SCHEDULING ISSUES IN SURVIVABILITY APPLICATIONS USING HYBRID FAULT MODELS.

This research addresses scheduling issues in networked computer systems with survivability requirements, i.e. systems in which essential services must survive malicious acts. In order to achieve survivability based on spatial redundancy, agreement algorithms are needed as a mechanism to consolidate results of individual replicas. The potentially enormous overhead associated with communication and voting schemes of the algorithms put unique burdens on the scheduler as the efficiency of scheduling determines the suitability of the agreement algorithm. This paper derives agreement task graphs, representing computations, and inter-process communication based on phantom tasks. Task graph primitives are identified and it is shown how their scheduling directly influences the performance of the agreement algorithm. Finally, the notion of dynamic k-of-N precedence is introduced and its impact on resource reclaiming for early stopping algorithms is discussed. [ABSTRACT FROM AUTHOR]