processing streams of data in an overlay network of operators distributed over a wide-area network is a common idea shared by different applications such as distributed event correlation systems and large-scale sensor...
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processing streams of data in an overlay network of operators distributed over a wide-area network is a common idea shared by different applications such as distributed event correlation systems and large-scale sensor networks. In order to utilize network resources efficiently and allow for the parallel deployment of a large number of large-scale operator networks, suitable placement algorithms are vital that place operators on physical nodes. In this paper, we present a distributed placement algorithm that minimizes the bandwidth-delay product of data streams between operators of the network in order to reduce the induced network load. Since the fundamental optimization problem is NP-hard, we propose a heuristic solution. First, we calculate an optimal solution in an intermediate continuous search space, called latency space. Subsequently the continuous solution is mapped to the physical network. Our evaluations show that this algorithm reduces the resulting network load significantly compared to state of the art algorithms and achieves results close to the optimum.
In this paper, a new particle filter (PF) which we refer to as the decentralized PF (DPF) is proposed. By first decomposing the state into two parts, the DPF splits the filtering problem into two nested sub-problems a...
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ISBN:
(纸本)9781424477456
In this paper, a new particle filter (PF) which we refer to as the decentralized PF (DPF) is proposed. By first decomposing the state into two parts, the DPF splits the filtering problem into two nested sub-problems and then handles the two nested sub-problems using PFs. The DPF has an advantage over the regular PF that the DPF can increase the level of parallelism of the PF. In particular, part of the resampling in the DPF bears a parallel structure and thus can be implemented in parallel. The parallel structure of the DPF is created by decomposing the state space, differing from the parallel structure of the distributed PFs which is created by dividing the sample space. This difference results in a couple of unique features of the DPF in contrast with the existing distributed PFs. Simulation results from a numerical example indicates that the DPF has a potential to achieve the same level of performance as the regular PF, in a shorter execution time.
We improve prior efforts to extract coherent image contents (objects) from complex scenes by exploiting structural and semantic coherency. Generative models like latent Dirichlet allocation (LDA) and its variants are ...
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We improve prior efforts to extract coherent image contents (objects) from complex scenes by exploiting structural and semantic coherency. Generative models like latent Dirichlet allocation (LDA) and its variants are popular methods for unsupervised object segmentation, but they lack comprehensive consideration of structure correlations. Even small amounts of globally distributed noise in the image can negatively effect results. In this paper, we introduce a structure preserving semantic coherent model (SP-SC) to support more comprehensive object segmentation. Our approach combines Euclidean distance, graph distances and structural similarity of homogeneous patches in a unified framework. The method groups structural and semantic coherent patches together thereby overcoming false segmentation due to many kinds of noise and scene complexities. Comparative results in segmentation experiments using standard image data sets show the efficacy of proposed approach.
Multi-core architectures have become mainstream. Trends suggest that the number of cores integrated on a single chip will increase continuously. However, lock contention in operating systems can limit the parallel sca...
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Multi-core architectures have become mainstream. Trends suggest that the number of cores integrated on a single chip will increase continuously. However, lock contention in operating systems can limit the parallel scalability on multi-cores so significantly that the speedup decreases with the increasing number of cores (thrashing). Although the phenomenon can be easily reproduced experimentally, most existing lock models are not able to do so. To overcome this challenge, this paper develops a discrete event simulation model which has the capability of capturing both the sequential execution in critical sections and the contention for shared hardware resources. The model is evaluated using a series of typical parameter configurations which can represent different degrees of lock contention. Experimental results suggest that the thrashing phenomenon can be observed when the model parameters are selected properly. To further understand this phenomenon, statistics such as the percentage of time spent waiting for locks and the number of cores waiting for a lock are exploited to characterize the lock thrashing. In addition, the model sensitivity to changes in memory latency and hardware architectures are also examined. Finally, we use this model to compare three methods which are proposed for preventing the lock thrashing.
Identifying an organic object like a flower against the background picture is known to be challenging. Several methods have been proposed so that unique characteristics of flowers can be extracted with increased accur...
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Identifying an organic object like a flower against the background picture is known to be challenging. Several methods have been proposed so that unique characteristics of flowers can be extracted with increased accuracy. Establishing this process as a mobile flower identification service for the public requires major adaptation of the system due to numerous picture requests being received simultaneously. This paper presents a framework for grid-based mobile flower recognition that employs 1) grid computing technology for further optimization of multiple concurrent imageprocessing and 2) mobile wireless communication as the primary data transfer for accessing this mobile service. Globus Toolkit is applied as the middleware in the distributed computing environment whereby Short Message Services (SMS) and Multimedia Messaging Services (MMS) technology are used for picture and result delivery.
