Power Conservation In Wireless Sensor Networks
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Power Conservation In Wireless Sensor Networks
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Author : Peng Cheng
language : en
Publisher:
Release Date : 2004
Power Conservation In Wireless Sensor Networks written by Peng Cheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Energy Conservation In Wireless Sensor Network Wsn
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Author : Om Verma
language : en
Publisher:
Release Date : 2013-09-20
Energy Conservation In Wireless Sensor Network Wsn written by Om Verma and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-20 with categories.
Summe Le Roijs Of Des Conines Summe
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Author :
language : en
Publisher:
Release Date : 1484
Summe Le Roijs Of Des Conines Summe written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1484 with categories.
Energy Conservation Methods For Use In Wireless Sensor Network Communications
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Author : Sofiane Moad
language : en
Publisher:
Release Date : 2011
Energy Conservation Methods For Use In Wireless Sensor Network Communications written by Sofiane Moad and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Wireless Sensor Networks (WSNs) are composed of tiny sensor nodes, which are cable of sensing and processing data from inaccessible environments and communicating them to the end-user for further analysis. WSNs are characterized by the limited capacity of sensor node batteries, which makes energy-efficiency a critical issue. Once a WSN is deployed, sensor nodes must self-organize and live as long as possible, based only on their initial amount of energy. Consequently, techniques minimizing energy consumption are required to improve network lifetime. In such a way, this thesis deals with the development of various energy-saving mechanisms. Our research revolves around three main areas: 1) in-network processing, 2) clustering, and 3) radio diversity. Concerning in-network processing, we proposed a Smart AGgregation technique (SAG) that controls energy consumption, while adjusting user error. On the same subject, we integrate a compression mechanism within a cluster-based architecture to develop a Compression Cluster-based scheme in a Spatial Correlated Region protocol (CC\_SCR), to further decrease energy consumption. Moving on to clustering, our research leds to the development of an ADaptive Energy-Efficient Clustering protocol (ADEEC), resulting in better network organization and decreased in energy consumption. In the field of diversity direction, we explored how to minimize energy consumption when using multiple radios for routing in WSNs. We first proposed a novel metric that uses a minimum-energy radio when routing, then we proposed another metric that allows energy balancing inside a network in order to extend its lifetime, and finally we proposed a delay-sensitive metric that adapts routing packets with different priorities. The validation of our contributions were carried out with deep analytical analysis and simulation using TOSSIM.
Power Conservation In Wireless Sensor Network Using Receiver Switch Off
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Author :
language : en
Publisher:
Release Date : 2003
Power Conservation In Wireless Sensor Network Using Receiver Switch Off written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
A wireless sensor network is a network of nodes equipped with sensors and capable of relaying their data to the monitoring station using multi-hop communication. Essentially, they operate using the ad hoc paradigm due to the unpredictable and dynamic topology. The lifetime of the nodes is limited to that of its battery. Thus in this work we try to conserve the battery by putting the nodes to sleep when they are not involved in any communication process. Sensor nodes produce readings every fixed time interval and we try to leverage the predictability of the packet inter-arrival time to obtain the sleep periods. We model the inter-arrival times that a node observes in the form of a probability distribution function. A node may be forwarding packets from multiple sources and it associate this knowledge to every stream it is carrying. After a node captures a packet, using its knowledge it can predict the approximate arrival time of the next packet. It can try to sleep during this period. It thus conserves power. In our study we show that simply forwarding the packet when they are received causes the predictability needed for this approach to be lost. We then propose an alternative approach, which is to maintain some local periodicity. This can be accomplished by delaying the packets. The multi-hop nature of the network causes these delays to accumulate and thus we have to consider the tolerances of the data packets to these delays. We then discuss the relation between the sleep durations possible and the delay tolerances of the packets. Finally, we explore the inter-dependence between packet loss, sleep duration, delay and the ultimate effect on the power savings.
Energy Efficient Wireless Sensor Networks
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Author : Vidushi Sharma
language : en
Publisher: CRC Press
Release Date : 2017-07-28
Energy Efficient Wireless Sensor Networks written by Vidushi Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-28 with Computers categories.
The advances in low-power electronic devices integrated with wireless communication capabilities are one of recent areas of research in the field of Wireless Sensor Networks (WSNs). One of the major challenges in WSNs is uniform and least energy dissipation while increasing the lifetime of the network. This is the first book that introduces the energy efficient wireless sensor network techniques and protocols. The text covers the theoretical as well as the practical requirements to conduct and trigger new experiments and project ideas. The advanced techniques will help in industrial problem solving for energy-hungry wireless sensor network applications.
