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.

Department of Veterinary and Biomedical Sciences: 2000 Annual Report

Foreword, 2000 John A . Schmitz. Professor and Department Head Veterinary and Biomedical Sciences Personnel Faculty Profiles Teaching program Research program Extension Program Nebraska Veterinary and Diagnostic Laboratory Systems Grants and Contracts Funded or Active in 2000 Patents by VBMS Faculty in 2000 Publications by VBMS Faculty in 2000 Presentations by VBMS Faculty in 2000 Articles Regarding the Department in 2000 Selected Committees, Editorial and Other Appointments of VBMS Faculty Departmental Budget Summaries Nebraska Agricultural Statistics 1999

Department of Veterinary and Biomedical Sciences 2004 Annual Report

Veterinary and Biomedical Sciences Personnel VBMS Teaching Program VBMS Research Program International Activities, 2004 Veterinary Extension Program. 2004 VBMS Grants and Contracts Program. 2004 Refereed Publications by VBMS Faculty in 2004 Department of Veterinary and Biomedical Sciences. Selected Committees, Editorial and Other Appointments. 2004 Articles Regarding the Department in 2004 Departmental Budget Summaries. 2004 Nebraska Agricultural Statistics. 2003/2004