Author Description

The Internet of Things (IoT) has brought countless opportunities over a decade in every part of the world. IoT, also an extended version of the localized Wireless Sensor Network (WSN) is employed to realize billions of intelligent, pervasive, smart devices and infrastructure. IoT has a layered architecture. The WSN is a part of its lowest layer called the perception layer. A WSN consists of a number of sensor devices also called nodes. These nodes encapsulate some basic units to perform various operations like sensing, data transmission, data storage, and data processing. The primary objective of a sensor node is to sense the data from its surroundings, collect this data and send it to the destination node or Base station, either using a single-hop approach or multi-hop approach of data transmission. In an IoT architecture, an intermediate node called a gateway node collects the information from all nodes in the network. The data from the gateway is communicated to the cloud using the Internet. The WSNs are highly resource-constrained networks. Nodes consume high energy in case of massive data transfer between node to node or nodes to B.S. Because of this the sensor nodes start depleting this constraint energy thereby impeding the data collection process. This is a major challenge in various WSN applications and is also termed as energy-hole problem. The massive data gathering enhances the risk of increased end-to-end delay and congestion, which in turn affects other QoS parameters. The problems of congestion, energy hole, etc have been addressed by many researchers. However, most of the literature do not focus on the changes affecting WSNs dynamically. An efficient design of dynamic data transmission model and algorithms are needed to manage high scalability of nodes and massive data flow amongst.