Firefly-inspired time synchronization mechanism for self-organizing energy efficient wireless sensor networks
One major issue faced by Wireless Sensor Network (WSN), which is based on pulsecoupled oscillators (PCOs) is the energy consumption and loss of data due to the deafness, high packet collision and high power in the application. Therefore, to overcome this problem this research proposes a technique...
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/68787/1/FSKTM%202018%2016%20IR.pdf |
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| Summary: | One major issue faced by Wireless Sensor Network (WSN), which is based on pulsecoupled
oscillators (PCOs) is the energy consumption and loss of data due to the
deafness, high packet collision and high power in the application. Therefore, to
overcome this problem this research proposes a technique for the efficient minimization
of energy usage among WSNs, particularly during transmission scheduling (sender state)
for time synchronization in WSNs. Specifically, the current work focuses on three
decentralized methods of energy efficiency with scalability and robustness. Among the
mechanisms used is the traveling wave pulse coupled oscillator (TWPCO), which is a
self-organizing technique for energy efficient WSNs by adopting a traveling wave
phenomenon based on phase locking of the PCO model regarding sensor nodes as
observed in the flashing synchronization behaviors of fireflies and secretion of radio
signals as firing to counteract deafness. The second mechanism is a self-organizing
energy efficiency pulse coupled oscillator (EEPCO) mechanism for WSNs, which
combines both the biologically inspired and non-biologically inspired network systems
to counteract packet collision. The third proposed mechanism is the random traveling
wave pulse coupled oscillator (RTWPCO), which reduces high-power to the smallest
level by using phase-locking travelling wave in biologically inspired of the PCO model
and random method based on anti-phase in non-biologically inspired of the PCO model.
The performances of the proposed algorithms were studied using a simulation analysis.
The results showed significant improvement in terms of reaching the steady state after a
certain number of cycles, obtaining superior data gathering ratio, and reducing the
energy consumption ratio of sensor nodes. Specifically, the TWPCO mechanism showed
superior performance compared to other mechanisms with a deduction on the total
energy consumption by 25 %, while improving the performance by 13 % in terms of
data gathering. On the other hand, the EEPCO mechanism improved data collection by up to 100% when the number of sensor nodes is below 40. In such a scenario, the energy
efficiency also improved by up to 15%. Finally, the proposed RTWPCO mechanism
achieved up to 53% and 60% reduction in the energy usage mainly due to the increase
in the number of sensor nodes as well as the increase in the data packet size of the
transmitted data. In addition, the mechanism improved the data gathering ratio by up to
75% and 73% respectively.
These mechanisms help to avoid deafness that occurs in the transmit state in WSNs, to
counteract packet collision during transmission in WSNs and minimize the high-power
utilization in the network and as well increase the data collection throughout the
transmission states in WSNs. |
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