Energy-Balancing and Lifetime Enhancement of Wireless Sensor Network with Archimedes Spiral

Abstract

Abstract.Energy is one of the scarcest resources in wireless sensor network (WSN). Therefore, the need to conserve energy is of utmost importance in WSN. There are many ways to conserve energy in such a network. One fundamental way of conserving energy is judicious deployment of sensor nodes within the network area so that the energy flow remains balanced throughout the network. This avoids the problem of occurrence of 'energy holes' and ensures prolonged network lifetime. In this paper, we have identified intrinsic features of Archimedes' Spiral and shown its suitability to model the layered WSN area. Next we have transformed the same Spiral in its discrete form and proposed this as a deployment function. A node deployment algorithm is developed based on this deployment function. Further, we have identified necessary constraints involving different network parameters to ensure coverage, connectivity and energy balance of the entire network. Performance of the deployment scheme is evaluated in terms of energy balance and network lifetime. Both qualitative and quantitative analyses are done based on these two performance metrics. Finally the scheme is compared with an existing Gaussian distribution-based deployment scheme and the results confirm the superiority of our scheme in respect to both the metrics over the existing one.

Lifetime Optimizing Clustering Structure Using Archimedes’ Spiral-Based Deployment in WSNs

“…It has been observed in recent state of the art [14] that, other than mitigating the energy hole problem, the predetermined node deployment shows significant improvement in end-toend delay, throughput, packet loss, etc. Keeping this in mind, we proposed a predetermined node deployment strategy based on Archimedes' spiral [15]. We have examined different standard geometric models, e.g., Gaussian distribution, and found Archimedes' spiral to be the one that can be modeled as layered network architecture because the successive circular turns of Archimedes' spiral have a constant separation distance.…”

“…Therefore, for any given region in a layer, (15) gives the maximum permissible number of circular turns. As R s and B are constants, the number of circular turns for a given layer depends on the area parameter, i.e., w i .…”

“…An Archimedes' spiral is a continuous spiral [15] with polar equation R d = θB, where R d is the radial distance, θ is the polar angle, and B is a real number, and its value is a constant. The distance between two successive circular turns can be calculated using B.…”

Research on 3D Wireless Sensor Networks ISC-EAR Routing Algorithm

“…Its objective is to minimize the power consumption, improve the use time of the network. The algorithm GFG (Greedy Face Greedy) [14] is a classical wireless sensor network Routing algorithm, the algorithm used at the beginning of the Routing Greedy Routing algorithm choose destination node nearest neighbor node as the next hop, when Routing hole (Local Minimum), use Face Routing algorithm make the data along the area of line segments in the plane of the mobile, when faced with a closer than their own away from the destination node, continue to use the Greedy Routing algorithm for data delivery. In order to overcome the shortage of GFG algorithm, reference [15] presented for local geography routing algorithm GRG (Greedy Random Greedy), the algorithm application of RW (Random Walks) algorithm recovery mechanism to avoid the local minimum.…”

Is sensor deployment using Gaussian distribution energy balanced?

“…Random deployment is typically used in physically inaccessible areas e.g., volcanoes, seismic zones, etc. where nodes are usually dropped from helicopter [2], [3]. On the other hand, deterministic deployment is preferable in physically accessible areas e.g., target tracking, urban monitoring, soil monitoring etc., where sensors are placed by hand at selected spots prior to network operation [2], [3].…”