Aerospace and Electronic Systems - March 2019 - 65
Khriji et al.
Figure 10.
Residual energy of the network: Nodes of ring 1 (left) and nodes of ring 2 (right).
As seen in Figure 10, the function of data sent to the
BS seems to be exponential. Thus, the number of packets
received on the BS increases from one time to another.
When nodes from ring 1 transmit their data packets to
their CH, nodes from ring 2 are in the receiving mode and
vice versa. Since the CH of ring 1 works as a relay node for
the CH from ring 2, more data packets are available in the
ring 1. Each node in the network sends a data packet to its
CH, which includes node ID, (X, Y) coordinates, chance for
being a CH, and the sensing data if available. The CH, in
his turn, collects data packets from its respective cluster
members installed within the same cluster. Then, the CH of
ring 2 forwards all received data to the CH of ring 1, which
will transmit all packets directly to the BS.
Results show that the energy consumption decreases
very slowly, where the CH of the closest ring to the BS is
the most energy consuming node, since it is responsible
for collecting data from its cluster members and from
other CHs. We propose therefore to vary the size of the
cluster radius, so that a small size of the closest ring to the
basis station is realized.
aware routing algorithm is carried out on the wireless sensor node PanStamp NRG 2.0. This network structure can
be easily integrated on IoT systems to monitor and control
different environmental and agricultural applications.
REFERENCES
[1] S. Khriji, D. E. Houssaini, I. Kammoun, and O. Kanoun,
"Energy-efficient techniques in wireless sensor networks:
Technology, components and system design," in Proc. Energy
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[2] K. Bayne, S. Damesin, and M. Evans, "The internet of
things-Wireless sensor networks and their application
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[3] M. Khari et al., "Wireless sensor networks: A technical
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[4] S. Bradai, S. Naifar, C. Viehweger, and O. Kanoun,
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CONCLUSION
[5] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan,
In agricultural applications, the use of spatially distributed
WSNs is expected to increase. Thereby, energy-efficiency
techniques have been investigated and become much more
important as the number of distributed sensor nodes
increases. Wireless communication can lead in general to
excessive demands of energy. Thus, a routing algorithm is
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nodes position. After that, a fuzzy-based unequal clustering
algorithm is developed to balance the energy consumption
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MARCH 2019
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[6] S. A. Nikolidakis, D. Kandris, D. D. Vergados, and
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balancing unequal clustering in wireless sensor networks
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65
Aerospace and Electronic Systems - March 2019
Table of Contents for the Digital Edition of Aerospace and Electronic Systems - March 2019
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