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.
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%.
18971548
Coverage-preserving Data Gathering in Wireless Sensor Networks
The power is the most significant resource in wireless sensor nodes, so energy conservation is the most important factor in designing the protocol for sensor networks. In this paper, we study the problem of energy-efficient collection of the physical information from the target area. The coverage-preserving data gathering (CPDG) problem is to build up a tree, which minimizes the total energy consumption, and preserves the original coverage to ensure the result correctness. This problem can be formalized as 0-1 integer linear programming, and solved by an efficient heuristic algorithm. Furthermore, an improved algorithm is also proposed to balance the energy consumption among all the sensor nodes. The experimental results show that CPDG algorithm can conserve the energy about 30% of PEDAP protocol, which is regarded as one of the most efficient data gathering protocols as we know.
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.
14073504
A multinomial logistic regression modeling approach for anomaly intrusion detection
Although researchers have long studied using statistical modeling techniques to detect anomaly intrusion and profile user behavior, the feasibility of applying multinomial logistic regression modeling to predict multi-attack types has not been addressed, and the risk factors associated with individual major attacks remain unclear. To address the gaps, this study used the KDD-cup 1999 data and bootstrap simulation method to fit 3000 multinomial logistic regression models with the most frequent attack types (probe, DoS, U2R, and R2L) as an unordered independent variable, and identified 13 risk factors that are statistically significantly associated with these attacks. These risk factors were then used to construct a final multinomial model that had an ROC area of 0.99 for detecting abnormal events. Compared with the top KDD-cup 1999 winning results that were based on a rule-based decision tree algorithm, the multinomial logistic model-based classification results had similar sensitivity values in detecting normal (98.3% vs. 99.5%), probe (85.6% vs. 83.3%), and DoS (97.2% vs. 97.1%); remarkably high sensitivity in U2R (25.9% vs. 13.2%) and R2L (11.2% vs. 8.4%); and a significantly lower overall misclassification rate (18.9% vs. 35.7%). The study emphasizes that the multinomial logistic regression modeling technique with the 13 risk factors provides a robust approach to detect anomaly intrusion.
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.
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.
6287453
A dynamic assignment problem in a mobile system with limited bandwidth
The assignment problem originally arising from parallel and distributed computing has been investigated intensively since the 70's when Harold Stone proposed a method to solve it with the aid of network flow algorithms. In this paper, we discuss this problem under a mobile environment with limited capacity of wireless links. The assignment problem is to schedule a group of related objects from a resource-constrained mobile device to its powerful proxy machine so that program activity migrates among processors as execution proceeds, and hence the overall performance will improve. First, we reduce this optimization problem to the 0/1 knapsack problem, and therefore show that it is NP-hard. Second, two heuristic algorithms are proposed. One is an adaptive heuristic algorithm with complexity O(NE), here, N and E represent the number of nodes and edges in the object graph abstracted from the mobile application. The other is a non-adaptive heuristic algorithm with complexity O(E), i.e, N times faster than the adaptive counterpart. Finally, we provide a simple distributed algorithm based on Raymond's tree-based distributed mutual exclusion algorithm for solving this problem with message complexity O(N/sup 2/ log N).
15938722
An Implicit Finite Difference Scheme with Preconditioning for Convection Dominated Diffusion Equation
An implicit finite difference scheme for solving time-dependent convection dominated diffusion equations in two space variables is presented. A one-sided difference approximation is used for the convection terms and a second-order central difference approximationfor the diffusion term. The implicit scheme is consistent,unconditionally stable and its $L^2$ error estimation is optimal. By preconditioning technique of incremental unknowns, the implicit scheme is an efficient one.