TDMA scheduling analysis of energy consumption for iot wireless sensor network
Wireless Sensor Network (WSN) is one of the most explored topics of research in the field of computer science for many years and recently it gets more concern because of Big Data, IoT and 5G robustness. WSN getting more concern because it is the only best and easy way to collect data, communicate be...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/83215/1/FSKTM%202019%2033%20-%20IR.pdf |
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| Summary: | Wireless Sensor Network (WSN) is one of the most explored topics of research in the field of computer science for many years and recently it gets more concern because of Big Data, IoT and 5G robustness. WSN getting more concern because it is the only best and easy way to collect data, communicate between device to device and device to human. Cost effectivity, easy configuration and distribution makes it more reliable to the users. It builds the communication bridge between device to event and device to event. The most advantages of WSN is it has multi-hop and self-organizing capacity which made it an important element of widespread applications such as home automation, smart city, monitoring, especially important for military to do testing and monitoring war field. WSN nodes are very small in size but very important in term of work. The main option to power up the nodes is battery. Nodes life depends on the battery capacity. And sometimes it is not possible to change the battery easily depends on the area it distributed. Few factors played important role in WSN nodes power consumption. The routing distance always important, signal interference and the computation cost of the routing are the main factor of energy consumption of the node. Long routing distance take more power to transmit the data, signal interference and computation always consume high energy in WSN. So, battery power is limited and if so many wastages by the node for unnecessary things then the network life time will reduce and network performance will decrease time to time. Many new algorithms are implemented to reduce nodes energy consumption including Time division Multiplexing algorithm (TDMA) for scheduling to allocate neighbor and reduce signal interference, Distributed Randomize (DRAND) Time Division Multiplexing to do nodes random distribution and allocation. The base-work paper of the research presents an improvement of DRAND algorithm based on energy consumption in IoT WSN to enhance the node energy consumption and
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increase the network lifetime. The algorithm use time division multiplexing algorithm together with hello message to allocate the neighbors and their energy level to find the best way to communicate and reduce packet drop, less signal interference and increase throughput. The major objective for this project is to re-implement the proposed Energy Topology DRAND (E-T-DRAND) algorithm in IoT WSN using time slot allocation method and allocate nodes together with the node energy information and compare the obtained results with the corresponding results in the base paper. Network Simulator NS2.35 is the tool used for simulation of the project. For the evaluation of the performance the parameters used are Energy consumption (Joules). The results in the trace files are analyzed by using the awk script. Finally, represent the difference between experimental results and the old results of E-T-DRAND will determine if the algorithm has been efficiently re-implemented. |
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