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Existing in-network heavy-hitter detection algorithms suffer from several shortcomings. On the one hand, most of the algorithms perform monitoring in intervals and reset the data structures in between; consequently, a notable amount of heavy hitters (HH) spanning across the intervals go undetected. On the other hand, the algorithms consume substantial hardware resources, potentially hindering other data plane functionalities to be integrated on the same device.In this work, we revisit the state-of-the-art in-network approaches in this regard and identify that they fall short in over-coming the aforementioned issues. In particular, we investigate whether it is possible to design a heavy-hitter detection algorithm that provides high accuracy without consuming substantial re-sources, thereby making it feasible to integrate with concurrent applications. To this end, we propose dSketch, a time-decaying algorithm for in …