# ICE Buckets: Improved Counter Estimation for Network Measurement

arXiv: https://arxiv.org/abs/1606.01364 · HTML: https://mlsanity.com/paper/1606.01364/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jun 2016.

## Built on by (most cited first, 1 of 1)

- [DynamiQ: Accelerating Gradient Synchronization using Compressed Multi-hop All-reduce](https://mlsanity.com/paper/2602.08923/) (2026)

## Abstract (arXiv)

Measurement capabilities are essential for a variety of network applications, such as load balancing, routing, fairness and intrusion detection. These capabilities require large counter arrays in order to monitor the traffic of all network flows. While commodity SRAM memories are capable of operating at line speed, they are too small to accommodate large counter arrays. Previous works suggested estimators, which trade precision for reduced space. However, in order to accurately estimate the largest counter, these methods compromise the accuracy of the smaller counters. In this work, we present a closed form representation of the optimal estimation function. We then introduce Independent Counter Estimation Buckets (ICE-Buckets), a novel algorithm that improves estimation accuracy for all counters. This is achieved by separating the flows to buckets and configuring the optimal estimation function according to each bucket's counter scale. We prove a tighter upper bound on the relative error and demonstrate an accuracy improvement of up to 57 times on real Internet packet traces.