CoDA: Collaborative Data Aggregation in Emerging Sensor Networks Using Bio-Level Voronoi Diagrams

Abstract

To implement minimum power consumption of the link, cluster heads adopt the multi-hop manner for inter-cluster communication so as to forward the aggregation data to the relay nodes. This paper proposes a collaborative data aggregation in emerging sensor networks using a bio-level Voronoi diagram, which is an energy-efficient data aggregation protocol that integrates topology control, Multiple Access Control (MAC) and routing. The sensor nodes situated in the lower level of the diagram are responsible for listening and gathering data, and should be organized by optimal clustering node. In the inter-cluster communication stage, a particle swarm optimization algorithm is addressed to seek optimal transmission path which could simultaneously achieve the minimization of the maximum next hop distance between two nodes in the routing path and the minimization of the maximum hop count, so the minimization of whole network energy consumption is realized. The results of theoretical analysis and simulation results show that energy efficiency and synchronization accuracy of the proposed algorithm can be much better than with traditional routing protocols, and the energy consumption of nodes in the whole network can be more balanced.

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