A comparison of receiver-initiated and sender-initiated adaptive load sharing
Performance Evaluation
Approximate Analysis of Fork/Join Synchronization in Parallel Queues
IEEE Transactions on Computers
Numerical methods for stochastic control problems in continuous time
Numerical methods for stochastic control problems in continuous time
A Hybrid Solution of Fork/Join Synchronization in Parallel Queues
IEEE Transactions on Parallel and Distributed Systems
Heavy traffic resource pooling in parallel-server systems
Queueing Systems: Theory and Applications
Analyzing imbalance among homogeneous index servers in a web search system
Information Processing and Management: an International Journal
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In this paper, we consider the approximation of the number of customers of a Poisson-type parallel system of two queues, operating under heavy traffic, by a reflected stochastic differential equation. The type of queueing system here has the so-called fork-join structure. In addition, the model allows for state-dependent (service and arrival) rates. A novelty in our study is that a signal named ''trigger'' is considered. These signals are used to move a customer from one queue to the other. This, in turn, can be used to reduce the imbalance (and as a consequence, the system response time) which appears in certain parallel systems. The results here are applied to a web search system, which is a relevant example of a parallel system which operates under heavy traffic and suffers from imbalance among servers. A stochastic optimal control problem is formulated in order to find the best routing policy of signals which reduces the imbalance. The optimal control was tested in a simulation, indicating significant reduction in system response time when compared to the uncontrolled system.