Workload characterization in a high-energy data grid and impact on resource management

The analysis of data usage in a large set of real traces from a high-energy physics collaboration revealed the existence of an emergent grouping of files that we coined “filecules”. This paper presents the benefits of using this file grouping for prestaging data and compares it with previously proposed file grouping techniques along a range of performance metrics. Our experiments with real workloads demonstrate that filecule grouping is a reliable and useful abstraction for data management in science Grids; that preserving time locality for data prestaging is highly recommended; that job reordering with respect to data availability has significant impact on throughput; and finally, that a relatively short history of traces is a good predictor for filecule grouping. Our experimental results provide lessons for workload modeling and suggest design guidelines for data management in data-intensive resource-sharing environments.

Leitlinien zur molekulargenetischen Diagnostik: Fragiles-X und Fragiles-X assoziiertes Tremor/Ataxie Syndrom

Ohne Zusammenfassung

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A self-managing wide-area data streaming service

Efficient and robust data streaming services are a critical requirement of emerging Grid applications, which are based on seamless interactions and coupling between geographically distributed application components. Furthermore the dynamism of Grid environments and applications requires that these services be able to continually manage and optimize their operation based on system state and application requirements. This paper presents a design and implementation of such a self-managing data-streaming service based on online control strategies. A Grid-based fusion workflow scenario is used to evaluate the service and demonstrate its feasibility and performance.

Scheduling mixed-parallel applications with advance reservations

This paper investigates the scheduling of mixed-parallel applications, which exhibit both task and data parallelism, in advance reservations settings. Both the problem of minimizing application turn-around time and that of meeting a deadline are studied. For each several scheduling algorithms are proposed, some of which borrow ideas from previously published work in non-reservation settings. Algorithms are compared in simulation over a wide range of application and reservation scenarios. The main finding is that schedules computed using the previously published CPA algorithm can be adapted to advance reservation settings, notably resulting in low resource consumption and thus high efficiency.

Individual variability of behavioural responses by Wandering Albatrosses (Diomedea exulans) to human disturbance

Sub-Antarctic Marion Island has had a permanent research station for 50 years and the islands Wandering Albatrosses have been intensively studied for 20 years. The reactions of breeding birds to approaches by a human on foot were recorded. Three response variables were calculated: intensity of vocal reaction (IVR), intensity of non-vocal reaction (INR) and overall response index (ORI). At 5 m from the nest, twice as many birds stood and/or vocalised as at 15 m. Nearest neighbour distance, age and gender did not explain individual variability of responses. Study colony birds had higher IVR scores than non-study colony birds; birds at colonies closest to the station had the highest ORI scores. A better breeding record was associated with lower IVR and ORI scores, but a causative relationship remains to be demonstrated. A minimum viewing distance of 25 m is recommended for breeding Wandering Albatrosses.

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Hennigian Phylogenetic Systematics and the ‘Groundplan’ vs. ‘Post-Groundplan’ Approaches: A Reply to Kukalová-Peck

The recent contribution by Jarmila Kukalová-Peck on Hennigian phylogenetics and hexapod limb evolution is critically evaluated.

Grid user requirements—2004: a perspective from the trenches

Pervasive Grid adoption is predicated on the availability of widely deployed usable software and a user community willing to use it. Currently, widespread adoption of Grids, even within technically sophisticated communities, is limited, and determining and eliminating these barriers to adoption are essential in order for Grids to becoming widely capitalized. Through a series of face-to-face interviews conducted during the summer of 2004, we have identified issues relating to job submission, file transfer, usability, and systems management that must be resolved in order to improve the usability of Grid infrastructures. The background to these issues and some possible solutions are described in this paper.

Causal Explanation of Indonesian Forest Fires: Concepts, Applications, and Research Priorities

Problems with studies, claims, and assumptions that have been made about the causes of fires in Indonesia's tropical moist forests are identified, and the kinds of concepts, methods, prioritizing, and data needed to resolve the problems are discussed. Separate sections are devoted to studying ignitions, studying fire susceptibility and fire behavior, and using the goal of causal explanation to guide interdisciplinary research.

Is it a revolution?

Jablonka and Lamb's claim that evolutionary biology is undergoing a ‘revolution’ is queried. But the very concept of revolutionary change has uncertain application to a field organized in the manner of contemporary biology. The explanatory primacy of sequence properties is also discussed.

Gridcast—a next generation broadcast infrastructure?

Gridcast is an R&D project investigating grid ideas and technologies in the broadcasting technical infrastructure. In this paper I discuss the business and technical issues in building infrastructures to support broadcasters and outline the structure of the Gridcast grid-based service oriented architecture for broadcasting playout support.