We reconstruct a spatially distributed three-dimensional (3D) wave field from a number of intensity observations, obtained in different sensor planes, parallel to the object plane. The proposed algorithm can be treate...
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We reconstruct a spatially distributed three-dimensional (3D) wave field from a number of intensity observations, obtained in different sensor planes, parallel to the object plane. The proposed algorithm can be treated as a multiple plane iterative Gerchberg-Saxton algorithm [1]. It is obtained from the best linear estimate of the complex-valued object distribution derived for the complex-valued observations. This estimator is modified for the intensity measurements in the sensor planes. The algorithm is studied by numerical experiments performed for amplitude and phase object distributions. It is shown that the proposed method allows reconstructing the whole 3D wave fields for different setup parameters. This technique can be applied for 3D imaging. The comparison versus the successive iterative method [2] shows an accuracy advantage of the proposed algorithm provided that the type of modulation in the object plane is known.
With the development of 3G network technology, the rapid upgrading of mobile phone hardware, and the refined requirements for mobile phones by mobile phone users, it is essential for mobile phones to be able to prompt...
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With the development of 3G network technology, the rapid upgrading of mobile phone hardware, and the refined requirements for mobile phones by mobile phone users, it is essential for mobile phones to be able to promptly and accurately process images. A mobile phone terminal sends the service requests to cloud computer system which then processes the requests and sends the results via 3G network back to the mobile phone terminal. This paper presents a architectural model to realize the imageprocessing system that connects mobile phone with clouding computing through 3G network. The method is to build intra-enterprise server group, distributed database system, and parallel computing system to form a private cloud computing system, which defines ontological semantic tags for images uploaded from mobile phone terminals and stores them in a distributed way (cloud storing), and to design the corresponding search algorithms to help the system to promptly and accurately query the images (cloud computing), and retrieve the appropriate images through sorting matching indexes, weights, and etc.
Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently ...
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ISBN:
(纸本)9781424442959;9781424442966
Imaging of cardiac perfusion with MR is a challenging area of research especially due to the motion of the heart and limited time of data acquisition. Compressed sensing is a popular signal estimation method recently adopted by researchers in MRI which can improve the spatial and/or temporal resolution of the acquired images by reducing the number of necessary samples for image reconstruction. This paper focuses on performance of temporal regularization with total variation and wavelets in compressed sensing. The impact of the choice of regularization parameters on the image quality and the temporal variation of intensity in region of interests (ROIs) are discussed. It is found that selecting the regularization parameter so as to optimize the quality of the reconstructed image sequence as a whole, leads to erroneous reconstruction of certain regions due to over regularization.
Spatial matching for object retrieval is often time-consuming and susceptible to viewpoint changes. To address this problem, we propose a novel spatial matching method and implement it on modern GPU in parallel. Unlik...
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Spatial matching for object retrieval is often time-consuming and susceptible to viewpoint changes. To address this problem, we propose a novel spatial matching method and implement it on modern GPU in parallel. Unlike previous spatial matching methods, in which the affine transformation estimation is based on the gravity vector assumption, our method abandons this strong assumption by matching the ACNs (affine covariant neighbors) of corresponding local regions and estimating affine transformation from a single pair of corresponding local regions. To speed up the process, we implement the method on modern GPU in parallel. Computations are distributed evenly to threads with load balancing, and the memory accesses are optimized and bitmap based parallel scan is exploited. Experimental results demonstrate that our method is more robust and more efficient than previous methods especially when the viewpoints are changed, and the parallel implementation on GPU obtains ten times speedup.
This paper presents an application of AES (Advanced Encryption Standard) operations in image encryption and decryption. The encrypted cipher images always display the uniformly distributed RGB pixels. It looks like th...
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ISBN:
(纸本)9781424450459
This paper presents an application of AES (Advanced Encryption Standard) operations in image encryption and decryption. The encrypted cipher images always display the uniformly distributed RGB pixels. It looks like the noise of TV without signals. However, in some cases the ECB mode operation may appear a kind of pattern in the area related to the portion of the original image having the same color. The reason for the pattern generation and the four operation modes of CBC, CFB, OFB and CTR which have the features to eliminate the patterns are discussed, in terms of the degree of random noise in cipher image as well as the feasibility of parallel operation in cipher blocks for high speed processing.
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