14060490
Power-aware broadcasting and activity scheduling in ad hoc wireless networks using connected dominating sets
In ad hoc mobile wireless networks, owing to host mobility, broadcasting is expected to be more frequently used to find a route to a particular host, to page a host, and to alarm all hosts. A straightforward broadcasting by flooding is usually very costly and will result in substantial redundancy and more energy consumption. Power consumption is an important issue since most mobile hosts operate on battery. Broadcasting based on a connected dominating set is a promising approach, where only nodes in the dominating set need to relay the broadcast packet. A set is dominating if all the nodes in the system are either in the set or are neighbors of nodes in the set. Wu and Li proposed a simple and efficient distributed algorithm for calculating connected dominating set in ad hoc wireless networks, where connections of nodes are determined by their geographical distances. In general, nodes in the connected dominating set consume more energy to handle various bypass traffic than nodes outside the set. To prolong the life span of each node and, hence, the network by balancing the energy consumption in the system, nodes should be alternately chosen to form a connected dominating set. Activity scheduling deals with the way of rotating the role of each node among a set of given operation modes (e.g. dominating nodes versus dominated nodes). In this paper, we propose to apply the notion of power-aware connected dominating set to broadcasting and activity scheduling. The effectiveness of the proposed method in prolonging the life span of the network is confirmed through simulation. Copyright © 2003 John Wiley & Sons, Ltd.
7582647
On self-similarity and hamiltonicity of dual-cubes
The dual-cube is a newly proposed topology for interconnection networks, which uses low dimensional hypercubes as building blocks. The primary advantages of the dual-cube over the hypercube are that, with the same node degree n, the dual-cube contains 2/sup n-1/ times more nodes than the hypercube and, with the same amount of nodes, the dual-cube has approximately 50% less links than the hypercube. This paper was focused on the investigations of the structural self-similarity and the Hamiltonian property of the dual-cube. It was shown that a dual-cube can be recursively constructed from lower dimensional dual-cubes and, conversely, a dual-cube can be recursively decomposed into lower dimensional dual-cubes. It was also proved that all dual-cubes are Hamiltonian. There exist multiple Hamiltonian cycles on a dual-cube, among which, [(n-1)/2] cycles are edge-disjoint. It was illustrated that rings and linear arrays can be effectively emulated on dual-cubes. Some strategies for track sharing in efficient VLSI layout design were also discussed.
16257632
XYZ: a scalable, partially centralized lookup service for large-scale peer-to-peer systems
Peer-to-peer (P2P) systems are characterized by direct access between peer computers, rather than through a centralized server. File sharing is the dominant P2P application on the Internet, allowing users to easily contribute, search and obtain content. P2P systems can be categorized by the degrees of centralization. For fully centralized systems, the lookup service will not be available when the central directory server is down. For purely decentralized and unstructured systems, since there is no information about which nodes are likely to have the relevant files, searching essentially amounts to random search. This makes the lookup service unscalable and unpredictable. The objective of this paper is to design a partially centralized, scalable and self-organizing lookup service (XYZ) for wide area P2P systems. A clustering method is used to create the system backbone by connecting the cluster heads together and a color clustering method is adopted to create color overlays and minimize the searching space. Simulations and analysis are also provided. Extensions are proposed to achieve better performance
27746153
Broadcasting in Faulty Cube-Connected-Cycles with Minimum Recovery Time
We propose a broadcasting algorithm for a faulty Cube-Connected-Cycles multiprocessor. The broadcasting algorithm delivers a message to all the nodes non-redundantly using a binomial tree. The traffic generated because of the recovery is guaranteed to be minimum.
2254959
Local-Safety-Information-Based Broadcasting in Hypercube Multicomputers with Node and Link Faults
This paper presents a method to cope with fault-tolerant broadcasting in hypercube multicomputers with both node and link faults. The local safety concept is extended to faulty hypercubes with both node and link faults. The local-safety-based algorithm is used in a fully unsafe hypercube, where there is no safe node. A fully unsafe hypercube can be split into a set of maximal safe subcubes. We show that if these maximal safe subcubes meet certain requirements given in the paper, broadcasting can still be carried out successfully and in some case optimal broadcast is still possible. The method is extended to fault-tolerant routing and multicasting when the system contains both node and link faults.
