גיל אינציגר

Network measurement is an essential building block for a variety of network applications such as traffic engineering, quality of service, load-balancing and intrusion detection. Maintaining a per-flow state is often impractical, and modern systems use complex data structures that are updated by each incoming packet. Thus, a major challenge is designing measurement applications that operate at line speed. This work provides a unified mechanism that improves the update time of a variety of measurement algorithms. We do so by identifying and optimizing a common algorithmic pattern that we call q-MAX. The goal is to maintain the largest q values in a stream of packets. Our algorithm replaces standard data structures such as heaps and skip lists, and accelerate the performance of measurement algorithms.