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In wireless sensor network studies the main objective is minimizing the energy consumption so that the lifetime is maximized under the limited battery capacity constraints. In most event-driven surveillance applications, the end-to-end delay should also be minimized. In this paper we present a new EDO-MAC (energy and delay optimization Media Access Control) which reaches a good balance between energy...
In order to result the problem of low-power routing for wireless sensor networks, a data aggregation routing protocol with minimum transmission cost spanning tree was proposed, Data from sensor nodes was transmitted to the root node to sink node within the same sensor area. Data aggregation and transmission to the in-network sink along the shortest path is in accordance with principles of least energy...
The border coverage of forest fire in a three dimensional space is rigorously analyzed and the minimum number of the sensor nodes of WSN and their placement for complete coverage is determined. Also, given a random distribution of the sensor nodes, the approach of selecting a minimum subset of the sensor nodes for complete coverage in the forest fire monitoring system is addressed. A computationally...
Intelligent environments employ electronics unobtrusively integrated with the ambient to predict and to respond to the needs of people, enhancing many aspects of the everyday life. Wireless sensor network (WSN) are at the center of ambient intelligence applications. They consists of thousands of distributed sensing devices, that continually collect and transmit information about the surrounding environment...
Wireless sensor networks are an important research area that has attracted a lot of attention in the past few years. Most of this attention, however, has focused on wireless sensor network collect scalar data such as temperature and vibration. Scalar data is insufficient for many applications such as video surveillance and traffic monitoring. Whereas, camera sensors collect video data, which are rich...
Wireless sensor networks consist of various sensor nodes which operate in a memory, energy and bandwidth constrained environment. Target tracking is an important application in wireless sensor networks and in this paper we propose an energy aware target tracking (EATT) algorithm. Energy efficiency is obtained due to the novel concept of tracking being performed in a collaborative manner by different...
In directed diffusion (DD) routing protocol, the establishment of routing depends on the plane flooding of interest, which costs too much time and energy and could not be applied to large-scale network. In order to solve these problems, directed diffusion based on clustering and inquiry (DDBCI) is proposed in this paper. DDBCI clusters all nodes into clusters, and each cluster head keeps a member...
This paper analyzes the energy consuming characteristics of data acquisition in wireless sensor network node. The impaction of node's data acquisition subsystem design is addressed. Schemes to improve energy saving of data acquisition are presented with precondition of guaranteeing performance, which includes choosing and setting working parameters of sensors, setting working parameters of the DC/DC...
The conventional matrix inversion method for weighted geometric dilution of precision (WGDOP) calculation has a large amount of operation. This paper employs an artificial neural network approach, namely, the resilient back-propagation (Rprop) method to implement WGDOP. We also present two novel architectures to implement the Rprop-based WGDOP. Simulation results show that the proposed architectures...
A major concern in wireless sensor networks is to maximize network lifetime while maintaining a high quality of services (QOS) such as target coverage and network connectivity. Communication and sensing consume energy, therefore efficient power management can extend network lifetime. in this paper we consider a large number of static sensor nodes are deployed in order to monitor a number of target...
Wireless Sensor Network (WSN) nodes are powered by limited battery and communication consumes most of the energy. Therefore, it's not appropriate to transmit data directly in the networks while compressing data before sending is an effective method to save energy for nodes. According to the need for fully recovering the compressed numerical data, based on the LZW (Lempel-Ziv-Welch) algorithm, this...
The different algorithm of data classification and clustering to identify the subject on the room is introduced. The aim is to provide a learning approach for pattern classification of presence sensors data. The focus system is on its application to find the best method for identification the subject location using a specific category of data simulated. The main features of the system include: automatic...
The problem of localizing an uncooperative target using binary observations and without the knowledge of the propagation model is considered. Three new estimators for the location of the target are utilized. Their performance, in the MSE sense, is studied analytically and through simulations. Results show that these estimators significantly outperform the existing approach.
Principal component analysis is a powerful technique for data analysis and compression, with a wide range of potential applications in wireless sensor networks. However, its centralized implementation, with a fusion center collecting all the samples, is inefficient in terms of energy consumption, scalability, and fault tolerance. Previous distributed approaches reduce the communication cost, but not...
This paper is concerned with the decentralized estimation of a Gaussian source using multiple sensors. We consider a diversity scheme where only the sensor with the best channel sends their measurements to a fusion center, using the analog amplify and forwarding technique. A distributed version of the diversity scheme where sensors decide what to transmit based only on their local information is also...
Based on the concept of hybrid shift-invariant spaces, we develop a distributed protocol for the reconstruction of time-varying physical fields in wireless sensor networks. The localized nature of these spaces allows for a clustered network architecture that leads to low communication overhead. Capitalizing on the sparsity of the reconstruction matrix, we propose an iterative reconstruction algorithm...
The statistical properties of the capacity of narrowband double Hoyt fading channels are studied. Toward this end, analytical expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the instantaneous channel capacity process are derived. Furthermore, for the characterization of the dynamical behavior of the time-varying channel capacity, expressions are...
A distributed transmit beamforming technique is developed for both a static and a time-varying channel in a wireless sensor network. This algorithm is based on an iterative procedure that synchronizes the transmitters to send a common message signal coherently to the receiver, using a 3-bit feedback in each timeslot. Results show that the received power increases quadratically with number of transmitters,...
This paper discusses an energy constrained distributed estimation in wireless sensor network (WSN) based on frequency and time division multiple access (FTDMA). In a measurement with WSN, sensors transmit observed quantized data to a fusion center (FC) via radio communication channels, to obtain a final estimate. Such systems require a multiple access technique such as time division multiple access,...
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