Neighborhood-Based Topology Recognition in Sensor Networks

Abstract

Abstract. We consider a crucial aspect of self-organization of a sensor network consisting of a large set of simple sensor nodes with no location hardware and only very limited communication range. After having been distributed randomly in a given two-dimensional region, the nodes are required to develop a sense for the environment, based on a limited amount of local communication. We describe algorithmic approaches for determining the structure of boundary nodes of the region, and the topology of the region. We also develop methods for determining the outside boundary, the distance to the closest boundary for each point, the Voronoi diagram of the different boundaries, and the geometric thickness of the network. Our methods rely on a number of natural assumptions that are present in densely distributed sets of nodes, and make use of a combination of stochastics, topology, and geometry. Evaluation requires only a limited number of simple local computations.ACM classification: C.2.1 Network architecture and design; F.2.2 Nonnumerical algorithms and problems; G.3 Probability and statistics MSC classification: 68Q85, 68W15, 62E17

Efficient Algorithms for Distributed Detection of Holes and Boundaries in Wireless Networks

“…We compare the performance of our approaches EC-BR and MDS-BR to three well-known boundary recognition algorithms: the algorithm by Fekete et al [8] (labelled Fekete04) and the centralized and distributed algorithms by Funke [9] and Funke et al [10] (labeled Funke05 and Funke06, respectively). In addition, we show qualitative comparisons of these algorithms and the algorithm by Wang et al [19] in Section 6.2.…”

“…Besides, these algorithms often require unrealistic high average node degrees. Prominent statistical approaches are Fekete et al [7,8], and Bi et al [1]. Topological approaches concentrate on information given by the connectivity graph and try to infer boundaries from its topological structure.…”

Topological Boundary Detection in Wireless Sensor Networks

“…As mentioned in Section 1, to the best of our knowledge, up to now only the algorithms in [5][6][7] belong to the topological class. Those in [5,6] are applicable only to uniform and dense wireless sensor networks, while that in [7] is not efficient since it has to solve two complex sub-problems, namely that of beacon selection or leader election, and the flooding problem [13].…”

“…Those in [5,6] are applicable only to uniform and dense wireless sensor networks, while that in [7] is not efficient since it has to solve two complex sub-problems, namely that of beacon selection or leader election, and the flooding problem [13]. Another disadvantage of algorithm [7] is that it does not deal well with network dynamics.…”

“…Up to now, and recently, only a few topological boundary detection algorithms have been proposed [5][6][7]. These algorithms are not competitors with our approach, with the exception of the one introduced in [7], since they seem feasible only for uniform and very high density node distributions.…”