Abstract
Representing traffic with sketch data structures to provide flow statistics is a fundamental strategy in network measurement. In the current double-stack circumstance, we observe that IPv4 and IPv6 flows are inequivalent in terms of both flow cardinality and flow size in Internet. The existing sketches, however, represent IPv4 and IPv6 flows with no differentiation. As a consequence, the IPv4 flows, which can be massive and large, while the IPv6 flows, which are usually handful and small. Such an unbalance or asymmetry feature may lead to unnecessary hash collision errors, especially for IPv6 flows. To this end, in this letter, we present D-Sketch, a new sketch optimization strategy to represent IP flows. At its core, D-Sketch differentiates IPv4 flows from IPv6 ones, thereafter represents them with isolated sketches whose capacities are proportional to the corresponding flow cardinality. Given the same space overhead, trace-driven evaluations further commit that D-Sketch decreases the ARE of per-flow measurement up to 52.5%, with an average of 24.0%, compared with the existing one-sketch and large-small strategies.
Highlights
N ETWORK traffic measurement provides basic information about the amount and type of flows for network management, security analysis, and beyond
To obtain the synthetic datasets, we retype the flow size randomly. With both real-world and synthetic datasets, the experiments are sufficient to reveal the impact of flow size distribution upon D-Sketch performance
Because D-Sketch only needs a small portion of packets to estimate the cardinality of IPv4 and IPv6 flows and performs an additional operation with a constant overhead to classify different kinds of flows, we just evaluate the accuracy of D-Sketch in terms of average relative error (ARE), and Decrease of ARE (DOA) (%)
Summary
N ETWORK traffic measurement provides basic information about the amount and type of flows for network management, security analysis, and beyond. Since the birth of IPv6, the Internet had been a double-stack network wherein both IPv4 and IPv6 are implemented. IPv4 and IPv6 flow coexist in the counter arrays These flows interfere with each other due to the potential hash collisions. Based on the above observation, in this letter, we propose D-Sketch, a differentiated sketch strategy for double-stack networks. D-Sketch differentiates IPv4 flows from IPv6 flows and represents them with separated sketches With such a design, D-Sketch confines the hash collisions inner a sketch and avoids interference between different types of flows. An adaptive space allocation scheme is enabled by introducing an additional sampling mechanism into D-Sketch To our knowledge, this is the first work, which takes the initial step to explore how to improve the accuracy.
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