Heuristic Approach to Distributed Server Allocation with Preventive Start-Time Optimization against Server Failure

Abstract

This paper proposes a heuristic approach for distributed server allocation with preventive start-time optimization against a single server failure. Server allocation is decided beforehand under each failure pattern to minimize the largest maximum delay among all failure patterns. The Previous work formulated the model as an an integer linear programming (ILP) problem. As the number of users and that of severs increase, the size of ILP problem increases; the computation time to solve the ILP problem becomes large. The proposed heuristic approach adopts both simulated annealing and ILP approach in a hybrid manner. The numerical results reveal that the proposed approach reduces computation time by 26% compared with the ILP approach with increasing the largest maximum delay by 3.4% in average. It reduces the largest maximum delay compared with the start-time optimization model; it avoids instability caused by the unnecessary disconnection, which occurs in the run-time optimization model.