Jennie Palmer

Optimal and heuristic policies for dynamic server allocation

We examine a system where the servers in a cluster may be switched dynamically and preemptively from one kind of work to another. The demand consists of M job types joining separate queues, with different arrival and service characteristics, and also different relative importance represented by appropriate holding costs. The switching of a server from queue i to queue j incurs a cost which may be monetary or may involve a period of unavailability. The optimal switching policy is obtained numerically by solving a dynamic programming equation. Two simple heuristic policies-one static and one dynamic-are evaluated by simulation and are compared to the optimal policy. The dynamic heuristic is shown to perform well over a range of parameters, including changes in demand.

Optimal Server Allocation in Reconfigurable Clusters with Multiple Job Types

We examine a system where the servers in a cluster may be switched dynamically and preemptively from one kind of work to another. The demand consists of M job types joining separate queues, with different arrival and service characteristics, and also different relative importance represented by appropriate holding costs. The switching of a server from queue i to queue j incurs a cost which may be monetary or may involve a period of unavailability. The optimal switching policy is obtained numerically by solving a dynamic programming equation. Two simple heuristic policies – one static and one dynamic – are evaluated by simulation and are compared to the optimal policy. The dynamic heuristic is shown to perform well over a range of parameters, including changes in demand.

Dynamic Allocation of Servers in a Grid Hosting Environment

A grid hosting environment is described, where servers may be reconfigured dynamically from one type of work to another in response to changes in demand. The problem of carrying out these reconfigurations in the most efficient manner is addressed by means of stochastic modelling and optimization. A heuristic policy, which is close to optimal over a wide range of parameters, is introduced. A prototype system based on existing resource management software has been developed to demonstrate the concepts described

Optimal tree structures for large service networks

We consider the problem of how best to structure and control a distributed computer system containing many processors. The performance trade-offs associated with different tree structures are evaluated approximately by applying appropriate queueing models. It is shown that, for a given set of parameters and job distribution policy, there is an optimal tree structure that minimizes the overall average response time. This is obtained numerically through comparison of average response times. A simple heuristic policy is shown to perform well under certain conditions.