  For many networking applications, recent data is more significant than older
data, motivating the need for sliding window solutions. Various capabilities,
such as DDoS detection and load balancing, require insights about multiple
metrics including Bloom filters, per-flow counting, count distinct and entropy
estimation.
  In this work, we present a unified construction that solves all the above
problems in the sliding window model. Our single solution offers a better space
to accuracy tradeoff than the state-of-the-art for each of these individual
problems! We show this both analytically and by running multiple real Internet
backbone and datacenter packet traces.