Mechanisms For Energy Conservation In Wireless Sensor Networks
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Author : Daniela Tulone (t.d.-)
language : en
Publisher:
Release Date : 2006
Mechanisms For Energy Conservation In Wireless Sensor Networks written by Daniela Tulone (t.d.-) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Energy Conservation In Wireless Sensor Networks And Related Problems Of Graph Theory
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Author : Li Liu
language : en
Publisher:
Release Date : 2008
Energy Conservation In Wireless Sensor Networks And Related Problems Of Graph Theory written by Li Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
This thesis is divided into two major parts according to the research fields : the energy conservation problems in wireless sensor networks and the scheduling problems in grid computing systems. Chapter 1 introduces the emergence of wireless sensor networks and its characteristics according to which the new problems of wireless sensor networks arise compared with the traditional network and wireless networks. Chapter 2-4 present the problem of energy conservation with coverage. We address an application which monitors a set of targets with coverage. We address an application which monitors a set of targets with known locations by a set of sensor nodes in heterogeneous wireless sensor networks. For further studies, we consider this problem under some specific conditions. We consider the wireless sensor networks satisfying that each node monitors one target or just for connection. Furthermore, we continue this work and defines the working time of a node is exactly d times. In chapter 5, present the efficient data routing problem for mobile tracking wireless sensor networks. Another issue we study in this thesis is about scheduling problems in grid computing systems. In chapter 6, we introduce a new approach that is with respect to job parallelism for computational grid. Chapter 7, tries to give a new grid system model to guarantee the quality of a schedule. This chapter is supposed to solve the problem of how to allocate the resources optimally and adaptively in the dynamic, scalable and distribute-controlled grid environment.
On The Use Of Data Inference For Energy Conservation In Wireless Sensor Networks Microform
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Author : Gregory Hartl
language : en
Publisher: Library and Archives Canada = Bibliothèque et Archives Canada
Release Date : 2004
On The Use Of Data Inference For Energy Conservation In Wireless Sensor Networks Microform written by Gregory Hartl and has been published by Library and Archives Canada = Bibliothèque et Archives Canada this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
In this thesis, we propose two approaches to using data inference techniques to conserve energy in wireless sensor networks. First, we propose a novel approach for efficiently sensing a remote field by trading off reduced energy usage for reduced accuracy of the data recorded. Our approach, the infer algorithm, puts nodes into sleep mode for a given period of time and uses Bayesian inference to infer the missing data from the nodes in sleep mode. Simulations show that on average our algorithm produces energy savings of 59% while producing results that are accurate to within 7.9%. Second, we solve the problem of inferring per node loss rates using passive end-to-end measurements. We formulate the problem as a Maximum-Likelihood Estimation (MLE) problem and show how it can be efficiently solved using the Expectation-Maximization (EM) algorithm. Finally, we validate our analysis through simulations.
Energy Conservation For Collaborative Applications In Wireless Sensor Networks
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Author : Oualid Demigha
language : en
Publisher:
Release Date : 2015
Energy Conservation For Collaborative Applications In Wireless Sensor Networks written by Oualid Demigha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Wireless Sensor Networks is an emerging technology enabled by the recent advances in Micro-Electro-Mechanical Systems, that led to design tiny wireless sensor nodes characterized by small capacities of sensing, data processing and communication. To accomplish complex tasks such as target tracking, data collection and zone surveillance, these nodes need to collaborate between each others to overcome the lack of battery capacity. Since the development of the batteries hardware is very slow, the optimization effort should be inevitably focused on the software layers of the protocol stack of the nodes and their operating systems. In this thesis, we investigated the energy problem in the context of collaborative applications and proposed an approach based on node selection using predictions and data correlations, to meet the application requirements in terms of energy-efficiency and quality of data. First, we surveyed almost all the recent approaches proposed in the literature that treat the problem of energy-efficiency of prediction-based target tracking schemes, in order to extract the relevant recommendations. Next, we proposed a dynamic clustering protocol based on an enhanced version of the Distributed Kalman Filter used as a prediction algorithm, to design an energy-efficient target tracking scheme. Our proposed scheme use these predictions to anticipate the actions of the nodes and their roles to minimize their number in the tasks. Based on our findings issued from the simulation data, we generalized our approach to any data collection scheme that uses a geographic-based clustering algorithm. We formulated the problem of energy minimization under data precision constraints using a binary integer linear program to find its exact solution in the general context. We validated the model and proved some of its fundamental properties. Finally and given the complexity of the problem, we proposed and evaluated a heuristic solution consisting of a correlation-based adaptive clustering algorithm for data collection. We showed that, by relaxing some constraints of the problem, our heuristic solution achieves an acceptable level of energy-efficiency while preserving the quality of data.