Efficient Data Delivery Model for Wireless Sensor Network

Abstract

Wireless Sensor Networks (WSNs) and Internet of Things (IoT), both are often made up of a broad range of devices like sensor nodes, routers, microcontroller, GPS and communication devices etc. some of are configured by their resources (such as energy, storage and processing) and some of are subject to extremely varied demands so that the data collection is becoming the key application area of the present time. In harsh and emergency situations such as floods, fires, or earthquakes where human participation in monitoring and collecting environmental data is too risky so the wireless sensor networks are typically deployed. Wireless Sensor Networks (WSNs) offer advantages like real-time data collection, low cost, easy deployment, and robustness in harsh environments. For these scenarios, we need to have certain devices which consume low energy to enhance network life time along with data collection models that can provide improvement in all parameters/aspects of WSN. Presently, there are various types of data delivery models, some of are Query-Driven Model, Time-Driven/Periodic Model, Hybrid Model and Event-Driven Model.

In this research paper, we are proposing a new data delivery model (PDDM). This Proposed Data Delivery Model (PDDM) is evaluated with different parameters like throughput, PDR and End to End Delay by using real time implementation of WSN kit. Our proposed model has shown that Periodic model has 50.24% improvement in Throughput, 89.9% improvement in PDR when compared to Event-Driven data delivery model. Event-Driven model showed 74.67% improvement in End-to-End delay when compared to Periodic data delivery model.