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When a Data Stream Management System (DSMS) becomes overloaded and fails to satisfy all kinds of requirements, such as tuple latency and result precision because the arrival rates are bursty. Especially, real-time queries have to be completed within certain deadlines for results to be full of value. Semantic load shedding is an effective approach to alleviate workload. A semantic load shedding algorithm based on priority table is presented which considers about execution costs and values of tuples at the same time when deciding which tuples are dropped in this paper. Experiment results show that this algorithm has better performance and flexibility to handle workload fluctuations gracefully.