FutureGrid Project Challenge: A CLOUD COMPUTING ARCHITECTURE FOR SUPPLY CHAIN NETWORK SIMULATION

Project Information

Discipline

Industrial/Manufacturing Engineering (108) 

Subdiscipline

14.17 Industrial/Manufacturing Engineering 

Orientation

Research 

Large-scale supply chains usually consist of thousands of stock keep units (SKUs) stocked at different locations within the supply chain. The simulation of large-scale multi-echelon supply chain networks is very time consuming. The purpose of this project is to design a cloud computing architecture to facilitate the computational performance of large scale supply chain network simulations. A Cloud Computing Architecture For Supply Chain Network Simulation (CCAFSCNS) will be designed in this project, and a prototype system will be developed using the computing resources in the FutureGrid. The simulations are essentially compute-intensive Monte-Carlo experiments requiring multiple replications. Replications are distributed across virtual machines within CCAFSCNS. One expected result is to show that the cloud computing solution can significantly shorten the simulation time.

This research will develop a Cloud Computing Architecture For Supply Chain Network Simulation (CCAFSCNS). This architecture will provide a blueprint to develop cloud computing solutions. In addition, this project will provide a way to compare the time to simulate on the local computer and the time spent on cloud computing solution. The impacts of the large scale data will also be considered to simulate large scale supply chain networks.

A Cloud Computing Architecture For Supply Chain Network Simulation (CCAFSCNS) is developed in this project and can be used as a blueprint to develop cloud computing solutions. A prototype system that implements the CCAFSCNS will be developed to simulate the supply chain networks in the cloud. Companies will be able to use the results to develop better systems and software products that rely on cloud computing for applications.

Project Contact

Project Lead

Yaohua Chen (chen) 

Project Manager

Yaohua Chen (chen) 

Resource Requirements

Hardware System

• alamo (Dell optiplex at TACC)

 

The Condor technology is used in this project to manage the computing resources. The VMs of Condor Server, Condor Worker and Condor Client are created based on the Grid Appliance. The Nimbus cloud client is used to start up Condor Worker VMs in the Alamo Network, and these VMs serve as the computing resources for this project. A Java-based web service, which is deployed in the Condor Client, will be available to receive the input file from the user through a web page. After receiving the input file from the user, the web service will generate the Condor job description file based on the input file. The web service sends the input file and the Condor job description file to the Condor Server, and the Condor Server schedules these jobs to be run on the Condor Worker VMs in the Alamo Network. When a job is completed on the Condor Worker, the simulation result will be sent back to the web service. After all the jobs are completed, the web service will package the generated files and notify the user through email.

Fifteen VMs will be needed for short durations (around 6 hours) in order to establish feasibility of prototype and be available for testing.

Project Timeline

Submitted

05/17/2012 - 12:51