Mahima, Karim (2022) Hybrid mac strategy exploiting markov chain model for iot enabled intra-vehicular health monitoring system. Masters thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: Arafatur, Rahman).
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Abstract
Vehicular networks, coined with IoT, have opened a new arena of possibilities for a comfortable and seamless driving experience. IoT is already incorporated into almost every aspect of human life for the past couple of years. Over the years, it has also shown remarkable development in the automotive industry. With the exponential growth of sensors and communication protocols inside a vehicle, intra-vehicular networks are becoming overcrowded and more complex day by day. This raises many issues, such as degraded QoS (Quality of Service), network congestion, packet loss, transmission delay, intrusions, unsatisfactory throughput, etc. These problems are also apparent in vehicular health monitoring systems. To overcome such challenges, it is necessary to develop an elaborate communication protocol to address them. In this thesis, the main area of focus was improving MAC protocol. TCP/IP is a five-layer standardized communication protocol that facilitates communication between devices over the internet. Unique network protocols and functions are authorized for each of the five layers. In this research, the work is fully focused on optimizing the MAC layer in vehicles. A hybrid MAC layer is a history-based and priority-based MAC combining the best features of both schemes proposed in this thesis. Here, the efficiency of the system is evaluated by calculating the system’s throughput using enhanced Markov chain calculation as well as doing ns-3 simulation for different conditions. The objective of this research is to improve MAC’s scalability and mitigate network traffic and congestion issues by improving the throughput and reducing collision and delay. The proposed Hybrid MAC shows a significant increase in throughput compared to history-based MAC and priority-based MAC, as well as efficiency in mitigating delay and collision in the network. Tags from this library: No tags from this library for this title.
Item Type: | Thesis (Masters) |
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Additional Information: | Thesis (Master of Science) -- Universiti Malaysia Pahang – 2022, SV : Dr. Md. Arafatur Rahman, NO. CD: 13290 |
Uncontrolled Keywords: | markov chain model, iot enabled intra-vehicular, health monitoring system |
Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Faculty/Division: | Institute of Postgraduate Studies Faculty of Computing |
Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
Date Deposited: | 17 May 2023 06:50 |
Last Modified: | 18 Sep 2023 03:02 |
URI: | http://umpir.ump.edu.my/id/eprint/37655 |
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