Advances in microelectronic mechanical systems (MEMS) and wireless communication technologies have enabled wireless sensor networks (WSNs) to do a wide range of tasks, such as environmental detection, traffic monitoring, and control. WSNs are composed of hundreds or even thousands of sensor nodes. They are designed and implemented for monitoring the physical world, gathering sensed information, and transmitting the generated data packets to interested end users. In emergent event reporting applications, such as forest fire detection and toxic gas leak detection, sensor nodes detect events or phenomena respectively and report sensed data to sink node as soon as possible.

WSNs are aiming at gathering integrated information rather than collecting individual data packets. Although each sensor node may seem to be lacking in capability and reliability, a collective effort of the sensor nodes may provide sensing capabilities that satisfy the end users' needs. Since generated data packets at nodes are not independent, data correlation should be taken into consideration. Instead of reporting the raw data at 100% probability, sensor nodes in READ utilize their processing abilities to carry out simple computations locally and report it at the minimal probability. It uses combined methods of multi-point coverage and multi-path forwarding but not doing in-network data aggregation. READ uses ReInforM for multi-path data packets forwarding and controls the number of copies by exploiting the data correlation among neighbor nodes with Data Correlation Processing (DCP) algorithm. To suppress data transmission, READ subtracts redundancy from data packets only using local knowledge of neighbor information and topology. Such suppression of data packets transmissions enables information gathering with the lowest traffic without compromising on the integrated information.

Our simulation witnessed the fact that READ ensured the integrated information in event area was gathered and transferred to sink node at a desired level of reliability. The total data transmissions were tremendously cut down and the power consumption was dramatically economized compared with protocols not using DCP (N-DCP).