13294756
Mapping subtasks with multiple versions on an ad hoc grid
An ad hoc grid is a heterogeneous computing system composed of mobile devices. Each computing resource is constrained in battery energy. The problem being studied is to assign statically computing resources to the subtasks of an application that has an execution time constraint, when the resources are oversubscribed. All subtasks must be executed; to accommodate this in an oversubscribed environment, each subtask has two versions: the primary or full version, and the secondary or degraded version. The secondary version utilizes only 10% of the resources that the primary version requires, and produces only 10% of the data output for the subsequent children subtasks. Thus, the degraded version (secondary version) represents a reduced capability of lesser overall value, while consuming fewer resources. The goal is to assign resources so that the application meets an execution time constraint and the battery energy constraint while minimizing the number of degraded versions used. Five resource allocation heuristics to derive near-optimal solutions to this problem are presented, evaluated, and compared.
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
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
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.
20964781
Special Issue on Image Understanding for Digital Photographs
2764558
A statistical modeling approach to content based video retrieval
Statistical: modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evaluation and comparison of a variety of different algorithms on a set of high-level queries for multimedia retrieval. We report on the use of techniques adopted from statistical learning theory. Our method depends on training of models based on large data sets. Particularly, we use statistical models such as Gaussian mixture models to build computational representations for a variety of semantic concepts including rocket-launch, outdoor greenery, sky etc. Training requires a large amount of annotated (labeled) data. Thus, we explore the use of active learning for the annotation engine that minimizes the number of training samples to be labeled for satisfactory performance.
6106969
Service-Based Distributed Querying on the Grid
Service-based approaches (such as Web Services and the Open Grid Services Architecture) have gained considerable attention recently for supporting distributed application development in e-business and e-science. The emergence of a service-oriented view of hardware and software resources raises the question as to how database management systems and technologies can best be deployed or adapted for use in such an environment. This paper explores one aspect of service-based computing and data management, viz., how to integrate query processing technology with a service-based Grid. The paper describes in detail the design and implementation of a service-based distributed query processor for the Grid. The query processor is service-based in two orthogonal senses: firstly, it supports querying over data storage and analysis resources that are made available as services, and, secondly, its internal architecture factors out as services the functionalities related to the construction of distributed query plans on the one hand, and to their execution over the Grid on the other. The resulting system both provides a declarative approach to service orchestration in the Grid, and demonstrates how query processing can benefit from dynamic access to computational resources on the Grid.
7794743
Efficient, automatic web resource harvesting
There are two problems associated with conventional web crawling techniques: a crawler cannot know if all resources at a non-trivial web site have been discovered and crawled ("the counting problem") and the human-readable format of the resources are not always suitable for machine processing ("the representation problem"). We introduce an approach that solves these two problems by implementing support for both the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) and MPEG-21 Digital Item Declaration Language (DIDL) into the web server itself. We present the Apache module "mod_oai", which can be used to address the counting problem by listing all valid URIs at a web server and efficiently discovering updates and additions on subsequent crawls. Our experiments indicated comparable performance for initial crawls, and dramatic increases in update speed mod_oaican also be used to address the representation problem by providing "preservation ready" versions of web resources aggregated with their respective forensic metadata in MPEG-21 DIDL format.
206475336
Adapting content to client resources in the Internet
We address the delivery of composite multimedia documents, namely Web pages, over the Internet to clients with diverse resources and capabilities. We do so by adapting the multimedia content to meet the client device characteristics. We model the adaptation process as a resource allocation problem in a generalized rate-distortion framework. In this framework, we address the issue of both multiple media types in a Web document and multiple resource types at the client. We extend this framework to allow prioritization on the content items in a Web document. We illustrate our content adaptation technique with a Web server that adapts multimedia news stories to clients as diverse as workstations, PDAs and cellular phones.