17371165
QoS Routing in Hypercube Multicomputers
In this paper, we present a coding method to capture QoS information in hypercube multicomputers. The coding method is based on a localized algorithm where each node interacts with its neighbors to gather QoS information. Specifically, each node maintains a QoS vector where the k-th element represents the guaranteed QoS performance to a destination that is k hops away. The localized algorithm exhibits desirable properties of self-stabilizing, self-optimizing, and self-healing. Simulation results show that this coding method provides a good approximation of the minimum QoS value to a k-hop destination and, at the same time, uses a relatively small number of packets to propagate a change in link state (QoS value) compared with the classical distributed Bellman-Ford method.
7567561
Genetic Algorithm based Selective Neural Network Ensemble
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, the relationship between the generalization ability of the neural network ensemble and the correlation of the individual neural networks is analyzed, which reveals that ensembling a selective subset of individual networks is superior to ensembling all the individual networks in some cases. Therefore an approach named GASEN is proposed, which trains several individual neural networks and then employs genetic algorithm to select an optimum subset of individual networks to constitute an ensemble. Experimental results show that, comparing with a popular ensemble approach, i.e. averaging all, and a theoretically optimum selective ensemble approach, i.e. enumerating, GASEN has preferable performance in generating ensembles with strong generalization ability in relatively small computational cost.
11280225
Realistic modeling of bird flight animations
In this paper we describe a physics-based method for synthesis of bird flight animations. Our method computes a realistic set of wingbeats that enables a bird to follow the specified trajectory. We model the bird as an articulated skeleton with elastically deformable feathers. The bird motion is created by applying joint torques and aerodynamic forces over time in a forward dynamics simulation. We solve for each wingbeat motion separately by optimizing for wingbeat parameters that create the most natural motion. The final animation is constructed by concatenating a series of optimal wingbeats. This detailed bird flight model enables us to produce flight motions of different birds performing a variety of maneuvers including taking off, cruising, rapidly descending, turning, and landing.
2718321
Face recognition with one training image per person
At present there are many methods that could deal well with frontal view face recognition. However, most of them cannot work well when there is only one training image per person. In this paper, an extension of the eigenface technique, i.e. projection-combined principal component analysis, (PC)2A, is proposed. (PC)2A combines the original face image with its horizontal and vertical projections and then performs principal component analysis on the enriched version of the image. It requires less computational cost than the standard eigenface technique and experimental results show that on a gray-level frontal view face database where each person has only one training image, (PC)2A achieves 3-5% higher accuracy than the standard eigenface technique through using 10-15% fewer eigenfaces.
2622485
Diagnostic test generation for sequential circuits
Efficient diagnosis of faults in VLSI circuits requires high quality diagnostic test sets. In this work novel techniques for diagnostic test generation are proposed that require significantly less time than previous methods. The set of fault pairs left undistinguished by a detection-oriented test set is first filtered to target only testable faults. Then diagnostic test generation is performed using a genetic algorithm (GA) combined with a diagnostic fault simulator. A new fitness metric is proposed for the GA that accurately measures the quality of candidate sequences while requiring a limited amount of CPU time. Experimental results illustrate the effectiveness of the approach for sequential circuits.
59008197
A cycle-based rerouting scheme for wavelength-routed WDM networks
In this paper, we propose a cycle-based rerouting scheme (CRS) for link restoration in wavelength-routed WDM networks. The CRS is based on a scalable set of Pcycles covering a mesh network. Instead of using these Pcycles as enhanced self-healing rings as in traditional approaches, the CRS decomposes these P-cycles into rerouting paths for the links that the P-cycles cover. In this way, flexible and cost-effective link restoration is achieved. Simulation results show that the rerouting performance of the CRS can be very close to the theoretical upper bound.