Non-uniform deployment of nodes in clustered wireless sensor networks

Abstract

Abstract-In this paper, we consider the problem of placing, with course-grained control, a large number of wireless networked sensor nodes employing a clustering network architecture. The goal of the deployment strategy is to maximize the lifetime while ensuring connectivity between cluster-heads so that samples from the monitored area may be forwarded to a fusion center. A model is derived to approximate the lifetime of a differentially deployed random network using both the density of cluster-heads and non-clusterheads as variables. Through optimization of the lifetime expression over both variables and through simulation results, it is shown that 1) a differential node deployment with a uniform cluster-head density increases the lifetime of the network over a uniform deployment and 2) the addition of a suitable differential cluster-head density further increases lifetime over the differential node deployment with uniform cluster-head density.

Optimal deployment and replenishment of monitoring wireless sensor networks

“…A solution to this problem was given in [1]; under this deployment the increase in network lifetime is shown to exhibit diminishing marginal increases as more nodes are deployed. Figure 1 shows numerical results for the optimal expected lifetime for three different deployment strategies: uniform, static p, and dynamic.…”

“…Using the expected values described above, an expression, in terms of the node densities λ and clusterhead probabilities p for each band, can be written for the expected energy consumption in each band (see [1] for complete derivation):…”

“…In a random deployment, as opposed to a deterministic placement where nodes are placed in specific predetermined locations, nodes are placed with coarse-grain control, either by dropping them from an aircraft or releasing them from a moving vehicle. Recently, there have been many efforts to design models and deployment strategies that optimize an objective such as maximizing lifetime (e.g., [1]), minimizing energy consumption (e.g., [2]), maximizing detection probability (e.g., [3]), and minimizing estimation error (e.g., [4]), subject to similar constraints. The decision variables in many of these works is the density of nodes to place over the monitored area.…”

Clustering algorithm for non‐uniformly distributed nodes in wireless sensor network

“…Let the sensor network field be circular with radius R and divided into J number of annular bands of the same radial width r with different densities of nodes in each band. Nodes are distributed non‐uniformly in theses annular bands by taking a variable density parameter , whose value can be changed for different kinds of deployment patterns [6]. The number of nodes in an annular band is as shown in Fig.…”