Distributed Algorithms to Form Cluster Based Spanning Trees in Wireless Sensor Networks

Abstract

We propose two algorithms to form spanning trees in sensor networks. The first algorithm forms hierarchical clusters of spanning trees with a given root, the sink. All of the nodes in the sensor network are then classified iteratively as subroot, intermediate or leaf nodes. At the end of this phase, the local spanning trees are formed, each having a unique subroot (clusterhead) node. The communication and data aggregation towards the sink by an ordinary node then is accomplished by sending data to the local subroot which routes data towards the sink. A modified version of the first algorithm is also provided which ensures that the obtained tree is a breadth-first search tree where a node can modify its parent to yield shorter distances to the root. Once the subspanning trees in the clusters are formed, a communication architecture such as a ring can be formed among the subroots. This hybrid architecture which provides co-existing spanning trees within clusters yields the necessary foundation for a two-level communication protocol in a sensor network as well as providing a structure for a higher level abstraction such as the γ synchronizer where communication between the clusters is performed using the ring similar to an α synchronizer and the intra cluster communication is accomplished using the sub-spanning trees as in the β synchronizers. We discuss the model along with the algorithms, compare them and comment on their performances.

Energy-Efficient Bridge Detection Algorithms for Wireless Sensor Networks

“…Although this algorithm is simple to implement, execution of central BFS is an expensive operation in terms of energy consumption caused by message transfers, and it is not suitable for large scale self-organizing distributed sensor networks. Because of these reasons, distributed BFS algorithms are proposed [12][13][14][15][16]. For synchronous networks, a well-known greedy algorithm is applied to construct BFS [14].…”

“…Because of these reasons, distributed BFS algorithms are proposed [12][13][14][15][16]. For synchronous networks, a well-known greedy algorithm is applied to construct BFS [14]. This algorithm consumes O( ) messages and O( ) time, where is the diameter of the network.…”

Review of Optimization Problems in Wireless Sensor Networks

“…This problem has been modeled by (Gagarin et al, 2009) as the minimum degree spanning tree (MDST), which is an NP-hard optimization problem. Variations of this problem are encountered in the literature, in (Erciyes et al, 2008;Huang et al, 2006). A joint routing and data aggregation problem is also discussed in (Karaki et al, 2009) for a two-tier network, and some heuristic algorithms such as GA and greedy are proposed.…”

Graph Matching-Based Distributed Clustering and Backbone Formation Algorithms for Sensor Networks

“…In [6], we find one of the algorithms that performs graph-theoretic clustering in sensor networks. Examples of graph-theoretic clustering algorithms for various networks are given in [7][8][9][10][11][12][13][14].…”

“…The following assumptions are made about the network as in [2,6,7,9,12] On the basis of these assumptions, the network may be modeled as a weighted undirected graph G w (V , E w ), where V is the set of vertices, E w is the set of the edges with weights. The weights of the edges can be represented by the link quality indicators supported by various underlying protocols as in [18,19].…”