Compositional reasoning of performance in component-based distributed systems

Rapid prototyping of distributed systems can be achieved by integrating commercial off-the-shelf (COTS) components. With components as the building blocks, it is important to predict the performance of the system based on the performance of individual components. In this paper, performance prediction of a system consisting of a small number of components is investigated under different inter-component communication patterns, and the number of threads provided by components. Based on the experimental results, it can be inferred that the proposed composition rules provide a reasonably accurate prediction of the performance of a system made out of these components.

Best practices for improved governance of coral reef marine protected areas

Coral reef marine protected areas (MPA) are widely distributed around the globe for social and ecological reasons. Relatively few of these MPAs are well managed. This review examines the governance of coral reef MPAs and the means to improve coral reef MPA management. It highlights common governance challenges, such as confused goals, conflict, and unrealistic attempts to scale up beyond institutional capacity. Recommendations, based on field experience and empirical evidence from around the world, are made for best practices at various stages of MPA implementation.

Personal adaptive clusters as containers for scientific jobs

We describe a system for creating personal clusters in user-space to support the submission and management of thousands of compute-intensive serial jobs to the network-connected compute resources on the NSF TeraGrid. The system implements a robust infrastructure that submits and manages job proxies across a distributed computing environment. These job proxies contribute resources to personal clusters created dynamically for a user on-demand. The personal clusters then adapt to the prevailing job load conditions at the distributed sites by migrating job proxies to sites expected to provide resources more quickly. Furthermore, the system allows multiple instances of these personal clusters to be created as containers for individual scientific experiments, allowing the submission environment to be customized for each instance. The version of the system described in this paper allows users to build large personal Condor and Sun Grid Engine clusters on the TeraGrid. Users then manage their scientific jobs, within each personal cluster, with a single uniform interface using the feature-rich functionality found in these job management environments.

Noninvasive Assessment of Gastrointestinal Parasite Infections in Free-Ranging Primates

Recent evidence of emerging human diseases with origins or likely transmission to humans, or both, that involve primates and a greater recognition of the risk of human pathogen transmission to free-ranging primates have raised awareness of the potential impact of zoonotic pathogen transmission on primate conservation and nonhuman primate and human health. As human population density continues to increase exponentially, speeding the reduction and fragmentation of primate habitats, greater human-primate contact is inevitable and even higher rates of pathogen transmission are likely. Thus interest has grown in collecting baseline data on patterns of parasitic infections in wild primate populations to provide an index of population health and to begin to assess and, to manage disease risks. Primatologists traditionally have been involved with such surveys through noninvasive assessment of gastrointestinal parasites. Unfortunately, previous studies have tended toward divergent methodologies, compromising the potential for longitudinal and comparative work. Here, I provide practical guidelines and standardized methodologies for the noninvasive assessment of gastrointestinal parasites of primates.

Hierarchical analysis of piecewise affine models of gene regulatory networks

A key point in the analysis of dynamical models of biological systems is to handle systems of relatively high dimensions. In the present paper we propose a method to hierarchically organize a certain type of piecewise affine (PWA) differential systems. This specific class of systems has been extensively studied for the past few years, as it provides a good framework to model gene regulatory networks. The method, shown on several examples, allows a qualitative analysis of the asymptotic behavior of a PWA system, decomposing it into several smaller subsystems. This technique, based on the well-known strongly connected components decomposition, is not new. However, its adaptation to the non-smooth PWA differential equations turns out to be quite relevant because of the strong discrete structure underlying these equations. Its biological relevance is shown on a 7-dimensional PWA system modeling the gene network responsible for the carbon starvation response in Escherichia coli.

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Time-sharing parallel applications through performance-targeted feedback-controlled real-time scheduling

Most parallel machines, such as clusters, are space-shared in order to isolate batch parallel applications from each other and optimize their performance. However, this leads to low utilization or potentially long waiting times. We propose a self-adaptive approach to time-sharing such machines that provides isolation and allows the execution rate of an application to be tightly controlled by the administrator. Our approach combines a periodic real-time scheduler on each node with a global feedback-based control system that governs the local schedulers. We have developed an online system that implements our approach. The system takes as input a target execution rate for each application, and automatically and continuously adjusts the applications’ real-time schedules to achieve those rates with proportional CPU utilization. Target rates can be dynamically adjusted. Applications are performance-isolated from each other and from other work that is not using our system. We present an extensive evaluation that shows that the system remains stable with low response times, and that our focus on CPU isolation and control does not come at the significant expense of network I/O, disk I/O, or memory isolation.

Robust clustering analysis for the management of self-monitoring distributed systems

We present a decentralized algorithm for online clustering analysis used for anomaly detection in self-monitoring distributed systems. In particular, we demonstrate the monitoring of a network of printing devices that can perform the analysis without the use of external computing resources (i.e. in-network analysis). We also show how to ensure the robustness of the algorithm, in terms of anomaly detection accuracy, in the face of failures of the network infrastructure on which the algorithm runs. Further, we evaluate the tradeoff in terms of overhead necessary for ensuring this robustness and present a method to reduce this overhead while maintaining the detection accuracy of the algorithm.