HSS: A Memory-Efficient, Accurate, and Fast Network Measurement Framework in Sliding Windows - Hang, Zijun; Wang, Yongjie; Lu, Yuliang (IEEE eTransactions on network and service management, 2024)
Network measurement is indispensable to network management. This paper focuses on three fundamental network measurement tasks: membership query, frequency query, and heavy hitter query. Existing solutions, such as sketches, sliding window algorithms, and the Sliding Sketch framework, struggle to simultaneously achieve memory efficiency, accuracy, real-time operation, and generic application. Accordingly, this paper proposes the Half Sliding Sketch (HSS), an improvement over the state-of-the-art Sliding Sketch framework. The HSS framework is applied to five contemporary sketches for the three aforementioned query tasks. Theoretical analysis reveals that our framework is faster, more memory-efficient and more accurate than the state-of-the-art Sliding Sketch while still being generic. Extensive experimental results reveal that HSS significantly enhances the accuracy for the three query tasks, achieving improvements of 2× to 28.7× , 1.5× to 9× , and 2.4× to 3.6× , respectively. Moreover, in terms of speed, HSS is 1.2× to 1.5× faster than the Sliding Sketch.