughput (Max TP) scheduling algorithm. The enhanced scheduling algorithms have been proposed based on Proportional Fair (PF) scheduling algorithm. PF is one‟s of scheduling algorithm that have compromise between throughput and fairness. From the observation, it shows that RF scheduling algorithm has been achieved about 19% of improvement in term of fairness index compared to other scheduling algorithm for all type of network scenarios. While Max TP scheduling algorithm has provide about 25% of improvement in term of throughput for all network scenario. Since RF scheduling algorithm provide second highest throughput value which having about 11% of improvement compared to other scheduling algorithm, it may be considered that RF scheduling algorithm has achieved high compromise between fairness and throughput compared to PF scheduling algorithm.

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Design and Development of GreedLea Routing Protocol for Internet of Vehicle (IoV)

2020-03-20 , Normaliza Omar , Naimah Yaakob , Zulkifli Husin , Mohamed Elshaikh Elobaid Said Ahmed

In Internet of Vehicle (IoV), each vehicle uses a routing protocol to find a path for sending its messages to the last destination. Nowadays, the studies of IoV routing protocols and their impact on the performances of network with different network scenarios has significantly developed a precise understanding of the requirements and goals for designing an IoV routing protocol. In IoV, topology of network diverse promptly which leads to the fragmentation of network, frequent route breakage, and packet loss. This paper discusses on the development of an integrated routing protocol for IoV scenario. Greedy Perimeter Stateless Routing (GPSR) and Reinforcement Learning (RL) is integrate to determine a route based on demand. Then, the mobility model has been designed to reduce road collision. Lastly, traffic management also been focused to deal with the loss, mobility and network delay to meet the application demands.

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Route Beaconing (RouteBea) Process in GreedLea Routing Protocol for Internet of Vehicle (IoV) Network Environment

2021-06-11 , Normaliza Omar , Naimah Yaakob , Saidahmed M.E.E. , Zulkifli Husin

Practically, vehicles tend to travel in long distances. As a result, a vehicle might attach to different network scenarios and topologies. This unique behavior in IoV brings the attention for a robust routing protocol design. For example, a vehicle that runs the same routing protocol, while it moves from one geographical area to another, it experiences different network topology requirements, and thus, the performance of the routing protocol contrasts. Consequently, the performances of the network drop. Considering a huge number of vehicles join in these networks with their high mobility, there are still having problem due to the viability of applications via different network topology. Traffic management problems come up as number of vehicle has been growing at an exponential rate. In order to make life easier, emergency response to road accidents, speed limits, and pollution checks should be considered to be observed. The common applied to this problem are observing of vehicle's speed via CCTV cameras, speed trackers and periodic pollution checks. However, these approaches be inclined to fail as a large number of vehicles need to be observed. Therefore, GreedLea routing protocol has been develop to overcome the problem of monitoring the traffic condition and traffic congestion. In GreedLea routing protocol, path interval is provided by the host to other vehicle to update the condition of traffic and routes in certain area. The details about GreedLea routing protocol has been described in following section. The performance of the GreedLea routing in different speed and distance has been analyze and presented in result and discussion section. In the result, it shows that the performance of GreedLea increase in the packet delivery ratio (PDR) which is packet loss is less than 0.1% and reducing protocol overhead by approximately 20-60% as the vehicle's speed increase for beaconing intervals in the range of 1-3 seconds.

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Performance Analysis of GreedLea Routing Protocol in Internet of Vehicle (IoV) Network

2021-08-27 , Normaliza Omar , Naimah Yaakob , Saidahmed M.E.E. , Zulkifli Husin

The Internet of Vehicles (IoV) network transforms smart life on the wheels through several connections between vehicles, highways, people and networks, providing a safer, more effective and more energy-efficient driving experience. In a specific field, the reliable arrival of independent vehicles and the typical enhancement of traffic safety change through a fast and consistent distribution of messages. It is important to disseminate messages between vehicles that make up the IoV network and to be exploit of the quick and effective transmission of multi-hop communication for the information broadcasting. This study introduces the standardization method and summarizes the primary technologies of IoV network. This study provides a set of traditional research developments, analyses key innovations to date and, eventually, proposes solutions to common use cases that could provide valuable references for the development and implementation of potential IoVs network. The simulation has been done using OMNET++ platform to evaluate the GreedLea routing protocol with the standard Greedy Perimeter Stateless Routing (GPSR) and Ad-hoc On-demand Distance Vector (AODV) routing protocol in IoV network scenario. In the performance analysis varied parameters for example direction, node and speed has been take into account. This study also proposed to evaluate GreedLea in a crowded city situation and in a highway situation to provide further realistic simulations. From the simulation results, it shown that the GreedLea presented better performance compared to the traditional GPSR and AODV in term of end-To-end latency, packet loss rate and path loss.

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Publication

MOVE Mobility Model in GreedLea Routing Protocol for Internet of Vehicle (IoV) Network

2021-07-26 , Normaliza Omar , Naimah Yaakob , Mohamed Elshaikh Elobaid Said Ahmed , Zulkifli Husin

Internet of Vehicles (IoV) is a broad variety of mobile transmission purposes for file sharing [l]-[5]. There are still debates on the viability of purposes using end to end multi-hop communication, since the significant number of high mobility nodes involved in the networks. The main issue is the efficiency of IoV routing protocols in cities and highways can meet the ideal delay and throughput for such purposes. In particular, it is not usually a challenge to locate a node to hold a message in urban daytime situations, where vehicles are tightly packed. Since fewer number of vehicles are running in highway scenarios and cities at night, and it might not be possible to set up end-to-end roads. In general, each protocol offered a performance evaluation in contradiction of some other protocols, giving considerable importance to a detailed performance evaluation of each protocol type. After such an assessment, it was found that geocast routing would perform best in urban areas. GreedLea routing protocol is develop to overcome the current routing protocol drawback. The development of GreedLea routing protocol involved Greedy Perimeter Stateless Routing (GPSR) and reinforcement learning method in order to deliver better performance compared to current existing routing protocol. Urban environments without obstacles has been simulated using actual maps for example intersection density. In order to measure efficiency, the metrics are: average delivery rate, average delay, average length of path and overhead. From the analysis, it shows that GreedLea offers better performance compared to GPSR for both city and highway scenario. The first section in your paper.

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