Abstract
In asynchronous event systems, the production of an event is decoupled from its consumption via an event queue. The loose coupling of such systems allows great flexibility as to where and when within the system the event handler of a given event is actually executed, allowing them to scale with increasing number of processors on a given node or across multiple nodes in a distributed system. Although this flexibility is useful in heterogeneous distributed systems, such as SOA, it may appear not to be well suited for real-time systems, which require an upper bound on how long an event can remain unhandled in a queue. However, we show how the weighted fair scheduling algorithms developed for QoS (quality of service) routing can be adapted to event queues to bound the delay between production and consumption. We achieve this, despite the fact that the underlying execution environment is only weakly controlled, through the use of predictive techniques on a calibrated model of the event system. Our choice of algorithms and data structures is driven in part by the highly concurrent nature of the system. We show how a weighted fair scheduler can be built on a lock-free concurrent priority queue. We analyze the performance of various such queues proposed in the literature and show that a very simple linear quantizing queue yields the best performance.
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