Adaptive delay tolerant routing for enhanced connectivity in vehicular networks / Mostofa Kamal Nasir

Mostofa Kamal , Nasir (2016) Adaptive delay tolerant routing for enhanced connectivity in vehicular networks / Mostofa Kamal Nasir. PhD thesis, Universiti Malaya.

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    To enhance the network performance, many researchers have proposed solutions to resolve the minimal persistence of routing protocols in urban vehicular networks. These proposals exploit basic network services and information for optimal route calculation and data delivery. Vehicular Adhoc Networks (VANETs) have distinct characteristics compared to other ad hoc network like high mobility and constrained road patterns. Therefore, it is hard to establish an end-to-end connection to transmit a packet from the source to the destination. In this context, geographic routing protocols are currently considered as the best choice for routing. Geographic routing requires each vehicle to obtain knowledge about other nodes in the network by broadcasting the HELLO beacon to the neighbours. However, it results in a heavy load being generated, which in turn leads to increased overheads, collision and contention. In VANETs, all the routing protocol consider a pre-calculated route for the dissemination of messages, but it is impractical. These problems can be mitigated by the Delay Tolerant Network (DTN). Therefore, providing a robust and adaptive routing protocol is considered as crucial for high performance in partially connected networks. Many routing techniques such as Greedy Perimeter Stateless Routing (GPSR) and Geographic Opportunistic (GeoOpps) etc. have been developed to solve those problems in partially connected vehicular networks but still have some limitations. For instance, GeoOpps route discovery is based on finding a vehicle which is driving towards the destination, though this choice is not practical. Meanwhile, existing DTN routing protocols in vehicular environment are cannot select appropriate intermediate nodes for the sparse environment. To overcome these drawbacks, a novel approach has been introduced in this research, which organizes the operation of broadcasting the HELLO beacon messages in VANETs by considering specific parameters. Each node in the network broadcasts the HELLO beacon message based on its position, vector and predicted future direction that are acquired by the vehicle Direction Indicator Light (DIL). DIL information has been introduced for the first time in this research domain. An Adaptive Geographic DTN Routing (AGDR) protocol is proposed in vehicular networks for the urban scenario to enhance connectivity. The solution is designed for heavily partitioned environments which suffer from frequent network disconnections by proposing the most suitable intermediate node selection mechanism through a next-hop selection process. The next- hop selection process utilizes node position, current direction, speed and the predicted direction that is acquired by DIL. The performance of the proposed protocol is evaluated by NS-2 in terms of efficiency, overhead and end-to-end delay in contrast with previous work. Simulation experiments confirm the performance supremacy of AGDR compared to contemporary schemes in terms of packet delivery ratio, overhead and end-to-end delay. Simulation results demonstrate that AGDR improves the packet delivery ratio (5-7%), reduces the overhead (1-5%) and decreases the delay (0.03 to 0.05 ms). Therefore, AGDR improves route.

    Item Type: Thesis (PhD)
    Additional Information: Thesis (PhD) – Faculty of Computer Science & Information Technology, Universiti Malaya, 2016.
    Uncontrolled Keywords: Vehicular networks; Direction Indicator Light (DIL); Greedy Perimeter Stateless Routing (GPSR); GeoOpps route; FreeBSD
    Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
    Q Science > QA Mathematics > QA76 Computer software
    Divisions: Faculty of Computer Science & Information Technology
    Depositing User: Mr Mohd Safri Tahir
    Date Deposited: 21 Oct 2021 04:07
    Last Modified: 21 Oct 2021 04:07

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