Design and Modelling of an Energy Aware Dynamic Management for Wireless Sensor Node with Dual Harvesters
Wireless Sensor Network (WSN) consists of a large number of spatially distributed low-power autonomous nodes equipped with sensors to cooperatively monitor the environmental conditions. The limited battery lifespan that is being used by a sensor node is the major bottleneck that restricts the extens...
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| Format: | Thesis |
| Language: | English English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/25536/1/Design%20and%20Modelling%20of%20an%20Energy%20Aware%20Dynamic%20Management%20for%20Wireless%20Sensor%20Node%20with%20Dual%20Harvesters.pdf http://eprints.utem.edu.my/id/eprint/25536/2/Design%20and%20Modelling%20of%20an%20Energy%20Aware%20Dynamic%20Management%20for%20Wireless%20Sensor%20Node%20with%20Dual%20Harvesters.pdf |
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| Summary: | Wireless Sensor Network (WSN) consists of a large number of spatially distributed low-power autonomous nodes equipped with sensors to cooperatively monitor the environmental conditions. The limited battery lifespan that is being used by a sensor node is the major bottleneck that restricts the extension of WSN application for its scalability and sustainability. Thus, the energy consumption efficiency remains the most prominent design criterion that need to be addressed urgently. There are two main research concerns on the energy-harvesting powered WSN, firstly is to reduce the node power consumption and the, secondly is to increase the harvesters' power to meet the minimum requirement of the node power consumption. In another word, it is to reduce the mismatch of the supply and demand of the node electrical power. Thus, an energy aware dynamic management model for wireless sensor node powered by dual harvesters is presented to deal with the mismatch. The first step of the research is to investigate the node power consumption profile. This is followed by investigating the electrical power supplies which are based on thermoelectric and piezoelectric as Hybrid Energy Harvesting (I-EH). The node is designed with a built-in main and backup energy storages to overcome the HEH energy gap issue. It features fast start up using a small capacitive energy storage as the main instantaneous power source. Whilst for wider energy gap coverage, a larger capacitance is used as the backup energy storage. To reduce the power consumption while not compromising the integrity of the signal transmission, the sensor node is improved with a novel energy-aware Event-Priority-Driven Dissemination (EPDD) algorithm. It is developed to make the sink station able to detect a missing node within the network. The function of the algorithm is to detect the energy sources availability and control the nodes' sleeping period accordingly. The empirical power profiling for each node and at system level were measured during active and sleep modes, which provides a useful data for designing low-power wireless sensor node. The node is designed and modelled using Matlab Simulink 2016 environment. The simulation results show an improvement in the node start-up time of less than 30s only with 48 hours of energy gap coverage, which is theoretically long enough to ensure that the node stayed active until the next phase of ambient energy to be available again. The experimental results are in good agreement with the simulation model. It is also found that the RF transceiver consumed the highest power of 24mW, followed by the microcontroller with 7.5mW and the sensor module with O. 16mW throughout the active period. During the sleep period, however, the microcontroller consumed a noticeable amount of power of 1.8mW compared to the other sensor node components. Moreover, it shows that energy at ideal cases where both energy harvesters, I-EH are operating at the same time, a power in the range of around 90 mW is generated which is more than enough to achieve the minimum requirement to operate a sensor node. |
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