Another project has been to help the Department of Energy define an optimal schedule in which, because of security concerns, the optimization problem must be solved in a decomposed and distributed manner. We have applied a classical variable splitting and decomposition algorithm, but due to the practical instance we are trying to solve we have had to apply many problem specific heuristics. One major challenge of this project arises from the fact that I have no security clearance and the end user is very concerned about divulging the true nature of the problem to non-secure personnel such as myself. The lack of knowledge about the true nature of the problem has made developing a useful model abstraction and solution algorithm quite challenging. In this particular case, the users are not concerned about the machines that compute the solutions, but rather they are concerned about divulging the constraints making up their problem.
Security is a very important issue.
We have chosen to build our optimization algorithms on top of existing metacomputing toolkits. As such, the security features offered to the owners of machines and the end users are precisely those implemented in these metacomputing tookits. For example, our algorithms will run with the Condor resource management and scheduling software. Condor implements low level operating system constructs guaranteeing that all programs running on a remote machine cannot harm the system. However, our current algorithms offer little in the way of security to the end user.