Data Transmission In Wireless Sensor Networks Research Articles

Comparative Study of Classification Techniques with Labeled Data in Wireless Sensor Network

The wireless sensor nodes are getting smaller, but Wireless Sensor Networks (WSNs) are getting larger with the technological developments, currently containing thousands of nodes and possibly millions of nodes in the future. To deal with the large volume of data produced by these special kinds of wireless networks, one approach is use of Data Mining techniques. Classification is an important task in data mining. Classification of sensory data is a major research problem in WSNs and it can be widely used in reducing the data transmission in WSNs effectively and also in process monitoring. In this paper, Labelled Wireless Sensor Network Data is used for mining. This multihop data consist of humidity and temperature measurements. To mine the sensor data three classification techniques J48(Decision Tree), Naive Bayes, and ZeroR are considered in this study. Experimental investigation yields a significant output in terms of the correctly classified instances. At the end it has been found that Naive Bayes is a suitable method to classify the large amount of data considered is made finally according to the mining result.

A local synchronization protocol for low-power data transmission in wireless sensor networks

Advances of the identifying, sensing, and communicating technologies make the applications of Internet of Things (IoT) possible. Among others, the ubiquitous deployment of wireless sensor networks (WSNs) is regarded as one of the most significant forces in the IoT. Great progress in micro-electro-mechanical systems and wireless communications make the applications of WSNs more and more accessible. The limited battery power of the sensor node is vitally precious. Therefore, it is important to promote the energy efficiency to stretch the lifetime of the WSNs. In this paper, a low-power data transmission protocol, which includes a dual-frequency model, local synchronization, and channel reservation, is proposed. The results of numerical analyses and simulations show that the proposed protocol presents better energy efficiency without sacrificing end-to-end latency of data transmission in WSNs.

Efficient data aggregation with in-network integrity control for WSN

Energy is a scarce resource in Wireless Sensor Networks (WSN). Some studies show that more than 70% of energy is consumed in data transmission in WSN. Since most of the time, the sensed information is redundant due to geographically collocated sensors, most of this energy can be saved through data aggregation. Furthermore, data aggregation improves bandwidth usage and reduces collisions due to interference. Unfortunately, while aggregation eliminates redundancy, it makes data integrity verification more complicated since the received data is unique.In this paper, we present a new protocol that provides control integrity for aggregation in wireless sensor networks. Our protocol is based on a two-hop verification mechanism of data integrity. Our solution is essentially different from existing solutions in that it does not require referring to the base station for verifying and detecting faulty aggregated readings, thus providing a totally distributed scheme to guarantee data integrity.We carried out numerical analysis and simulations using the TinyOS environment. Results show that the proposed protocol yields significant savings in energy consumption while preserving data integrity, and outperforms comparable solutions with respect to some important performance criteria.

Wireless Sensor Networks Data Transmission Based on Congestion by Cognized Routing Protocol

In wireless sensor networks (WSNs), sensor nodes share wireless channels to communicate with each other. So, link congestion often occurs and induces data retransmission easily. To avoid these issues, data transmission efficiency would be greatly enhanced and the energy consumption of network would save a lot. Based on this idea, we have designed a transmission-effective congestion-cognized (TECC) routing protocol in the paper. Routings are selected probabilistically and real-timely, according to the out-bound nodes’ satisfactory degrees of forwarding. Also, time stamps are used to control nodes’ status, effectively reducing the occurrence probability of conflict and link congestion in networks. Simulation results show that, TECC routing protocol has good performances of low-latency and energy-consuming equilibrium, which could significantly improve energy utilization and data transmission efficiency of network.

One Unequal Error Control Method for Telemetric Data Transmission

One Unequal Error Control Method for Telemetric Data TransmissionIn wireless sensor networks (WSN) it is necessary to use very simple codes for transmission of information since the nodes in these networks have usually only limited energy available not only for transmission but also for processing. On the other hand, common codes do not usually take into account the fact that in case of telemetric information the weights of individual orders are not equal and errors in different orders cause different deviations from correct value. In this contribution, new very simple codes for transmission of telemetric information on WSN will be presented, which take into account the above-mentioned requirements. Resulting square deviation will be used as a quality evaluation criterion.

An efficient online‐battery aware geographic routing algorithm for wireless sensor networks

AbstractWireless sensor networks (WSNs) are being used in a wide variety of critical applications such as military and health‐care applications. Such networks, which are composed of sensor nodes with limited memory capacity, limited processing capabilities, and most importantly limited energy supply, require routing protocols that take into consideration these constraints. The aim of this paper is to provide an efficient power aware routing algorithm for WSNs that guarantees QOS and at the same time minimizes energy consumption by calculating the remaining battery capacity of nodes and taking advantage of the battery recovery process. We present an online‐battery aware geographic routing algorithm. To show the effectiveness of our approach, we simulated our algorithm in ns2 and compared it with greedy perimeter stateless routing for wireless networks and battery‐aware routing for streaming data transmissions in WSNs. Copyright © 2009 John Wiley & Sons, Ltd.

Transmission power adjustment of wireless sensor networks using fuzzy control algorithm

AbstractEnergy constraint is the most conspicuous characteristic in wireless sensor networks (WSN). Node deployment, dynamic topology control, and data transmission in WSN all consume a large amount of energy. Therefore, proper adjustment of transmission power (TP) contributes much energy saving. In this paper, a new TP adjustment method based on Fuzzy Control Theory, called FCTP, is proposed for the dynamic topology control. The simulation results show that this method is more robust to tolerate accidental interfere, more rapidly convergent, and more energy efficient than other TP adjustment approaches, which lead to longer network lifetime. Copyright © 2008 John Wiley & Sons, Ltd.