Title page for etd-0705118-215052


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URN etd-0705118-215052
Author Tsung-Lin Lee
Author's Email Address No Public.
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Department Electrical Engineering
Year 2017
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Adaptive Linked-List Mechanism For Wi-Fi Wireless Network
Date of Defense 2018-07-24
Page Count 85
Keyword
  • IoT
  • Wi-Fi
  • wireless network
  • data collection network
  • linked-list network
  • Abstract In response to the concept of Smart City and Internet of Things (IoT) being prevailed in recent years, networking requirements for various devices have increased significantly, however, many related problems have arisen. To solve the problems and shortcomings of the existing IoT wireless networking technologies, for example, the data rate of ZigBee is slow and the wireless networking technologies which uses star topology like NB-IoT and LoRa is rely on the signal of base station, if the node is at communication deadzone, it will not be able to successfully transmit data. Therefore, this thesis proposes an Adaptive Linked-List Mechanism For Wi-Fi Wireless Network, this algorithm takes advantage of the low-collision of the linked-list architecture and solves the problem that multiple nodes cannot be started at the same time, moreover, the nodes are able to use signal strength as the basis for constructing a linked-list network that ensure that the nodes within the signal coverage can be stably connected, and the entire system will not be interrupted due to a problem with a few nodes. The algorithm also modifies the linked-list network construction and broken node recovery process, and adds the packet signal strength queue mechanism, so that multiple nodes can quickly construct the network chain. Furthermore, we design a Wi-Fi control board which is based on CC3220MODA and implement our algorithm on it, finally, after testing in different environment, we offer two objective function for two important arguments. We hope to take advantage of this wireless linked-list network in data collection network in the future, and then solve the multi-device networking requirements, and build a stable, reliable and high-speed data collection network for IoT.
    Advisory Committee
  • Chu-Sing Yang - chair
  • Kai-Ming Yang - co-chair
  • Tong-Yu Hsieh - co-chair
  • Jih-Ching Chiu - advisor
  • Files
  • etd-0705118-215052.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2018-08-05

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