FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network
<p>An overview of the FTUC protocol including the ’referenced position circles’ to elect evenly the CHs.</p> "> Figure 2
<p>Timeline showing the operations of FTUC: at the first iteration, it builds a tree type sub-network. Then, periodically, it forms the clusters, and progresses to the steady state, where sensing and data transmissions are performed.</p> "> Figure 3
<p>Flooding tree algorithm phases to build a tree type sub-network. The flooding phase enables one to create a unique and fast path between all nodes in the network. (<b>a</b>) Network initialization; (<b>b</b>) Running flooding tree algorithm; (<b>c</b>) Build tree type network; (<b>d</b>) Network finished.</p> "> Figure 4
<p>Cupcarbon simulation of FTUC. Cluster heads are evenly distributed in the network, and unequal clusters are created.</p> "> Figure 5
<p>Number of elected CH per 10 rounds, depending on the competition radius calculation.</p> "> Figure 6
<p>Evolution of M<sub>E</sub>(t) depending on the C value.</p> "> Figure 7
<p>C1 and C2 value influences on the mean residual energy of the network. Well-positioned fCHs enables one to prolong the network lifetime.</p> "> Figure 8
<p>Variance of residual energy depending on C1 and C2. Lowering C2 increases σ<sub>E</sub>(t) as the residual energy of nodes has less impact on the fCH selection.</p> "> Figure 9
<p>Evolution of the mean residual energy depending on the referenced position circles.</p> "> Figure 10
<p>T value impact on network lifetime.</p> "> Figure 11
<p>Impact of the iteration time T<sub>R</sub> on the network LT-1 lifetime.</p> "> Figure 12
<p>Network alive node numbers depending on time using LEACH, UCR, and FTUC.</p> "> Figure 13
<p>Variance of residual energy for each network. FTUC enables one to have a better repartition over time, increasing the network lifetime.</p> ">
Abstract
:1. Introduction
- A clustering algorithm enabling the CH election in large WSNs by building a tree network to convey the global minimum and maximum distance data to the BS.
- A way to balance the uneven distribution of CH by introducing referenced positions to elect CH, which balance the network load and prolong the network lifetime.
- The construction of unequal clusters to optimize the energy consumption of the overall network.
- A set of simulations to show the effectiveness of our approach, and to compare to state-of-art algorithms.
2. Related Work
3. Definitions and Models
3.1. Network Model
3.2. Node Energy Model
3.3. Network Life Cycle
3.4. Energy Consumption Balance
4. Problem Statements
4.1. Unevenly Distributed Cluster Problem
4.2. Global Minimum and Maximum Distances Problem
5. FTUC Algorithm
5.1. Flooding Tree Subnetwork
Algorithm 1 Building the tree sub-network | |
Input: id root Output: leaf | |
1: id = getId() | 13: if (type == T1) and (once == false) then |
2: if (id == id root) then | 14: once = true |
3: leaf = false | 15: message = (T2, id) |
4: once = true | 16: send(message, rid) |
5: message = (T1, id) | 17: message = (T1, id) |
6: send(message, *) | 18: send(message, *) |
7: else | 19: end if |
8: leaf = true | 20: if (type == T2) then |
9: once = false | 21: leaf = false |
10: end if | 22: end if |
11: while (true) do | 23: end while |
12: (type, rid) = read() |
5.2. Building Cluster Phase
5.3. Inter-Cluster Communication
5.4. Stable Communication Phase
6. Simulation and Analysis
6.1. FTUC Parameterization
6.2. Analysis of Cluster Creation
6.3. Energy Efficiency
7. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Parameter | Value |
---|---|
50 | |
6 | |
0.0011 | |
87 | |
0.001 | |
0.001 |
Parameter | Value |
---|---|
C, C1, C2 | 0.8, 0.8, 0.2 |
T, R0 | 0.08, 200 |
TR (s) | 800 |
0.4, 0.3, 0.3 |
LT-1 (s) | LT-2 (s) | Improved of LT-1 (%) | Improved of LT-2(%) | |
---|---|---|---|---|
LEACH | 5420 | 34,510 | 186.3 | 130.6 |
UCR | 13,380 | 63,810 | 16.0 | 24.7 |
FTUC | 15,520 | 79,510 |
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He, W.; Pillement, S.; Xu, D. FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network. Sensors 2017, 17, 2706. https://doi.org/10.3390/s17122706
He W, Pillement S, Xu D. FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network. Sensors. 2017; 17(12):2706. https://doi.org/10.3390/s17122706
Chicago/Turabian StyleHe, Wei, Sebastien Pillement, and Du Xu. 2017. "FTUC: A Flooding Tree Uneven Clustering Protocol for a Wireless Sensor Network" Sensors 17, no. 12: 2706. https://doi.org/10.3390/s17122706