scholarly journals Sensor Node Placement in Wireless Sensor Network Based on Territorial Predator Scent Marking Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Husna Zainol Abidin ◽  
Norashidah Md. Din

Optimum sensor node placement in a monitored area is needed for cost-effective deployment. The positions of sensor nodes must be able to provide maximum coverage with longer lifetimes. This paper proposed a sensor node placement technique that utilizes a new biologically inspired optimization technique that imitates the behaviour of territorial predators in marking their territories with their odours, known as territorial predator scent marking algorithm (TPSMA). The TPSMA deployed in this paper uses the maximum coverage objective function. A performance study has been carried out by comparing the performance of the proposed technique with the minimax and lexicographic minimax (lexmin) sensor node placement schemes in terms of coverage ratio and uniformity. Uniformity is a performance metric that can be used to estimate a WSN lifetime. Simulation results show that the WSN deployed with the proposed sensor node placement scheme outperforms the other two schemes with larger coverage ratio and is expected to provide as long lifetime as possible.

2014 ◽  
Vol 39 (8) ◽  
pp. 6317-6325 ◽  
Author(s):  
H. Zainol Abidin ◽  
N. M. Din ◽  
I. M. Yassin ◽  
H. A. Omar ◽  
N. A. M. Radzi ◽  
...  

WSN are the group nodes and these nodes are grouped into several clusters, each cluster has its own CH (Cluster Head). Moreover, each cluster Head collects the data and sends either through the corresponding CH or through the CH. Moreover, the clustering plays one of the eminent role in WSN, since Clustering reduces the energy consumption in the cluster Head and improvises the lifetime and scalability of WSN. However, this maximizes the burden on the CH and certainly, it causes the coverage loss. Hence, in this paper we design a model named as EE-NCT (Energy Efficient model for maximizing the network coverage time) which helps in increasing the Network Coverage time for the non-deterministic model, i.e. Sensor nodes location are not known. Non –deterministic model makes hard to maximize, as the node placement is not known. Moreover, this is achieved through monitoring the sensor node location and applying the routing based clustering scheme. Our model is evaluated by considering the various constraint such as first sensor node death, 75% of node death and loss of connectivity by considering the parameter as energy consumption and average number of failed nodes


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