Abstract
In recent years, energy-efficient data collection has evolved into the core problem in the resource-constrained Wireless Sensor Networks (WSNs). Different from existing data collection models in WSNs, we propose a collaborative data collection scheme based on optimal clustering to collect the sensed data in an energy-efficient and load-balanced manner. After dividing the data collection process into the intra-cluster data collection step and the inter-cluster data collection step, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius. Then, we design a Cluster Heads (CHs)-linking algorithm based on the pseudo Hilbert curve to build a CH chain with the goal of collecting the compressed sensed data among CHs in an accumulative way. Furthermore, we also design a distributed cluster-constructing algorithm to construct the clusters around the virtual CHs in a distributed manner. The experimental results show that the proposed method not only reduces the total energy consumption and prolongs the network lifetime, but also effectively balances the distribution of energy consumption among CHs. By comparing it o the existing compression-based and non-compression-based data collection schemes, the average reductions of energy consumption are 17.9% and 67.9%, respectively. Furthermore, the average network lifetime extends no less than 20-times under the same comparison.
Highlights
Nowadays, wireless sensor networks have emerged as a powerful and low-cost platform for connecting the physical world to the digital world [1]
Aiming at answering the above questions, we propose a collaborative data collection scheme based on optimal clustering for periodical data collection in Wireless Sensor Networks (WSNs)
After evaluating the intra-cluster energy consumption and the inter-cluster energy consumption individually, we model the optimal clustering problem as a separable convex optimization problem and solve it to obtain the analytical solutions of the optimal clustering size and the optimal data transmission radius
Summary
Wireless sensor networks have emerged as a powerful and low-cost platform for connecting the physical world to the digital world [1]. We propose a cluster heads-linking algorithm based on the pseudo Hilbert curve to collect the compressed sensed data among cluster heads in an accumulative way. We design a cluster heads-linking algorithm based on the pseudo Hilbert curve to collect the compressed sensed data among cluster heads in a collaborative and accumulative manner. We design a distributed cluster-constructing algorithm to construct the inter-cluster data collection structure around virtual cluster heads in a wireless sensor network. CS-based data collection schemes in WSNs. In Section 3, we model the optimal clustering problem and solve it analytically to obtain the optimal network parameters.
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