Data Aggregation in Wireless Sensor Networks

2012

A Wireless Sensor network (WSN) (Heinzelman et al., 2000; Yick et al., 2008) consists of a large number of spatially distributed autonomous resource-constrained tiny sensor devices which are also known as sensor nodes (Horton et al., 2002). WSNs have some unique features, for instance, limited power, ability to withstand harsh environmental conditions, ability to cope with node failures, mobility of nodes, dynamic network topology, communication failures, heterogeneity of nodes, large scale of deployment and unattended operation. Although sensor nodes forming WSNs are resource-constrained, i.e., limited power supply, slow processor and less memory, they are widely used in many civilian application areas, including environment and habitat monitoring, healthcare applications, home automation, traffic control and in military applications such as battlefield surveillance (Pottie & Kaiser, 2000).

The main objective of routing in wireless sensor networks (WSN) is to minimize the energy as well as energy while sending the information to sink. Since, the nodes in the WSNs are resource constrained nature; hence the reduced utilization of energy with minimum delay is an important factor. Some of the application in WSN needs continuous monitoring (i.e. the sensors from the Region of Interest (RI) periodically monitor the field and send the sensed data to the sink) which significantly [email protected] increases the data transmission cost in terms of energy, since the nodes in the WSN are resource constrained in nature. In order to reduce the energy utilization of the nodes in these types of applications, the aggregation mechanism plays vital role for providing better trade-off between energy and delay. In this proposed approach a novel Data Aggregation Based Routing Scheme (DABRE) is proposed for time constrained applications of WSNs. In this DABRE an aggregator node is selected from the RI and duly transmits the aggregated information to sink in order to avoid the unnecessary data transmissions as well as unwanted energy utilization.

Data aggregation is an effective technique in saving energy in WSNs. With the help of data aggregation we reduce the energy consumption by eliminating redundancy. The main goal of data aggregation is to gather and aggregate redundant data in an energy efficient manner, so that network lifetime is enhanced. Since it is the most challenging task. Location based aggregation ensures the minimum distance between two nodes while aggregation. In this paper we discuss data aggregation approaches based on routing protocols. Data aggregation framework on wireless sensor network is presented.

Sensor networks are distributed event-based systems that differ from traditional communication networks in several ways: sensor networks have severe energy constraints, redundant low-rate data, and many-to-one flows. Data-centric mechanisms that perform in-network aggregation of data are needed in this setting for energy-efficient information flow. In this paper we model data-centric routing and compare its performance with traditional end-to-end routing schemes. We examine the impact of source-destination placement and communication network density on the energy costs and delay associated with data aggre-gation. We show that data-centric routing offers significant performance gains across a wide range of operational scenarios. We also examine the complexity of optimal data ag-gregation, showing that although it is an NP-hard problem in general, there exist useful polynomial-time special cases.

IJSRD, 2013

The use of Wireless Sensor Networks (WSNs) is anticipated to bring lot of changes in data gathering, processing and dissemination for different environments and applications. However, a WSN is a power constrained system, since nodes run on limited power batteries which shorten its lifespan. Prolonging the network lifetime depends on efficient management of sensing node energy resource. Energy consumption is therefore one of the most crucial design issues in WSN. Hierarchical routing protocols are best known in regard to energy efficiency. By using a clustering technique hierarchical routing protocols greatly minimize energy consumed in collecting and disseminating data. To prolong the lifetime of the sensor nodes, designing efficient routing protocols is critical. In this paper, we have discussed various energy efficient data aggregation protocols for sensor networks.

the prime objective of deploying large-scale wireless sensor networks is to collect information from to control systems associated with these networks. Wireless sensor networks are widely used in application domains such as security and inspection, environmental monitoring, warfare, and other situations especially where immediate responses are required such as disasters and medical emergency. Whenever there is a growth there are challenges and to cope with these challenges strategies and solutions must be developed. This paper discusses the recently addressed issues of data aggregation through presenting a comparative study of different research work done on minimizing delay in different structures of wireless sensor networks. Finally we introduce our proposed method to minimize both delay and power consumption using a tree based clustering scheme with partial data aggregation.

A Wireless Sensor networks are characterized by restricted energy, processing power, and normally limited in communication bandwidth capabilities. The major operation on wireless sensor networks is extracting aggregated information from the network, which can be time-consuming due to environmental dynamics and the huge number of sensor nodes involved there. The nodes implementing the wireless sensor network are themselves limited in computing power and usually have a limited battery life. In this research, we have tried to represent an efficient data aggregation process which uses a randomized architecture in wireless sensor networks. Our intention is to maximize the network lifetime by utilizing data aggregation and in-network processing techniques.

The Wireless Sensor Networks (WSN) is one of the emerging technologies in the field of wireless ad-hoc networks. It consists of several low cost and low power sensor nodes which are capable of sensing, processing and communicating the various environmental parameters. These sensor nodes are randomly and densely deployed in the region of interest. The denser deployment of sensor nodes leads to the sensing and transmission of redundant information. Routing of such redundant data not only saturates the network resources, but also results in the wastage of energy and hence reduces the network lifetime. Data aggregation is the techniques which aggregate the data from different sensor nodes and reduces the redundant transmissions. Data aggregation ensures the efficient utilization of energy and hence enhances the network lifetime. In this paper, we present a survey on different data aggregation techniques for Wireless Sensor Networks.

Iet Communications, 2017

Wireless sensor networks consist of a large number of distributed sensor devices, which are connected and coordinated through multi-hop routing. Due to the existence of correlated information and redundancy in measuring data, data messages can be combined and merged by performing data aggregation function in the routing process. To reduce energy consumption is a major optimisation objective of data aggregation approaches, which can be achieved by decreasing the compulsory communication load of routing. From the theoretical level, an energy model is proposed to validate the benefits of data aggregation on energy consumption. The key parameters which may impact the aggregation performance are further discussed. Finally, the corresponding simulations are implemented in order to verify the analysis conclusions from the theoretical model, and the comparison results can effectively reflect the advantages of data aggregation in different scenarios.

Encyclopedia of Database Systems, 2009