This paper proposes a biometric-based user authentication protocol for wireless sensor networks (WSN) when a user wants to access data from sensor nodes, since WSN are often deployed in an unattended environment. Th...
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This paper proposes a biometric-based user authentication protocol for wireless sensor networks (WSN) when a user wants to access data from sensor nodes, since WSN are often deployed in an unattended environment. The protocol employs biometric keys and resists the threats of stolen verifier, of which many are logged-in users with the same login identity, guessing, replay, and impersonation. The protocol uses only Hash function and saves the computational cost, the communication cost, and the energy cost. In addition, the user's password can be changed freely using the proposed protocol.
The upper bounds on lifetime of three dimensional extended Time hopping impulse radio Ultrawide band (TH-IR UWB) sensor networks are derived using percolation theory arguments. The TH-IR UWB sensor network consists of...
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The upper bounds on lifetime of three dimensional extended Time hopping impulse radio Ultrawide band (TH-IR UWB) sensor networks are derived using percolation theory arguments. The TH-IR UWB sensor network consists of n sensor nodes distributed in a cube of edge length n1/3 according to a Poisson point process of unit intensity. It is shown that for such a static three dimensional extended TH-IR UWB sensor network, the upper bound on the lifetime is of order O(n-1), while in the ideal case, the upper bound on the lifetime is longer than that of a static network by a factor of n 2/3. Therefore sensor nodes moving randomly in the deployment area can improve the upper bound on network lifetime. The results also reveal that the upper bounds on network lifetime decrease with the number of nodes n, thus extended THIR UWB sensor networks aren't prone to be employed in large-scale network.
A critical function of wireless sensor networks (WSNs) is data gathering. While, one is often only interested in collecting a relevant function of the sensor measurements at a sink node, rather than downloading all th...
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ISBN:
(纸本)9781424499199
A critical function of wireless sensor networks (WSNs) is data gathering. While, one is often only interested in collecting a relevant function of the sensor measurements at a sink node, rather than downloading all the data from all the sensors. This paper studies the capacity of computing and transporting the specific functions of sensor measurements to the sink node, called aggregation capacity, for WSNs. It focuses on random WSNs that can be classified into two types: random extended WSN and random dense WSN. All existing results about aggregation capacity are studied for dense WSNs, including random cases and arbitrary cases, under the protocol model (ProM) or physical model (PhyM). In this paper, we propose the first aggregation capacity scaling laws for random extended WSNs. We point out that unlike random dense WSNs, for random extended WSNs, the assumption made in ProM and PhyM that each successful transmission can sustain a constant rate is over-optimistic and unpractical due to transmit power *** derive the first result on aggregation capacity for random extended WSNs under the generalized physical model. Particularly, we prove that, for the type-sensitive perfectly compressible functions and type-threshold perfectly compressible functions, the aggregation capacities for random extended WSNs with n nodes are of order Θ ((log n) -β/2-1 ) and Θ (((log n) -β/2 )/(log log n)), respectively, where β >; 2 denotes the power attenuation exponent in the generalized physical model.
Passive sensor networks can achieve accurate detection of target under complex environment. In order to adapt to different communication demands of sensor networks in different environments, this paper designed and im...
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This essay introduces the concepts of knowledge granularity and information system. On this basis, we propose two new more general knowledge granularities: the combination granularity and polynomial granularity, which...
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Reducing noise disturbances in the frequency segment of high frequency (HF) ground wave radar and restraining the sidelobes of strong targets that interfere with the detection of weak targets are the interesting Topic...
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ISBN:
(纸本)9789955690184
Reducing noise disturbances in the frequency segment of high frequency (HF) ground wave radar and restraining the sidelobes of strong targets that interfere with the detection of weak targets are the interesting Topic. A new method based on an adaptive techniques that solves these problems is proposed. By changing the working time of the frequency spectrum monitor (FSM), we have shown not only that radar can run in the frequency segments with lower noise disturbances, but also that the noise data produced by FSM can be exploited effectively. There is no correlation between the noise and the useful echo signal, though the correlation between noises over very short time periods is strong,. Exploiting the phenomena, we can adjust system parameters in real-time by adaptive methods to solve the two problems,namely sidelobe disturbance of strong targets and noise distrubance in the frequency segment.
This paper proposes a new method for finding principal curves from complex distribution dataset. Motivated by solving the problem, which is that existing methods did not perform well on finding principal curve in comp...
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ISBN:
(数字)9783642162480
ISBN:
(纸本)9783642162473
This paper proposes a new method for finding principal curves from complex distribution dataset. Motivated by solving the problem, which is that existing methods did not perform well on finding principal curve in complex distribution dataset with high curvature, high dispersion and self-intersecting, such as spiral-shaped curves, Firstly, rudimentary principal graph of data set is created based on the thinning algorithm, and then the contiguous vertices are merged. Finally the fitting-and-smoothing step introduced by Kegl is improved to optimize the principal graph, and Kegl's restructuring step is used to rectify imperfections of principal graph. Experimental results indicate the effectiveness of the proposed method on finding principal curves in complex distribution dataset.
Indentification of informative gene subsets responsible for discerning between available samples of gene expression data is an important task in bioinformatics. Reducts, from rough sets theory, corresponding to a mini...
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The essence characteristics of software trustworthiness are software execution effect and behavior can be anticipated, which is an important index of software quality. Under the open and dynamic environments, some unc...
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service-oriented computing is a new software development paradigm that allows application developers to select available services from the Internet and to form new web services. A main problem is how to efficiently de...
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