R. Prabakaran

Study on ZigBee technology

Wireless Sensor Networks are being gradually introduced in different application scenarios. ZigBee is one of the most widely used transceiver standard in wireless sensor networks. ZigBee over IEEE 802.15.4., defines specifications for low data rate WPAN (LR-WPAN) to support low power monitoring and controlling devices. This paper presents a detailed study of Zigbee wireless standard, IEEE 802.15.4 specification, ZigBee device types, the protocol stack architecture and its applications.

Real time paddy crop field monitoring using Zigbee network

Sensors are the essential device for precision agricultural applications. In this paper we have detailed about how to utilize the sensors in paddy crop field area and explained about Wireless Sensor Network (WSN), Zigbee network, Protocol stack, zigbee Applications and the results are given, when implemented the zigbee network experimentally in real time environment. This paper proposed idea about monitoring the crop field area without human interaction. The fundamental concept of this paper is to provide a highly enabled monitoring of crop field. This paper is focus on the sensing and monitoring of the crop field and gives various sensing analyzes in the paddy crop field.

Rate Optimization Scheme for Node Level Congestion in Wireless Sensor Networks

The Application specific wireless sensor network differs basically from the general data network. It focuses on tight communication but restricted in storage, lifetime, power and energy. The WSNs consists of unbelievable network load and it leads to energy wastage and packet loss. Many of the existing concepts are developed for link level congestion control. The Rate optimization technique for node level congestion will assist to control the traffic at node level. Except source and sink node the remaining nodes may participate in forwarding the packets towards the communication direction. The rate based adjustment technique is applied to avoid packet dropping in order to save the network resources. We are proposing this scheme to avoid the buffer overflow and it is not taking too much energy consumption in the communication. This scheme will assist to improve the throughput, efficiency and resource saving. Node level congestion control is effectively needed for WSN, because the node deployment can be anywhere. We are Introducing this scheme using the network simulators extended tool called mannasim.

Industrial utilization of wireless sensor networks

Currently the need of the hour is how the emerging technologies going to change the existing system. This is an important idea which has been focused by many developers and research scholars. A Wireless Sensor Network (WSN) is a wireless network consisting of different devices that use sensors to monitor physical or environmental conditions. WSN has greatly influenced in developing various applications and provide a new dimension for research scholars. Most research scholars concentrate on experimenting the ideas, proposals which are complex in nature. In industrial systems, instrumentation leads to the designs of high level configurable and automated systems which measures, regulates and process the data. They play important role in wireless sensor network. This paper discusses in detail about the concepts and techniques in the industrial and instrumental usage of wireless sensor networks.

A study on optimized power consumption routing in Wireless Sensor Networks

Two extensively studied and analyzed factors related to Wireless Sensor Networks (WSNs) are optimization of power or energy consumption of node or network and efficient routing mechanism for data transfer between sensor nodes. These two aspects play a major role in the effectiveness and efficiency of the WSN being deployed. This paper, is a study of these aspects of WSN and the various mechanisms that have been proposed to provide an efficient network with reasonable functional time. In this paper, (i) we have studied the various factors that affect the energy consumption of the node and modeled it in a layered approach for better understanding (ii) we have created a framework for the Power Optimized Network Protocol

Queue Reloading Scheme for Congestion Leveling in Wireless Sensor Networks

The Randomly deployed wireless sensor nodes form an unpredictable structure. Normally wireless sensor networks are distinguished from conventional networks by their energy constraints and limited computational power. Huge volumes of data are sensed and generated by the sensor nodes when they are deployed in the dynamic environment. Mostly the source and sink nodes are not within each others transmission range. Congestion occurs when the intermediate nodes forward the data from source to sink. Many of the existing approaches focus on controlling the link level congestions in the network. Our proposed Queue reloading scheme controls the node level congestion. In order to avoid the retransmission of packets, the proposed scheme uses an alternative queue for caching the overflowed packets. The dropped packets are reloaded from the alternative queue when the current queue becomes available. The lifetime of the nodes depend on allocation rate. Our scheme saves the network resources; consuming less energy and aids achievement of improved efficiency and throughput. The node level congestion control is basically needed for WSNs, because the node can be deployed anywhere in the environment.

Implementation of EN-Elman Backprop for Dynamic Power Management

Power utilization has become a major issue in portable designs, since its battery storage is less compared to its usage. One of the popular techniques to solve this problem is to use Dynamic Power Management (DPM) at the system level. Dynamic power management is a technique used to save power when the system is idle. Earlier it was assumed that the prediction can be done only in long range dependent systems which may be a random process or short range dependent. But a single user will not work similarly the next time, so a single assumption will not hold good. To overcome the above assumptions, we propose an Elman Model which uses Moving Average, Elman Back prop network and random walk model to predict the idle period. Here we use Artificial Neural Network (ANN) in which we train the neurons in a particular way the user desires, replacing neurons by time series we can calculate how much power is saved. Our enhanced version consequently reduces energy consumption, noise and cooling requirements. There by we achieve prolong battery life. By simulation we can show that this method achieves higher power saving compared to other methods.

Industrial Monitoring Using Zigbee Network

We have developed a Zigbee network in real time using Zigbee nodes. Discussed Wireless Sensor Network (WSN), Zigbee Technology, and its Applications. Derived results from the network created. Characteristics and network parameters such as data rate, packet delay, Received Signal Strength Indication and packet loss are derived. It is found that this Zigbee network is more suitable for industrial monitoring and control Applications.