Stochastic analysis of data collection using Mobile Sink with fixed and variable trajectories

One of the main applications of Wireless Sensor Networks (WSN) is monitoring environmental parameters. The urban areas are covered by Sensor Nodes (SN), which collect data and forward to Mobile Sink (MS). MS travels in variable trajectory and collect data from SN within the range. The existing approaches single hop data transfer from SN that is within the range of MS or the node close to MS are heavily used and hence, their energy is consumed faster. To minimize the overall network overhead, balanced energy expenditure, and prolong network lifetime, we present a model. This is done by selecting a better path of MS such that balancing traffic load in network. Then cluster structure is built and it forwards the data to assigned Cluster Head (CH). CH performs filtering and forwards the filtered data to an end node with sufficient energy, located close to MS. Stochastic programming is used to analyze energy consumption and effectiveness is compared against other methods.