Development Of Virtual Backbone Scheduling Technique For Faster Data Collection In Wireless Sensor Networks


P. Vignesh Raja
S. Subasree
N. K. Sakthivel


The past two decades have witnessed the boom of Wireless Sensor Networks (WSNs) and a key technology for various applications that involve long-term and low-cost monitoring, such as Battlefield Reconnaissance, Building Inspection, Security Surveillance and etc. In most WSNs, the battery is the sole energy source of the sensor node. Sensor nodes are expected to work on batteries for several months to a few years without replenishing. Thus, energy efficiency becomes a critical issue in WSNs. The ultimate goal of a sensor network is often to deliver the sensing data from all sensors to a sink node and then conduct further analysis at the sink node. Thus, data collection is one of the most important common services used in sensor network applications. In the existing techniques, different approaches have been used to realistic simulation models under the many-to-one communication paradigm known as convergecast.  In the TDMA scheduling technique, it consider time scheduling on a single frequency channel with the aim of minimizing the number of time slots required (schedule length) to complete a converge cast. By using this scheduling mechanism, the data collection is higher than previous mechanisms.  However, from our experimental results, this Project Work is realized that the TDMA Scheduler unable to collect data from large Sensor Networks.  This is the major identified problem.  To address this issue, this paper proposed an efficient Virtual Backbone Scheduling (VBS) Technique.  From our experimental results, it is observed that the proposed work improves the performance of Wireless Sensor Networks interms of Network Error Rate, Sensor's Lifetime, Communication Cost and Scheduling Time as compared with existing technique.  It is also observed that the proposed work improves the performance of Data Collection Process, which saves Battery Life Time and the Scheduling Time.