1598637
Dynamic resource management heuristics for minimizing makespan while maintaining an acceptable level of robustness in an uncertain environment
Heterogeneous parallel and distributed computing systems may operate in an environment where certain system performance features degrade due to unpredictable circumstances. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. This paper presents a mathematical model for quantifying robustness in a dynamic environment where task execution times estimates are known to contain errors. This research proposes, evaluates, and compares ten different dynamic heuristics for their ability to maintain or maximize the proposed dynamic robustness metric in an uncertain environment. In addition, the makespan results of the proposed heuristics are compared to a lower bound
3042095
Measuring the Robustness of Resource Allocations in a Stochastic Dynamic Environment
Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times are stochastic. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of a stochastic dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.
11001529
A Stochastic Approach to Measuring the Robustness of Resource Allocations in Distributed Systems
Often, parallel and distributed computing systems must operate in an environment replete with uncertainty. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of quality of service (QoS) is achieved is an important research problem. This paper defines a stochastic methodology for quantifiably determining a resource allocation's ability to satisfy QoS constraints in the midst of uncertainty in system parameters. Uncertainty in system parameters and its impact on system performance are modeled stochastically. This stochastic model is then used to derive a quantitative expression for the robustness of a resource allocation. The paper investigates the utility of the proposed stochastic robustness metric by applying the metric to resource allocations in a simulated distributed system. The simulation results are then compared with deterministically defined metrics from the literature
18353433
VideoZoom Spatio-Temporal Video Browser
We describe a system for browsing and interactively retrieving video over the Internet at multiple spatial and temporal resolutions. The VideoZoom system enables users to start with coarse, low-resolution views of the sequences and selectively zoom-in in space and time. VideoZoom decomposes the video sequences into a hierarchy of view elements, which are retrieved in a progressive fashion. The client browser incrementally builds the views by retrieving, caching, and assembling the view elements, as needed. By integrating browsing and retrieval into a single progressive retrieval paradigm, VideoZoom provides a new and useful system for accessing video over the Internet. VideoZoom is suitable for digital video libraries and a number of other applications in which streaming methods provide insufficient quality of video, video downloading introduces large latencies, and generating video summaries is difficult or not well integrated with video retrieval tasks.
5110411
Quasigroups and quandles
Abstract Two connexions between quasigroups and quandles are established. In one direction, Joyce's homogeneous quandle construction is shown to yield a quasigroup isotopic to the loop constructed by Scimemi on the set of o-commutators of a group automorphism o. In the other direction, the universal multiplication group construction of quasigroup theory is extended to quandles. The group of a knot becomes the universal right multiplication group of the knot quandle.
13961662
Improving Nearest Neighbor Classifier Using Tabu Search and Ensemble Distance Metrics
The nearest-neighbor (NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good results with this technique is the choice of distance function, and correspondingly which features to consider when computing distances between samples. In this paper, a new ensemble technique is proposed to improve the performance of NN classifier. The proposed approach combines multiple NN classifiers, where each classifier uses a different distance function and potentially a different set of features (feature vector). These feature vectors are determined for each distance metric using Simple Voting Scheme incorporated in Tabu Search (TS). The proposed ensemble classifier with different distance metrics and different feature vectors (TS-DF/NN) is evaluated using various benchmark data sets from UCI Machine Learning Repository. Results have indicated a significant increase in the performance when compared with various well-known classifiers. Furthermore, the proposed ensemble method is also compared with ensemble classifier using different distance metrics but with same feature vector (with or without Feature Selection (FS)).
9694445
The architecture and implementation of a distributed hypermedia storage system
Our project is studying the process by which groups of individuals work together to build large, complex structures of ideas and is developing a distributed hypermedia collaboration environment (called ABC) to support that process. This paper focuses on the architecture and implementation of the Distributed Graph Storage (DGS) component of ABC. The DGS supports a graph-based data model, conservatively extended to meet hypermedia requirements. Some important issues addressed in the system include scale, performance, concurrency semantics, access protection, location independence, and replication (for fault tolerance).
37610017
Validated Cost Models for Parallel OQL Query Processing
Query cost models are widely used, both for performance analysis and for comparing execution plans during query optimisation. In essence, a cost modelp redicts where time is being spent during query evaluation. Although many cost models have been proposed, for serial, parallel and distributed database systems, surprisingly few of these have been validated against real systems. This paper presents cost models for the parallel evaluation of ODMG OQL queries, which have been compared with experimental results obtained using the Polar object database system. The paper describes the validation of the cost model for a collection of queries, using three join algorithms over the OO7 benchmark database. The results show that the cost model generally both ranks alternative plans appropriately, and gives a useful indication of the response times that can be expected from a plan. The paper also illustrates the application of the cost model by highlighting the contributions of different features and operations to query response times.