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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Ravie Chandren Muniyandi, Assoc. Prof. Dr. | |
| dc.contributor.author | Haitham Qutaiba Ghadhban (P74475) | |
| dc.date.accessioned | 2023-10-06T09:18:47Z | - |
| dc.date.available | 2023-10-06T09:18:47Z | - |
| dc.date.issued | 2017-05-11 | |
| dc.identifier.other | ukmvital:97954 | |
| dc.identifier.uri | https://ptsldigital.ukm.my/jspui/handle/123456789/476455 | - |
| dc.description | Vehicular Ad hoc Network (VANET) is a subclass of ad hoc networks and a special type of Mobile Ad Hoc Network (MANET). Location prediction model is a mathematical based model to predict the location of a moving object. Location prediction is very important for many applications of Vehicular Ad Hoc Networks such as routing, network management, data dissemination protocols, road congestion, etc. In routing algorithms in Vehicular Ad Hoc Networks, various routing protocols are highly dependent on location information. An example is location aided routing LAR, in which location information are used to route packets through the network to its final destination. In this thesis, an improvedKalman filter based location prediction model is developed based on the sensing system of the car and incorporated in location aided routing model under Kalman filter based location aided routing. In this model the predictions of the positions of objects with rapidly changing locations can be achieved with a higher accuracy than a traditional Vehicular Ad Hoc Network model. The development aspect has assumed the kinematic model of the road and the vehicle as constraint to exclude error data coming from sensors when it conflicts with the assumed constraints. Results have shown that our Kalman filter based location aided routing model has outperformed normal Kalman based location aided routing in terms of parentage of delivery ratio and other network measures. Packet Delivery Ratio (PDR) was at 95% with a smaller network overhead, with an of 12% improvement in the delay.,Certification of Master's/Doctoral Thesis" is not available | |
| dc.language.iso | eng | |
| dc.publisher | UKM, Bangi | |
| dc.relation | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
| dc.rights | UKM | |
| dc.subject | Location prediction | |
| dc.subject | Kalman filter | |
| dc.subject | Location aided routing | |
| dc.subject | Universiti Kebangsaan Malaysia -- Dissertations | |
| dc.title | Improved Kalman filter based LAR in Vehicular Ad Hoc Network | |
| dc.type | theses | |
| dc.format.pages | 89 | |
| dc.identifier.barcode | 003037(2017) | |
| Appears in Collections: | Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ukmvital_97954+SOURCE1+SOURCE1.0.PDF Restricted Access | 514.29 kB | Adobe PDF |  View/Open |
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