Controller

1. Software Defined Measurement for Data Centers Masoud Moshref, Minlan Yu, Ramesh Govindan Motivation Software Defined Measurement • Management policies such as • Traffic engineering • Accounting • Troubleshooting • Need measurements in • Different time-scales • Multiple granularities of flows • Single/Multiple switches • Can we encapsulate the measurement tasks in a controller module? • Select the right primitive at switches • Counters in OpenFlow rules • Sketches in hash-based switches • Sampling (NetFlow, sFlow) • Programmable switches • Based on • Traffic properties (stability) • Measurement task properties • Time-scale • Local/Global view • Use resources efficiently based on • Resource/Accuracy tradeoff Controller TE Accounting SDM Configure resources Fetch statistics Hierarchical Heavy Hitters • Definition: • The longest IP prefixes • That contribute a large amount of traffic (>threshold) • After excluding any HHH descendants in prefix tree • For traffic engineering, accounting, anomaly detection Hierarchical heavy hitter Heavy hitter Flow-based Switches Hash-based Switches • For variable traffic and large time-scale • At switches: sketches: • Multiple hash functions • SRAM counters • Hierarchical Count-Min sketch • At controller: restricted resource allocation • For slowly-varying traffic and large time-scale • At switches: Uses TCAM entries • At controller:pick which prefixes to monitor, given a limit on the number of counters • Max-Cover algorithm • Split the prefix with maximum traffic • Merge siblings with total minimum traffic • Stop if no sibling with traffic < maximum prefix packet H1 H2 H3 H4 w d Programmable Switches Discussion • Because of large control traffic at small time-scales • Give more responsibilities to the switches • The right division of labor between the controller and switches? • Find heavy hitters for each IP prefix length at switches using • Sketches (Count-Min sketch) • Counting algorithms (Space Saving) • How to do a global task? • Multiple switches • Distribute labor on the path of flows • Compose measured data at the controller • Multiple tasks • Distribute resources among tasks • Use joint information to save resources • Multiple time-scales • New primitives for programmable switches • Heap for Space Saving counting algorithm Resource/Accuracy Tradeoff for Flow-based vs Hash-based Switches • Flow-based: Max-Cover • Hash-based: Count-Min sketch • Equal switch resource cost • TCAM  80*SRAM • 80x less bandwidth for flow-based • 2x accuracy for sketch-based for small threshold