Power Aware Routing for Sensor Databases

Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), and high communication costs, design of energy efficient communication algorithms is of great importance. The data flow in a sensor database is very different from data flow in an ordinary network and poses novel challenges in designing efficient routing algorithms. In this work we explore the problem of energy efficient routing for various different types of database queries and show that in general, this problem is NP-complete. We give a constant factor approximation algorithm for one class of query, and for other queries give heuristic algorithms. We evaluate the efficiency of the proposed algorithms by simulation and demonstrate their near optimal performance for various network sizes

Energy-Efficient Data Management in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are deployed widely for various applications. A variety of useful data are generated by these deployments. Since WSNs have limited resources and unreliable communication links, traditional data management techniques are not suitable. Therefore, designing effective data management techniques for WSNs becomes important. In this dissertation, we address three key issues of data management in WSNs. For data collection, a scheme of making some nodes sleep and estimating their values according to the other active nodes’ readings has been proved energy-efficient. For the purpose of improving the precision of estimation, we propose two powerful estimation models, Data Estimation using a Physical Model (DEPM) and Data Estimation using a Statistical Model (DESM). Most of existing data processing approaches of WSNs are real-time. However, historical data of WSNs are also significant for various applications. No previous study has specifically addressed distributed historical data query processing. We propose an Index based Historical Data Query Processing scheme which stores historical data locally and processes queries energy-efficiently by using a distributed index tree. Area query processing is significant for various applications of WSNs. No previous study has specifically addressed this issue. We propose an energy-efficient in-network area query processing scheme. In our scheme, we use an intelligent method (Grid lists) to describe an area, thus reducing the communication cost and dropping useless data as early as possible. With a thorough simulation study, it is shown that our schemes are effective and energy- efficient. Based on the area query processing algorithm, an Intelligent Monitoring System is designed to detect various events and provide real-time and accurate information for escaping, rescuing, and evacuation when a dangerous event happened

An objective based classification of aggregation techniques for wireless sensor networks

Wireless Sensor Networks have gained immense popularity in recent years due to their ever increasing capabilities and wide range of critical applications. A huge body of research efforts has been dedicated to find ways to utilize limited resources of these sensor nodes in an efficient manner. One of the common ways to minimize energy consumption has been aggregation of input data. We note that every aggregation technique has an improvement objective to achieve with respect to the output it produces. Each technique is designed to achieve some target e.g. reduce data size, minimize transmission energy, enhance accuracy etc. This paper presents a comprehensive survey of aggregation techniques that can be used in distributed manner to improve lifetime and energy conservation of wireless sensor networks. Main contribution of this work is proposal of a novel classification of such techniques based on the type of improvement they offer when applied to WSNs. Due to the existence of a myriad of definitions of aggregation, we first review the meaning of term aggregation that can be applied to WSN. The concept is then associated with the proposed classes. Each class of techniques is divided into a number of subclasses and a brief literature review of related work in WSN for each of these is also presented

Sensor context information for energy-efficient optimization of wireless procedures

The wide deployment of Wireless Local Area Networks (WLAN) we are witnessing today increases connectivity opportunities for mobile terminal devices, such as smartphones. However, continuous scanning for WLAN points of attachment can be a power exhausting mechanism for such battery-powered devices. These mobile devices, besides being equipped with different wireless access interfaces, are also coupled with sensors such as accelerometer, GPS, luminance and magnetic compass. In fact, sensors are increasingly being coupled into different devices and environments and are able to convey sensing information through networks into decision entities able to optimize different processes. In this paper we propose a framework where media independent sensing information is used to enhance wireless link management towards energy-efficiency. This framework enables the dissemination of sensing information towards local and remote decision entities, enhancing other processes (e.g. mobility) with sensing information in order to provide true Ambient Intelligence scenarios. We introduce this framework into a wireless management scenario able to provide energy-efficient optimal network connectivity

An Energy-conscious Transport Protocol for Multi-hop Wireless Networks

We present a transport protocol whose goal is to reduce power consumption without compromising delivery requirements of applications. To meet its goal of energy efficiency, our transport protocol (1) contains mechanisms to balance end-to-end vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgements and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within a recently developed ultra low-power multi-hop wireless network system, extensive simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network.Defense Advanced Research Projects Agency (NBCHC050053

A Physical Estimation based Continuous Monitoring Scheme for Wireless Sensor Networks

Data estimation is emerging as a powerful strategy for energy conservation in sensor networks. In this thesis is reported a technique, called Data Estimation using Physical Method (DEPM), that efficiently conserves battery power in an environment that may take a variety of complex manifestations in real situations. The methodology can be ported easily with minor changes to address a multitude of tasks by altering the parameters of the algorithm and ported on any platform. The technique aims at conserving energy in the limited energy supply source that runs a sensor network by enabling a large number of sensors to go to sleep and having a minimal set of active sensors that may gather data and communicate the same to a base station. DEPM rests on solving a set of linear inhomogeneous algebraic equations which are set up using well-established physical laws. The present technique is powerful enough to yield data estimation at an arbitrary number of point-locations, and provides for easy experimental verification of the estimated data by using only a few extra sensors

VGDRA: A Virtual Grid-Based Dynamic Routes Adjustment Scheme for Mobile Sink-Based Wireless Sensor Networks

In wireless sensor networks, exploiting the sink mobility has been considered as a good strategy to balance the nodes energy dissipation. Despite its numerous advantages, the data dissemination to the mobile sink is a challenging task for the resource constrained sensor nodes due to the dynamic network topology caused by the sink mobility. For efficient data delivery, nodes need to reconstruct their routes toward the latest location of the mobile sink, which undermines the energy conservation goal. In this paper, we present a virtual gridbased dynamic routes adjustment (VGDRA) scheme that aims to minimize the routes reconstruction cost of the sensor nodes while maintaining nearly optimal routes to the latest location of the mobile sink. We propose a set of communication rules that governs the routes reconstruction process thereby requiring only a limited number of nodes to readjust their data delivery routes toward the mobile sink. Simulation results demonstrate reduced routes reconstruction cost and improved network lifetime of the VGDRA scheme when compared with existing work

Parallel Load Sharing Technique Used To Increase the Life Time of Wireless Sensor Network

Wireless Sensor Networks are low power networks which have many small nodes. In wireless sensor network inherent limited energy resource is the major drawback. To maximize the lifetime of the sensor node it is preferable to distribute the energy dissipated throughout the wireless sensor network in order to minimize maintenance and maximize overall system performance. In this paper we introduce parallel load sharing technique to increase the life time of all the nodes in a way to get maximum efficiency from the network. DOI: 10.17762/ijritcc2321-8169.15032