  The conventional design of real-time approaches depends heavily on the normal
performance of systems and it often becomes incapacitated in dealing with
catastrophic scenarios effectively. There are several investigations carried
out to effectively tackle large scale catastrophe of a plant and how real-time
systems must reorganize itself to respond optimally to changing scenarios to
reduce catastrophe and aid human intervention. The study presented here is in
this direction and the model accommodates catastrophe generated tasks while it
tries to minimize the total number of deadline miss, by dynamically scheduling
the unusual pattern of tasks. The problem is NP hard. We prove the methods for
an optimal scheduling algorithm. We also derive a model to maintain the
stability of the processes. Moreover, we study the problem of minimizing the
number of processors required for scheduling with a set of periodic and
sporadic hard real time tasks with primary/backup mechanism to achieve fault
tolerance. EDF scheduling algorithms are used on each processor to manage
scenario changes. Finally we present a simulation of super scheduler with
small, medium and large real time tasks pattern for catastrophe management.
