Tuning qod in stream processing engines

Quality of Service (QoS) and Quality of Data (QoD) are the two major dimensions for evaluating any query processing system. In the context of data stream management systems (DSMSs), multi-query scheduling has been exploited to improve QoS. In this paper, we are proposing to exploit query scheduling to improve QoD in DSMSs. Specifically, we are present-ing a new policy for scheduling multiple continuous queries with the objective of maximizing the freshness of the output data streams and hence the QoD of such outputs. The proposed Freshness-Aware Schedul-ing of Multiple Continuous Queries (FAS-MCQ) pol-icy decides the execution order of continuous queries based on each query's properties (i.e., cost and se-lectivity) as well the properties of the input update streams (i.e., variability of updates). Our experimen-tal results have shown that FAS-MCQ can improve QoD by up to 50% compared to existing scheduling policies used in DSMSs. Finally, we propose and eval-uate a parametrized version of our FAS-MCQ sched-uler that is able to balance the trade-off between freshness and response time according to the appli-cation's requirements.