Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Talent Management in Higher Education: Developing Emerging Leaders Within the Administration at Private Colleges and Universities

This research focused on identifying a series of successful practices relating to administrative talent management within the higher education setting. The field study included a thorough examination of seven small to mid-size private colleges and universities that have incorporated employee development strategies. These strategies were aimed at growing future leaders from within the organization in order to achieve continuity and support institutional priorities. Specifically, several focus areas were investigated including presidential vision, leadership commitment, talent management’s place among institutional priorities, program characteristics, and program evaluation. Among the commonalities that were gathered included support at the senior officer level who serve as advocates, mentors, and program facilitators, a strong connection between talent management and the institutions’ strategic plans, and a holistic approach to developing talent at all levels of the organizations. In addition, both coaching and opportunities for growth in the work environment were evident within several of the institutions. Also, academic leadership development was considered to be a part of the talent management strategy within three of the colleges and universities. The key differentiators included the incorporation of organizational and leadership competencies to provide focus toward the performance development process at two institutions, the implementation of a succession planning model at another institution, and the location of human resource generalists in departments across two of the institutions to identify learning opportunities for both individuals and work teams. Based on both the findings from the field study and the literature review, a comprehensive procedural model is introduced that serves to support human resource departments and higher education professionals, in general, who are looking to either begin or broaden their own talent management approach. However, despite the progress that has been made across several institutions noted throughout the research study, much more must be learned in terms of how the time and resources invested in talent management translates to institutional success. Advisor: James O‘Hanlon

Joint Computing and Network Resource Scheduling in a Lambda Grid Network

Data-intensive Grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth lightpath is called a Lambda Grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on Lambda Grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a Lambda Grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a Lambda Grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Ecology, stable isotopes, and management of grassland songbirds at National Park Service properties on the Great Plains

Grassland ecosystems have been severely reduced and grassland bird populations have experienced consistent declines. National Park Service (NPS) properties on the Great Plains provide breeding habitat for grassland songbirds, though little is known about the quality of this habitat. A short-term study on songbirds at three NPS properties complemented current monitoring, providing an among park comparison addressing grassland bird productivity and fidelity relative to NPS property size. During 2008-2009, I assessed avian species richness, and estimated bird density and grassland songbird nest success. Bird species richness was greatest at small and medium sites, while number of nesting obligate species was greatest at the large site. Species-specific densities varied among sites, with few grassland obligates occurring at all three sites. Nest success estimates for grassland obligates were highest at the small site and lower at the large site. Another method to quantify habitat quality is assessment of breeding site fidelity. Current extrinsic markers used in monitoring site fidelity are inadequate for small birds; stable isotope analyses provide an alternative. I compared two techniques for assigning stable isotope tissue origin and measured grassland songbird site fidelity. My method of assigning origin provided site-specific variances of expected stable isotope values, an improvement over the most commonly used method. Fidelity tended to be higher at the large site, which may indicate a more robust breeding community of grassland birds. The small size of two of my sites precluded large sample sizes and made strong inferences difficult. To quantify how scientists cope with weak inference, I conducted a literature review. Strong inference was rarely observed, and most authors of weak-inference papers provided specific management recommendations. I suggest that adaptive management is an ideal method to resolve uncertainty from weak inference. Managers should consider my results within the context of regional and global management and the extent to which their unit might aide songbird conservation.