A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks
碩士 === 國立高雄師範大學 === 光電與通訊工程學系 === 106 === In the process of heading the era of automation and Internet of Things (IoT), Machine-to-Machine (M2M) communication plays a significant role in the realization of Internet of Things. With the explosive growth of the quantity of data and the number of devi...
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ndltd-TW-106NKNU06520022019-05-16T00:30:14Z http://ndltd.ncl.edu.tw/handle/e5976y A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks 感知機器通訊網路中封包保留多工存取的動態許可機率之研究 WEI, LI-SHIANG 魏理湘 碩士 國立高雄師範大學 光電與通訊工程學系 106 In the process of heading the era of automation and Internet of Things (IoT), Machine-to-Machine (M2M) communication plays a significant role in the realization of Internet of Things. With the explosive growth of the quantity of data and the number of devices, the M2M communication networks have faced some obstacles such as the network congestion and the shortage of the radio spectrum resources. Therefore, to find a method to use the spectrum resources effectively is a major issue for deploying M2M devices extensively. This paper concentrates on combining M2M communication with cognitive radio technology, adopting the packet reservation multiple access (PRMA) as the MAC protocol for the communication in M2M system. Under the above system architecture, we propose three dynamic permission probability methods and expect a better efficiency of the communication system. We simulate through the program then inspect the differences of performances between those three proposed methods and the previous method using a static permission probability. In this simulation, we select primary user (PU) interference, utilization of idle slots, efficiency of power usage, packet delay and packet dropping ratio as the performance indicators of the communication system. The simulation results show that, while keeping PU interference in the same degree, the three proposed methods adopting dynamic permission probability could not only promote utilization of idle slots and efficiency of power usage but also reduce packet delay and packet dropping ratio. We find that the system using dynamic permission actually has better performances than the system using the static permission probability. Keyword:Machine-to-Machine, cognitive radio, PRMA, permission probability TZENG, SHOW-SHIOW 曾秀松 2018 學位論文 ; thesis 48 zh-TW |
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碩士 === 國立高雄師範大學 === 光電與通訊工程學系 === 106 === In the process of heading the era of automation and Internet of Things (IoT), Machine-to-Machine (M2M) communication plays a significant role in the realization of Internet of Things. With the explosive growth of the quantity of data and the number of devices, the M2M communication networks have faced some obstacles such as the network congestion and the shortage of the radio spectrum resources. Therefore, to find a method to use the spectrum resources effectively is a major issue for deploying M2M devices extensively.
This paper concentrates on combining M2M communication with cognitive radio technology, adopting the packet reservation multiple access (PRMA) as the MAC protocol for the communication in M2M system. Under the above system architecture, we propose three dynamic permission probability methods and expect a better efficiency of the communication system.
We simulate through the program then inspect the differences of performances between those three proposed methods and the previous method using a static permission probability. In this simulation, we select primary user (PU) interference, utilization of idle slots, efficiency of power usage, packet delay and packet dropping ratio as the performance indicators of the communication system.
The simulation results show that, while keeping PU interference in the same degree, the three proposed methods adopting dynamic permission probability could not only promote utilization of idle slots and efficiency of power usage but also reduce packet delay and packet dropping ratio. We find that the system using dynamic permission actually has better performances than the system using the static permission probability.
Keyword:Machine-to-Machine, cognitive radio, PRMA, permission probability
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author2 |
TZENG, SHOW-SHIOW |
author_facet |
TZENG, SHOW-SHIOW WEI, LI-SHIANG 魏理湘 |
author |
WEI, LI-SHIANG 魏理湘 |
spellingShingle |
WEI, LI-SHIANG 魏理湘 A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
author_sort |
WEI, LI-SHIANG |
title |
A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
title_short |
A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
title_full |
A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
title_fullStr |
A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
title_full_unstemmed |
A Study in Adaptive Permission Probability for Packet Reservation Multiple Access in Cognitive Machine-to-Machine Networks |
title_sort |
study in adaptive permission probability for packet reservation multiple access in cognitive machine-to-machine networks |
publishDate |
2018 |
url |
http://ndltd.ncl.edu.tw/handle/e5976y |
work_keys_str_mv |
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