14338621
A distributed object model for solving irregularly structured problems on cluster
This paper presents a distributed object model MOIDE (Multithreaded Object-oriented Infrastructure on Distributed Environment) for solving irregularly structured problems on cluster. The primary appeal of MOIDE is its flexible system structure that is adaptive to heterogeneous architecture of a cluster. MOIDE integrates the object-oriented and multithreaded methodologies to set up a unified computing environment. Both the shared-data access and remote messaging are incorporated in a two-layer communication mechanism for efficient inter-object communication with the common communication interface. MOIDE supports dynamic load balancing by its autonomous load scheduling technique. A runtime support system implements the MOIDE model as a platform-independent infrastructure for developing and executing irregularly structured applications. N-body, ray tracing, and conjugate gradient applications are implemented to illustrate the advantages of MOIDE model.
1335499
Dynamic configuration management in a graph-oriented Distributed Programming Environment
Dynamic configuration is a desirable property of a distributed system where dynamic modification and extension to the system and the applications are required. It allows the system configuration to be specified and changed while the system is executing. This paper describes a software platform that facilitates a novel approach to the dynamically configurable programming of parallel and distributed applications and systems. This platform is based on a graph-oriented model and it provides support for constructing reconfigurable distributed programs. We describe the design and implementation of a dynamic configuration manager for the graph-oriented distributed programming environment. The requirements and services for dynamic reconfiguration are identified. The architectural design of a dynamic configuration manager is presented, and a parallel virtual machine-based prototypical implementation of the manager, on a local area network of workstations, is described.
11115305
Graph Scaling: A Technique for Automating Program Construction and Deployment in ClusterGOP
Program development and resource management are critical issues in large-scaled parallel applications and they raise diffculties for the programmers. Automation tools can benefit the programmer by reducing the time and work required for programming, deploying, and managing parallel applications. In our previous work, we have developed a visual tool, VisualGOP, to help visual construction and automatic mapping of parallel programs to execute on the ClusterGOP platform, which provides a graph-oriented model and the environment for running the parallel applications on clusters. In VisualGOP, the programmer needs to manually build the task interaction graph. This may lead to scalability problem for large applications. In this paper, we propose a graph scaling approach that helps the programmer to develop and deploy a large-scale parallel application minimizing the effort of graph construction, task binding and program deployment. The graph scaling algorithms expand or reduce a task graph to match the specified scale of the program and the hardware architecture, e.g., the problem size, the number of processors and interconnection topology, so as to produce an automatic mapping. An example is used to illustrate the proposed approach and how programmer benefits in the automation tools.
2733368
Low delay rate-control in video transcoding
In order to obtain optimal visual quality while meeting the bit rate requirements, a video transcoder needs efficient rate-control with fine and dynamic adjustments. This paper proposes a new frequency domain complexity estimation scheme and an algorithm for adaptive bit allocation during transcoding. In conjunction with frame skipping mechanism, the proposed algorithm adaptively determines spatial coding parameters to realize very low target bitrate for MPEG-2 to MPEG-4 transcoding. Experiments show that the proposed algorithm performs accurate target bit rate transcoding, improves the visual quality and effectively alleviates visual quality degradation during scene changes.
3124333
Stochastic iterative algorithms for signal set design for Gaussian channels and optimality of the L2 signal set
We propose a stochastic iteration approach to signal set design. Four practical stochastic iterative algorithms are proposed with respect to equal and average energy constraints and sequential and batch modes. By simulation, a new optimal signal set, the L2 signal set (consisting of a regular simplex set of three signals and some zero signals), is found under the strong simplex conjecture (SSC) condition (equal a priori probability and average energy constraint) at low signal-to-noise ratios (SNR). The optimality of the L1 signal set, the confirmation of the weak simplex conjecture, and two of Dunbridge's (1967) theorems are some of the results obtained by simulations. The influence of SNR and a priori probabilities on the signal sets is also investigated via simulation. As an application to practical communication system design, the signal sets of eight two-dimensional (2-D) signals are studied by simulation under the SSC condition. Two signal sets better than 8-PSK are found. Optimal properties of the L2 signal set are analyzed under the SSC condition at low SNRs. The L2 signal set is proved to be uniquely optimal in 2-D space. The class of signal sets S(M, K) (consisting of a regular simplex set of K signals and M-K zero signals) is analyzed. It is shown that any of the signal sets S(M, K) for 3/spl les/K/spl les/M-1 disproves the strong simplex conjecture for M/spl ges/4, and if M/spl ges/7, S(M, 2) (the L1 signal set) also disproves the strong simplex conjecture. It is proved that the L2 signal set is the unique optimal signal set in the class of signal sets S(M, K) for all M/spl ges/4. Several results obtained by Steiner (see ibid., vol.40, no.5, p.721-31, 1994) for all M/spl ges/7 are extended to all M/spl ges/4. Finally, we show that for M/spl ges/7, there exists an integer K'
61852216
Cross-Evaluation: A new model for information system evaluation
In this article, we introduce a new information system evaluation method and report on its application to a collaborative information seeking system, AntWorld. The key innovation of the new method is to use precisely the same group of users who work with the system as judges, a system we call Cross-Evaluation. In the new method, we also propose to assess the system at the level of task completion. The obvious potential limitation of this method is that individuals may be inclined to think more highly of the materials that they themselves have found and are almost certain to think more highly of their own work product than they do of the products built by others. The keys to neutralizing this problem are careful design and a corresponding analytical model based on analysis of variance. We model the several measures of task completion with a linear model of five effects, describing the users who interact with the system, the system used to finish the task, the task itself, the behavior of individuals as judges, and the self-judgment bias. Our analytical method successfully isolates the effect of each variable. This approach provides a successful model to make concrete the “three-realities” paradigm, which calls for “real tasks,” “real users,” and “real systems.” © 2006 Wiley Periodicals, Inc.
2615609
EigenNail for Finger Force Direction Recognition
This paper presents a technique termed eigennails to classify fingertip force during contact based on the coloration patterns in the fingernail and surrounding skin. Fingertip force is classified into six directions: no force, normal force only, two directions (left/right) of lateral shear force, and two directions (forward/backward) of longitudinal shear forces. Based on the face recognition technique eigenfaces, a small number of eigennails are sufficient to express the color pattern features for shear force direction classification. Results show that 98% of 960 fingernail images of 8 different subjects are correctly classified. The lowest imaging resolution without sacrificing classification accuracy is found to be 10-by-10.
47269670
Motion estimation for content adaptive video compression
A multistage motion estimation scheme is proposed. The scheme extracts video characteristics by first performing an online video analysis separately for foreground and background regions. Motion parameters are extracted and passed to the next stage. The next stage includes a mathematical model for the block distortion surface (BDS) that enables the algorithm to accordingly adjust its search technique. The search is performed on a precise search area adaptive to the statistical property of the motion vector prediction error. Due to its self-tuning property, not only does the proposed scheme adapt to scenes by yielding better visual quality but it also yields a lower computational complexity, compared with the other predictive motion estimation algorithms on standard benchmark sequences