- Lekhraj, Alok Kumar, Pooja verma
Sensor nodes deployment in inaccessible areas so that nodes consume low power energy to transfer the information/data in between the nodes. To enhance the lifetime of the network because sensor nodes are not rechargeable in inaccessible areas.
People using tracking systems
Forest fire detection
Clustering techniques for wireless sensor networks (WSNs) have been extensively studied and proven to improve the network lifetime, a primary metric, used for performance evaluation of sensor networks. Although introduction of clustering techniques has the potential to reduce energy consumption and extend the lifetime of the network by decreasing the contention through either power control or node scheduling, scalability remains an issue. Therefore, the optimality of the cluster size still needs to be thoroughly investigated. In this paper, a single cluster head (CH) queuing model is presented. Using an event based simulation tool (Castalia), key issues that affect the practical deployment of clustering techniques in wireless sensor networks are analysed. These include identifying the bottlenecks in terms of cluster scalability and predicting the nature of data packets arrival distribution at the CH. Results presented show that this analysis can be used to specify the size of a cluster, when a specific flow of data is expected from the sensing nodes based on a particular application and also the distribution of the inter-arrival times of data packets at the CH follows exponential distribution.
In this paper all the deployment is taken place in OMNET++ but there is not a hardware implementation of such type of problems to fell the real life implementation of the this problem.
Performance modelling and evaluation should consider metrics, such as channel bandwidth and arrival distribution of data packets at the CH, and the introduction of new traffic attributes. In this paper, key issues affecting the practical deployment of clustering techniques are thoroughly investigated. Though clustering techniques extend the lifetime of the network, scalability is still an issue, hence the optimality of the cluster size still needs to be thoroughly investigated. In order to have a wider coverage, a trade-off exists between the number of nodes in a cluster being considered and the aggregate packets received at the CH. The results presented show that this analysis can be used to specify the size of a cluster when a specified flow of data is expected from the sensing nodes. In other words, higher packet rates can be accommodated by fewer nodes to attain saturation, as compared to the network with low data rates and higher number of nodes. This directly affects the volume of traffic, the CH can handle. The results presented in order to predict the distribution of interarrival times at the CH follows the exponential distribution phenomenon, thus confirming the Markovian nature of the first parameter in Kendall's notation.