A study on data aggregation techniques in wireless sensor network in static and dynamic scenarios

Small-size sensor nodes are used as the basic component for collecting and sending the data or information in the ad hoc mode in wireless sensor network (WSN). This network is generally used to collect and process data from different regions where the movement of human is very rare. The sensor nodes are deployed in such a region for collecting data using ad hoc network where, at any time, the unusual situation may happen or there is no fixed network that can work positively and provide any transmission procedure. The location may be very remote or some disaster-prone area. In disaster-prone zone, after disaster, most often no fixed network remains alive. In that scenario, the ad hoc sensor network is one of the reliable sources for collecting and transmitting the data from that region. In this type of situation, sensor network can also be helpful for geo-informatic system. WSN can be used to handle the disaster management manually as well as through an automated system. The main problem for any activity using sensor node is that the nodes are very much battery hunger. An efficient power utilization is required for enhancing the network lifetime by reducing data traffic in the WSN. For this reason, some efficient intelligent software and hardware techniques are required to make the most efficient use of limited resources in terms of energy, computation and storage. One of the most suitable approaches is data aggregation protocol which can reduce the communication cost by extending the lifetime of sensor networks. The techniques can be implemented in different efficient manners, but all are not useful in same application scenarios. More specifically, data can be collected by dynamic approach using rendezvous point (RP), and for that purpose, intelligent neural network-based cluster formation techniques can be used and for fixing the targeted base station, the ant colony optimization algorithm can be used. In this work, we have made a comprehensive study of such energy efficient integrated sensor-based system in order to achieve energy efficiency and to prolong network lifetime.