Models and heuristics for robust resource allocation in parallel and distributed computing systems

Includes bibliographical references.This is an overview of the robust resource allocation research efforts that have been and continue to be conducted by the CSU Robustness in Computer Systems Group. Parallel and distributed computing systems, consisting of a (usually heterogeneous) set of machines and networks, frequently operate in environments where delivered performance degrades due to unpredictable circumstances. Such unpredictability can be the result of sudden machine failures, increases in system load, or errors caused by inaccurate initial estimation. The research into developing models and heuristics for parallel and distributed computing systems that create robust resource allocations is presented.This research was supported by NSF under grant No. CNS-0615170 and by the Colorado State University George T. Abell Endowment

A New Species of \u3ci\u3eMyxidium\u3c/i\u3e (Myxosporea: Myxidiidae), from the Western Chorus Frog, \u3ci\u3ePseudacris triseriata triseriata\u3c/i\u3e, and Blanchard\u27s Cricket Frog, \u3ci\u3eAcris crepitans blanchardi\u3c/i\u3e (Hylidae), from Eastern Nebraska: Morphology, Phylogeny, and Critical Comments on Amphibian \u3ci\u3eMyxidium\u3c/i\u3e Taxonomy

During March 2001-April 2004, 164 adult anurans of 6 species (47 Rana blairi, 35 Rana catesbeiana, 31 Hyla chrysoscelis, 31 Pseudacris triseriata triseriata, 11 Bufo woodhousii, and 9 Acris crepitans blanchardi) from Pawnee Lake, Lancaster County, Nebraska, were surveyed for myxozoan parasites. Of these, 20 of 31 (65%) P. triseriata triseriata and 1 of 9 (11%) A. crepitans blanchardi were infected with a new species of Myxidium. Myxidium melleni n. sp. (Myxosporea) is described from the gallbladder of the western chorus frog, P. triseriata triseriata (Hylidae). This is the second species of Myxidium described from North American amphibians. Mature plasmodia are disc-shaped or elliptical 691 (400-1,375) × 499 (230-1,200) × 23 (16-35) μm, polysporic, producing many disporic pansporoblasts. The mature spores, 12.3 (12.0-13.5) × 7.6 (7.0-9.0) × 6.6 (6.0-8.0) μm, containing a single binucleated sporoplasm, are broadly elliptical, with 2-5 transverse grooves on each valve, and contain two equal polar capsules 5.2 (4.8-5.5) × 4.2 (3.8-4.5) μm positioned at opposite ends of the spore. Myxidium melleni n. sp. is morphologically consistent with other members of Myxidium. However, M. melleni n. sp. was phylogenetically distinct from other Myxidium species for which DNA sequences are available. Only with improved morphological analyses, accompanied by molecular data, and the deposit of type specimens, can the ambiguous nature of Myxidium be resolved. Guidelines for descriptions of new species of Myxidium are provided

Tributes to Rick Edwards upon His Retirement

I understand that you will be retiring from UNL in August. I wanted to express my sadness that you will be leaving the Center for Great Plains Studies, but am glad that you will now be able to perhaps enjoy life even more without having to do the administrative tasks that go with being the director of any organization. (RFD

Measuring the robustness of resource allocations for distributed domputer systems in a stochastic dynamic environment

Heterogeneous distributed computing systems often must function in an environment where system parameters are subject to variations during operation. 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 vary within predictable ranges and tasks arrive randomly. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of the stochastically modeled 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

Fundulus as the premier teleost model in environmental biology : opportunities for new insights using genomics

Author Posting. © Elsevier B.V., 2007. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology Part D: Genomics and Proteomics 2 (2007): 257-286, doi:10.1016/j.cbd.2007.09.001.A strong foundation of basic and applied research documents that the estuarine fish Fundulus heteroclitus and related species are unique laboratory and field models for understanding how individuals and populations interact with their environment. In this paper we summarize an extensive body of work examining the adaptive responses of Fundulus species to environmental conditions, and describe how this research has contributed importantly to our understanding of physiology, gene regulation, toxicology, and ecological and evolutionary genetics of teleosts and other vertebrates. These explorations have reached a critical juncture at which advancement is hindered by the lack of genomic resources for these species. We suggest that a more complete genomics toolbox for F. heteroclitus and related species will permit researchers to exploit the power of this model organism to rapidly advance our understanding of fundamental biological and pathological mechanisms among vertebrates, as well as ecological strategies and evolutionary processes common to all living organisms.This material is based on work supported by grants from the National Science Foundation DBI-0420504 (LJB), OCE 0308777 (DLC, RNW, BBR), BES-0553523 (AW), IBN 0236494 (BBR), IOB-0519579 (DHE), IOB-0543860 (DWT), FSML-0533189 (SC); National Institute of Health NIEHS P42-ES007381(GVC, MEH), P42-ES10356 (RTD), ES011588 (MFO); and NCRR P20 RR-016463 (DWT); Natural Sciences and Engineering Research Council of Canada Discovery (DLM, TDS, WSM) and Collaborative Research and Development Programs (DLM); NOAA/National Sea Grant NA86RG0052 (LJB), NA16RG2273 (SIK, MEH,GVC, JJS); Environmental Protection Agency U91620701 (WSB), R82902201(SC) and EPA’s Office of Research and Development (DEN)

POST-RETIREMENT ACTIVITY AND ADJUSTMENT TO OCCUPATIONAL RETIREMENT: A RE-EXAMINATION WITHIN A FRAMEWORK OF ROLE AND SELF THEORY

Abstract not availabl

Tributes to Rick Edwards upon His Retirement

I understand that you will be retiring from UNL in August. I wanted to express my sadness that you will be leaving the Center for Great Plains Studies, but am glad that you will now be able to perhaps enjoy life even more without having to do the administrative tasks that go with being the director of any organization. (RFD

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. 1

Measuring the robustness of resource allocations in a stochastic dynamic environment

Includes bibliographical references.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.This research was supported by the NSF under Contract No: CNS-0615170, by the Colorado State University Center for Robustness in Computer Systems (funded by the Colorado Commission on Higher Education Technology Advancement Group through the Colorado Institute of Technology), and by the Colorado State University George T. Abell Endowment

Stochastic-based Robust Dynamic Resource Allocation for Independent Tasks in a Heterogeneous Computing System

Heterogeneous parallel and distributed computing systems frequently must operate in environments where there is uncertainty in system parameters. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. In such an environment, the execution time of any given task may fluctuate substantially due to factors such as the content of data to be processed. Determining a resource allocation that is robust against this uncertainty is an important area of research. In this study, we define a stochastic robustness measure to facilitate resource allocation decisions in a dynamic environment where tasks are subject to individual hard deadlines and each task requires some input data to start execution. In this environment, the tasks that cannot meet their deadlines are dropped (i.e., discarded). We define methods to determine the stochastic completion times of tasks in the presence of the task dropping. The stochastic task completion time is used in the definition of the stochastic robustness measure. Based on this stochastic robustness measure, we design novel resource allocation techniques that work in immediate and batch modes, with the goal of maximizing the number of tasks that meet their individual deadlines. We compare the performance of our technique against several well-known approaches taken from the literature and adapted to our environment. Simulation results of this study demonstrate the suitability of our new technique in a dynamic heterogeneous computing system