Abstract
The simple graph theory is commonly employed in wireless sensor networks topology control. An inherent problem of small-granularity algorithms is the high computing complexity and large solution space when managing large-scale WSNs. Computed transmission paths are of low fault tolerance because of unattended sensor nodes and frail wireless transmitting channels. This paper uses hyper-graph theory to solve these practical problems and proposes a spanning hyper-tree algorithm (SHTa) to compute the minimum transmitting power delivery paths set for WSNs convergecast. There are three main contributions of this paper: (1) we present a novel hyper-graph model to abstract large-scale and high connectivity WSNs into a robust hyper-tree infrastructure; (2) we present a precise mathematical derivation that solves the “hyper-tree existence” problem; (3) SHTa is proposed to compute the delivery paths set, which is the minimum power transmitting convergecast hyper-tree. Variable scale hyper-edges represented as computing units limit solution space and reduce computing complexity. Mutual backup delivery paths in one hyper-edge improve the capability of fault tolerance. With experiment results, SHTa computes short latency paths with low energy consumption, compared with previous algorithms. Furthermore, in dynamic experiments scenes, SHTa retains its robust transmitting quality and presents high fault tolerance.
Highlights
Self-organized wireless sensor networks can be used to cooperatively detect and perceive real objects
A wireless sensor network is generalized as data center, and the optimum number of transmissions required per datum in the DC (Data Centre) is equal to the number of edges in the Minimum Steiner Tree (MST)
If the weight of edges is defined as energy consumption, MST is just the optimal energy consumption tree in the wireless sensor network
Summary
Self-organized wireless sensor networks can be used to cooperatively detect and perceive real objects. Because of the low reliability of the sensor nodes and wireless communication links, many real-time control messages have to be used to maintain an established path. These tasks use significant amount of bandwidth and consume the extra energy. To solve this problem, in this paper, we used the hypergraph theory and proposed Spanning Hyper-Tree algorithm (SHTa) to create a concise and robust hyper-graph infrastructure for large-scale and high connectivity self-organized wireless networks. More than one connected pairs in a hyperedge provides high bandwidth and low loss rate during transmission
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