SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
On choosing a task assignment policy for a distributed server system
Journal of Parallel and Distributed Computing - Special issue on software support for distributed computing
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Asymptotic convergence of scheduling policies with respect to slowdown
Performance Evaluation
Optimal Load Balancing on Distributed Homogeneous Unreliable Processors
Operations Research
Cycle stealing under immediate dispatch task assignment
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
Analysis of Task Assignment with Cycle Stealing under Central Queue
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Optimal state-free, size-aware dispatching for heterogeneous M/G/-type systems
Performance Evaluation - Performance 2005
Surprising results on task assignment in server farms with high-variability workloads
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
M/M/1-PS queue and size-aware task assignment
Performance Evaluation
Minimizing slowdown in heterogeneous size-aware dispatching systems
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Markov decision algorithms for dynamic routing [telephone networks]
IEEE Communications Magazine
Understanding the marginal impact of customer flexibility
Queueing Systems: Theory and Applications
Performance Modeling and Design of Computer Systems: Queueing Theory in Action
Performance Modeling and Design of Computer Systems: Queueing Theory in Action
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Applying the first policy iteration (FPI) to any static dispatching (task assignment) policy yields a new improved dynamic policy that takes into account the particular cost structure and the expected future arrivals. However, it is generally hard to go beyond that due to the complex state space and the resulting difficulty in computing the value function for a dynamic policy. For example, applying FPI to identical FCFS servers with Bernoulli split gives the Least-Work-Left (LWL) policy, for which no closed-form value function is known. In fact, LWL with identical servers is equivalent to an M/G/k queue, the performance measures of which have remained as open problems. The situation gets even more complicated with heterogeneous servers. In this paper, we take an intermediate approach and consider lookahead actions that concern not only the current job but also the job arriving next, after which a basic (static) policy is assumed to take over. This is important as the benefits from some decisions can only be reaped with appropriate subsequent actions. The lookahead enables sound estimates also for marginal admission costs, e.g., with respect to LWL. The superior performance of the new near-optimal dispatching policies is demonstrated numerically.