Target Aucourant Data Dissemination by Collaboratory Sensing in IOT Environment

Abstract

Spatially Identifying and communicating corresponding objects in a massively distributed Internet of Things environment is crucial. Objects or the nodes self-governing to monitor the environmental conditions such as pressure, humidity, sound and temperature cooperatively transmit sensed data from the mote to the desired location without human interface. As the sensors are resource constrained device efficacious topology is required to manage, to aggregate and disseminate data from the base station to the cloud service in the business layer. To handle this challenge, an efficient Event Based Echeloned Topology (EBET) is deployed using convex hull for electing collaborators and typically constructing event based region for the coordinator nodes using R+ tree. Convex hull ensures that with the less number of nodes maximum coverage is accomplished and also supports traffic forwarding. R+ tree ensures that search regions are divided efficiently based on events. An Event-Based Data Aggregation algorithm is used which does intra data aggregation at the coordinator using absolute deviation and inter data reduction at the collaborator using polynomial regression. Data accuracy and data privacy are preserved using polynomial regression. Thus, the proposed topology with efficient intra and inter aggregation reduces overall latency, energy consumption and also preserved the data accuracy of the nodes thereby network lifetime is improved.