1 Introduction
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We propose an analytical energy consumption model to determine the optimal number of clusters in a big data WSN. In this model, the communication between two clusters use cooperative transmission. By using cooperative nodes, we can reduce the energy consumption of cluster heads efficiently and prolong the lifetime of network.
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We propose a centralized clustering algorithm based on spectral partitioning and a distributed implementation of the clustering method based on fuzzy C-means in cluster head selection.
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We verify the performance of the proposed algorithm in terms of network lifetime and node remaining energy. In particular, our algorithm can decrease the interval between the time of the first node dying and the time of the last node dying, which implies our algorithm can efficiently balance the energy consumption among sensor nodes.
2 Related work
3 Network model and spectral classification
3.1 Network model
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The network topology keeps unchanged over time, and the base station has unlimited power, computing ability, and locates at the network center.
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Nodes are deployed uniformly, and all the nodes are homogeneous.
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Each node is aware of its own position through RSSI localization.
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All sensor nodes are static, and their battery cannot be recharged.
3.2 Energy model
3.3 Laplacian matrix and Fiedler vector
4 Clustering algorithm
4.1 The optimal number of clusters
4.2 Clustering algorithm
4.2.1 Centralized clustering algorithm
4.2.2 Distributed clustering algorithm
4.3 Cooperative nodes and cluster head selection
4.3.1 Strategy to choose cooperative sensor nodes
4.3.2 Cluster head selection
Distance to CN | Residual energy | Probability |
---|---|---|
Close | High | Very high |
Close | Rather high | Rather high |
Close | Medium | High |
Close | Rather low | Very low |
Close | Low | Very low |
Close | Very low | Very low |
Medium | High | High |
Medium | Rather high | Rather high |
Medium | Medium | Medium |
Medium | Rather low | Medium |
Medium | Low | Very low |
Medium | Very low | Very low |
Far | High | Medium |
Far | Rather high | Medium |
Far | Medium | Rather low |
Far | Rather low | Rather low |
Far | Low | Low |
Far | Very low | Very low |
5 Simulation results
Parameter | Value |
---|---|
E
elec
| 50 nJ/bit |
ε
fs
| 10 pJ/bit/m2 |
ε
amp
| 0.0013 pJ/bit/m4 |
E
DA
| 5 nJ/bit/message |
Size of message | 4000 bits |
Initial energy | 0.5 j |