8353514
Performance of routing protocols in very large-scale mobile wireless ad hoc networks
As wireless devices become more and more popular, ad hoc networks grow in the number of nodes as well as the complexity of communication among the large number of nodes. However, due to the limitation of simulation technologies, it is either impossible or very hard to investigate the scalability of ad hoc routing protocols in very large-scale wireless networks. In this paper, a comprehensive simulation study is conducted of the performance of an on-demand routing protocol on a very large-scale, with as many as 50,000 nodes in the network. We address the scalability analysis based on various network sizes, traffic load, and mobility. The reasons for packet loss are analyzed and categorized at each layer. Based on the observations, we optimize the parameter selection and try to exhaust the scalability boundary of the on-demand routing protocol for wireless ad hoc networks.
1109125
An on-demand Bluetooth scatternet formation and routing protocol for wireless sensor networks
Bluetooth is a promising short-range wireless communication technology with the characteristics of interference resilience and power efficiency which are required by wireless sensor networks. As an enhanced sensor node platform, the Intel Mote uses Bluetoth as its radio scheme and MAC protocol. However, most of the existing scatternet formation protocols intend to connect all the nodes within the networks regardless of traffic pattern. For wireless sensor network applications with traffic of low duty cycle, on-demand scatternet formation and routing achieve significant power saving by avoiding to maintain the entire network connectivity. We propose in this paper an on-demand scatternet and route formation protocol for Bluetooth-based wireless sensor networks. It is able to cope with multiple sources initiating traffic simultaneously in densely deployed wireless sensor networks. We also introduce a modified inquiry scheme using extended ID packet for power efficient propagation of route request messages. Furthermore, we propose a mechanism employing POLL packets in Page processes to transfer scatternet formation and route reply information without extra overhead. Simulation results show that our on-demand scatternet formation and routing protocol can provide multihop channels with reasonable delay for Bluetooth-base wireless sensor networks.
14863017
A simulation and data analysis system for large-scale, data-driven oil reservoir simulation studies
The main goal of oil reservoir management is to provide more efficient, cost-effective and environmentally safer production of oil from reservoirs. Numerical simulations can aid in the design and implementation of optimal production strategies. However, traditional simulation-based approaches to optimizing reservoir management are rapidly overwhelmed by data volume when large numbers of realizations are sought using detailed geologic descriptions. In this paper, we describe a software architecture to facilitate large-scale simulation studies, involving ensembles of long-running simulations and analysis of vast volumes of output data. Copyright © 2005 John Wiley & Sons, Ltd.
18753637
Fast factorization architecture in soft-decision Reed-Solomon decoding
Reed-Solomon (RS) codes are among the most widely utilized block error-correcting codes in modern communication and computer systems. Compared to its hard-decision counterpart, soft-decision decoding offers considerably higher error-correcting capability. The recent development of soft-decision RS decoding algorithms makes their hardware implementations feasible. Among these algorithms, the Koetter-Vardy (KV) algorithm can achieve substantial coding gain for high-rate RS codes, while maintaining a polynomial complexity with respect to the code length. In the KV algorithm, the factorization step can consume a major part of the decoding latency. A novel architecture based on root-order prediction is proposed in this paper to speed up the factorization step. As a result, the time-consuming exhaustive-search-based root computation in each iteration level, except the first one, of the factorization step is circumvented with more than 99% probability. Using the proposed architecture, a speedup of 141% can be achieved over prior efforts for a (255, 239) RS code, while the area consumption is reduced to 31.4%.
14269691
Multiprocessor scalability predictions through detailed program execution analysis
Scalability measures the ability of a parallel system to improve performance as the size of an application problem and the number of processors involved increase. There are some limits to existing scalability studies. First, the problem size in a computation is not well-defined. Second, the methods used to differentiate algorithmic and architectural scalabilities are not effective enough. Thh-dly, most approaches to scalability study are either highly time-consuming or restricted to simple problem/architecture structures. A major effort of this work is to address these limits. We have extended the latency metric [11] for more complex scaling of problems, and to possibly isolate the scalability of an algorithm from a parallel system. The scalability y prediction is based on a semi-empirical approach [10] that significantly reduces the time and cost of measurements and simulation. Our prediction results were validated on the KSR1 and on the CM-5.
14218778
Reconstruction of DNA sequencing by hybridization
MOTIVATION
It is widely recognized that the hybridization process is prone to errors and that the future of DNA sequencing by hybridization is predicated on the ability to successfully cope with such errors. However, the occurrence of hybridization errors results in the computational difficulty of the reconstruction of DNA sequencing by hybridization. The reconstruction problem of DNA sequencing by hybridization with errors is a strongly NP-hard problem. So far the problem has not been solved well.


RESULTS
In this paper, a new approach is presented to solve the reconstruction problem of DNA sequencing by hybridization, which realizes the computational part of the SBH experiment. The proposed algorithm accepts both the negative and positive errors. The computational experiments show that the algorithm behaves satisfactorily, especially for the case with k-tuple repetitions and positive errors.
14579845
Texture image retrieval based on a Gaussian mixture model and similarity measure using a Kullback divergence
In a content-based image retrieval (CBIR) system, indexing feature vectors and the similarity measure between feature vectors are two key factors for retrieval performance. We present a new CBIR system with statistical-model based image feature extraction in the wavelet domain and a Kullback divergence based similarity measure. A two component Gaussian mixture model (GMM) in the wavelet domain is employed and the model parameters are used to form features for image indexing. A new Kullback divergence based similarity measure is then presented for image retrieval. The experimental results demonstrate that the similarity measure based on the Kullback divergence is more effective than conventional similarity measures, such as the city-block distance and the Euclidean distance. It is shown that the new CBIR system, with the combination of the GMM and the new Kullback divergence based similarity measure, outperforms most other methods in retrieval performance for texture images, while keeping a comparable level of computational complexity.