ACRDA: An adaptive combined relay based dynamic data aggregation technique for wireless sensor networks

Abstract

Based on the monitoring environment, the frequent generation of extensive amounts of redundant sensing data is processed in the WSN applications. For reducing the consumption of energy in a network, aggregation of all these data with efficient methods of data aggregation is playing a key role. For aggregating the generated large amounts of data from sensor nodes, various clustering techniques have been used. In the closed and less or partially-dense sensor environments only, effectiveness shows by such type of algorithms of data aggregation. Also, in most of the clustering environments, the CH nodes are forced to send the sink node which locates distant away from the CHs, due to the ineffectiveness of the clustering and CH selection algorithms. Here, an adaptive combined relay based Dynamic data aggregation technique was proposed that could dynamically adapts with the network and aggregate the data in two ways. If the hop count between the sensors and CHs is higher than the hop count between sensors and sink directly, the sensors can be transmitted the data directly to the SINK without the requirement of data aggregation at CH levels. If the hop count exceeds, then the normal data aggregation at the CHs would apply. Also to improve the stable CH selection, the CHs are selected based on ERROR RATE & QUEUE LENGTH. This dynamic data aggregation technique can adaptively aggregate the data at any kind of environments and the efficiency of data aggregation and energy consumption can improve over the network. The proposed data aggregation mechanism has been proved the better performance than the earlier algorithms based on the experimental results.