206606945
Self-organization Data Gathering for Wireless Sensor Networks
Sensor networks have attracted much attention in the recent years for its wide applications in biology, medicine, security and battlefield, etc. Data gathering is one of the most important operations in wireless sensor networks. In this paper, we present an energy-delay efficient data gathering protocol, SODG, for sensor networks while taking the transmission interference into considerations. The significance of this proposal is that it is fully localized and distributed, and only depends on the one-hop neighbors’ information. To minimize the delay, the parallel transmissions are permitted with interference- free guaranteed. The experimental simulations show that our protocol is energy- delay efficient. Especially, SODG protocol improves about 64% over PEGASIS on energy consumption, and about 80% over chain-based protocols on delay.
19569321
An Efficient Data Exchange Protocol Using Improved Star Trees in Wireless Sensor Networks
In wireless sensor networks, it is necessary and important to send information to all nodes. In some situation, every node has its own data to send to all the other nodes. The communication patterns are all-to-all broadcasting, which is called data exchange problem. In this paper, we present an efficient data exchange protocol using improved star trees. We divide the sensor area into four equal grids and each sensor node associates itself with a virtual grid based on its location information. These grids can be divided again if necessary. In each grid, we calculate the position of root node with location information of sensor nodes. Then, an efficient data exchange Star-Tree was constructed and used to achieve the exchange behavior in the grid. The fused data of each grid was sent to the center node. Simulations show that our protocol can prolong the lifetime about 69% to the multiple-chain protocols, and the delay can be reduced at least 35%.
12687767
Comments on "Estimation of frequencies and damping factors by two-dimensional ESPRIT type methods"
For original paper, see Rouquette and Najim (IEEE Trans. Signal Process., vol.49, no.1, p.237-45, 2001).The original authors present two high-resolution approaches to estimate two-dimensional (2-D) signal parameters. The first approach decomposes the 2-D estimation problem into two one-dimensional (1-D) ones, estimates the 1-D frequencies with the MEMP method, and then forms correct pairs using a new pairing scheme introduced in Vanpoucke et al. (1994). The second method (the 2-D ESPRIT method) directly estimates the 2-D frequencies. It is shown that both methods are more accurate than the related methods. The present authors note that the original paper appears to have a key error in the permutation matrix specification of the first method. In this comment, they derive the correct one with the performance simulations.
9587091
Topology control for delay-constraint data collection in wireless sensor networks
Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.
5825556
Coverage and Exposure Paths in Wireless Sensor Networks
Wireless sensor networks have posed a number of challenging problems such as localization, deployment and tracking, etc. One of the interesting problems is the calculation of the coverage and exposure paths for the sensor networks. This paper presents a fully localized algorithm to solve the worst coverage problem first introduced by Meguerdichian et al. The nodes of the sensor network cooperate to construct the worst coverage path only by the one-hop neighbor’s information, thus avoiding the massive communication and conserving the energy. The correctness of the proposed algorithm is proved formally under the sensing diminishing model. Moreover, this algorithm can be easily extended to solve the minimal exposure problem with local information as well.
11462203
Wireless fire monitoring system for ancient buildings
With the development of micro-processor and wireless communication, wireless sensor networks have becomes reality in some applications. In this paper, we mainly introduce the development of the fire monitoring system for ancient buildings based on wireless sensor networks. To satisfy the requirements of the application, lifetime and latency, etc, we design some key technologies in the different layers of the sensor nodes, such as data link layer, network layer and application layer. Finally, we realize the system based on MicaZ node and MTS300CB sensor broad, made by XBow Co.
45169888
Multi-teraflops spin dynamics studies of the magnetic structure of FeMn/Co interfaces
6062507
On Data Fusion and Lifetime Constraints in Wireless Sensor Networks
The problems of energy efficient sensor network configuration and local fusion of sensed data have been addressed separately in the previous works. In this paper, we propose to analyze the sensing accuracy with the consideration of the node distribution and fusion overhead in terms of the energy consumption. By extending existing sensing model in the literature, we quantify how the sensing ranges and node densities of sensor nodes impact the sensing accuracy, and how it affects the fusion overhead and the sensing lifetime of the network. We identify the tradeoff between sensing accuracy and energy consumption in an analytical framework. It can be used to choose optimal parameters of sensor networks to meet the specified sensing or lifetime requirements.
13971731
Video segmentation based on graphical models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notions of distance transformation and Markov random field are used to express spatiotemporal constraints. Given consecutive frames, an optimization method is proposed to maximize the conditional probability density of the three fields in an iterative way. Experimental results show that the approach is robust and generates spatiotemporally coherent segmentation results.
18413233
Range-Free Localization Using Expected Hop Progress in Wireless Sensor Networks
Localization algorithm continues to be an important and challenging topic in today's wireless sensor networks (WSNs). In this paper, a novel range-free localization algorithm using expected hop progress (LAEP) to predict the location of any sensor in a WSN is proposed. This algorithm is based on an accurate analysis of hop progress in a WSN with randomly deployed sensors and arbitrary node density. By deriving the expected hop progress from a network model for WSNs in terms of network parameters, the distance between any pair of sensors can be accurately computed. Since the distance estimation is a key issue in localization systems for WSNs, the proposed range-free LAEP achieves better performance and less communication overhead as compared to some existent schemes like DV-Hop and RAW. In addition, we study the effect of anchor placement on the algorithm performance by deriving the corresponding mean position error range. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis.
43411240
Semi-Supervised Graph-Ranking for Text Retrieval
Much work has been done on supervised ranking for information retrieval, where the goal is to rank all searched documents in a known repository with many labeled query-document pairs. Unfortunately, the labeled pairs are lack because human labeling is often expensive, difficult and time consuming. To address this issue, we employ graph to represent pairwise relationships among the labeled and unlabeled documents, in order that the ranking score can be propagated to their neighbors. Our main contribution in this paper is to propose a semi-supervised ranking method based on graph-ranking and different weighting schemas. Experimental results show that our method called SSG-Rank on 20-newsgroups dataset outperforms supervised ranking (Ranking SVM and PRank) and unsupervised graph ranking significantly.