20128924
Long path connectivity of regular graphs
Abstract Any pair of vertices in a 4-connected non-bipartite k -regular graph are joined by a Hamilton path or a path of length at least 3 k −6.
1145290
Hamilton cycles in regular 3-connected graphs
Abstract We show in this paper that for k ⩾63, every 3-connected, k -regular simple graph on at most 22 7 k vertices is hamiltonian.
15428033
On Optimal Physical Carrier Sensing: Theoretical Analysis and Protocol Design
Traditional Physical Carrier Sensing (PCS), which aims at eliminating hidden terminals in wireless networks, causes too many exposed terminals and deteriorates the throughput per user seriously. Some existing work has proven that an aggressive PCS can improve the throughput by balancing the tradeoff between hidden terminals and exposed terminals. However, little work has been conducted to optimize the PCS according to the network conditions. In this paper, we develop an analytical model to study the behaviors of a user in the aggressive PCS scenario, with which the optimal PCS threshold can be derived. Then, to avoid the complicated computation, we present a heuristic algorithm, in which the parameters required for PCS tuning are estimated by the carrier sensing mechanism employed in IEEE 802.11. Simulation results show that the proposed heuristic algorithm can make the PCS threshold approach to the theoretical optimal one. Moreover, the proposed heuristic algorithm can obtain significant throughput gain compared to the traditional PCS threshold setting solutions.
2014328
A 3D reconstruction algorithm based on 3D deformable atlas
Reconstructing 3D models from 2D images is an important problem in visualization, particularly in medical and biological visualization. We present a new algorithm for 3D model reconstruction from 2D-images. In our approach, a 3D atlas is deformed to fit the feature data set in the target images. Compared with existing 3D reconstruction techniques, our approach is more efficient and easier to control. The resultant model has good inherent connectivity and smoothness. The resolution of the final model is determined by the resolution of reference model rather than the dataset. The model generates highly detailed view with a limited number of images. This algorithm has been successfully applied to medical simulation.
10155852
Nexus: a novel weighted-graph-based prefetching algorithm for metadata servers in petabyte-scale storage systems
An efficient, accurate and distributed metadata-oriented prefetching scheme is critical to the overall performance in large distributed storage systems. In this paper, we present a novel weighted-graph-based prefetching technique, built on successor relationship, to gain performance benefit from prefetching specifically for clustered metadata servers, an arrangement envisioned necessary for petabyte-scale distributed storage systems. Extensive trace-driven simulations show that by adopting our new prefetching algorithm, the hit rate for metadata access on the client site can be increased by up to 13%, while the average response time of metadata operations can be reduced by up to 67%, compared with LRU and an existing state of the art prefetching algorithm.
2274256
Overlay Networks with Linear Capacity Constraints
Overlay networks are virtual networks residing over the IP network; consequently, overlay links may share hidden lower level bottlenecks. Previous work has assumed an independent overlay model: a graph with independent link capacities. We introduce a model of overlays that incorporates correlated link capacities and linear capacity constraints (LCC) to formulate hidden shared bottlenecks; we refer to these as LCC-overlays. We define metrics to qualitatively measure overlay quality in terms of its accuracy (in representing the true network topology) and efficiency (that is, performance). Through analysis and simulations, we show that LCC-overlay is perfectly accurate and, hence, enjoys much higher efficiency than the inaccurate independent overlay. We discover that even a highly restricted LCC class-node-based LCC-yields near-optimal accuracy and significantly higher efficiency. We study two network flow problems in the context of LCC-graphs: widest path and maximum flow. We prove that Widest Path with LCC is NP-complete. We formulate Maximum Flow with LCC as a linear program and propose an efficient distributed algorithm to solve it. Based on the LCC model, we further study the problem of optimizing delay while still maintaining optimal or near-optimal bandwidth. We also outline a distributed algorithm to efficiently construct an overlay with node-based LCC.
8105623
Computerized tumor boundary detection using a Hopfield neural network
The authors present a new approach for detection of brain tumor boundaries in medical images using a Hopfield neural network. The boundary detection problem is formulated as an optimization process that seeks the boundary points to minimize an energy functional based on an active contour model. A modified Hopfield network is constructed to solve the optimization problem. Taking advantage of the collective computational ability and energy convergence capability of the Hopfield network, the authors' method produces the results comparable to those of standard "snakes"-based algorithms, but it requires less computing time. With the parallel processing potential of the Hopfield network, the proposed boundary detection can be implemented for real time processing. Experiments on different magnetic resonance imaging (MRI) data sets show the effectiveness of the authors' approach.