LAUSR

This paper proposes an optimization model to derive a primary and backup resource allocation considering a workload-dependent failure probability to minimize the maximum expected unavailable time (MEUT). The workload-dependent failure probability is a non-decreasing function which reveals the relationship between the workload and the failure probability. The proposed model adopts hot backup and cold backup strategies to provide protection. The cold backup strategy is a protection strategy, in which the requested loads of backup resources are not activated before failures occur to reduce resource utilization with the cost of longer recovery time. The hot backup strategy is a protection strategy, in which the backup resources are activated and synchronized with the primary resources to recover promptly with the cost of higher workload. We formulate the optimization problem as a mixed integer linear programming (MILP) problem. We prove that MEUT of the proposed model is equal to the smaller value between the two MEUTs obtained by applying only hot backup and cold backup strategies with the same total requested load. A heuristic algorithm inspired by the water-filling algorithm is developed with the proved theorem. The numerical results show that the proposed model suppresses MEUT compared with the conventional model which does not consider the workload-dependent failure probability. The developed heuristic algorithm is approximately 105 times faster than the MILP approach with 10−2 performance penalty on MEUT.