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.

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.

Hydrogeology, Chemical Characteristics, and Transport Processes in the Zone of Contribution of a Public-Supply Well in York, Nebraska

In 2001, the U.S. Geological Survey, as part of the National Water Quality Assessment (NAWQA) Program, initiated a topical study of Transport of Anthropogenic and Natural Contaminants (TANC) to PSW (public-supply wells). Local-scale and regional-scale TANC study areas were delineated within selected NAWQA study units for intensive study of processes effecting transport of contaminants to PSWs. This report describes results from a local-scale TANC study area at York, Nebraska, within the High Plains aquifer, including the hydrogeology and geochemistry of a 108-square-kilometer study area that contains the zone of contribution to a PSW selected for study (study PSW), and describes factors controlling the transport of selected anthropogenic and natural contaminants to PSWs.

Situational and Driver Characteristics Associated With Deervehicle Collisions in Southeastern Michigan

Deer-vehicle collisions (DVCs) create societal impacts throughout the range of white-tailed deer (Odocoileus virginanus). In Michigan reported DVCs increased by nearly 60% between 1992-2003, with current estimates at more than 65,000 DVCs per year and a mean of $2,300 vehicle damage. To better understand where to direct education and information programs, we used Office of Highway Safety Planning (OHSP) data, 2001-2003, to profile driver characteristics and accident situations of DVCs in Washtenaw, Oakland, and Monroe Counties in Michigan. Each county varies in intensity of land use, human and deer densities, and available deer habitat. Deer density in Washtenaw, Oakland, and Monroe Counties was 49.5, 21.9 and 8.9 per mi2, respectively, and the annual rate of DVCs in these counties was 5.3, 2.6 and 1.8 per 1,000 licensed drivers. Drivers are at particular risk of being involved in DVCs between 6pm- 6am, which includes dawn and dusk commuting hours, and night. Single lane roads and roads with higher posted speed limits provided greater risk to drivers of involvement in a DVC. Middle-aged drivers, particularly males, were at increased risk deer-related collisions. Results from this study will be combined with survey research to determine how best to educate drivers about risk factors that make occurrence of a DVC more likely.