Jennifer Rexford Princeton University MW 11:00am-12:20pm Data-Center Traffic Management COS 597E: Software Defined Networking.

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Presentation transcript:

Jennifer Rexford Princeton University MW 11:00am-12:20pm Data-Center Traffic Management COS 597E: Software Defined Networking

Cloud Computing 2

Elastic resources – Expand and contract resources – Pay-per-use – Infrastructure on demand Multi-tenancy – Multiple independent users – Security and resource isolation – Amortize the cost of the (shared) infrastructure Flexible service management 3

Cloud Service Models Software as a Service – Provider licenses applications to users as a service – E.g., customer relationship management, , … – Avoid costs of installation, maintenance, patches… Platform as a Service – Provider offers platform for building applications – E.g., Google’s App-Engine – Avoid worrying about scalability of platform 4

Cloud Service Models Infrastructure as a Service – Provider offers raw computing, storage, and network – E.g., Amazon’s Elastic Computing Cloud (EC2) – Avoid buying servers and estimating resource needs 5

Enabling Technology: Virtualization Multiple virtual machines on one physical machine Applications run unmodified as on real machine VM can migrate from one computer to another 6

Multi-Tier Applications Applications consist of tasks – Many separate components – Running on different machines Commodity computers – Many general-purpose computers – Not one big mainframe – Easier scaling

Multi-Tier Applications 8 Front end Server Aggregator … Aggregator Worker … …

Data Center Network 9

Virtual Switch in Server 10

Top-of-Rack Architecture Rack of servers – Commodity servers – And top-of-rack switch Modular design – Preconfigured racks – Power, network, and storage cabling 11

Aggregate to the Next Level 12

Modularity, Modularity, Modularity Containers Many containers 13

Data Center Network Topology 14 CR AR... S S S S Internet S S S S A A A A A A … S S S S A A A A A A …... Key CR = Core Router AR = Access Router S = Ethernet Switch A = Rack of app. servers ~ 1,000 servers/pod

Capacity Mismatch 15 CR AR S S S S S S S S A A A A A A … S S S S A A A A A A …... S S S S S S S S A A A A A A … S S S S A A A A A A … ~ 5:1 ~ 40:1 ~ 200:1

Data-Center Routing 16 CR AR... S S S S DC-Layer 3 Internet S S S S A A A A A A … S S S S A A A A A A …... DC-Layer 2 Key CR = Core Router (L3) AR = Access Router (L3) S = Ethernet Switch (L2) A = Rack of app. servers ~ 1,000 servers/pod == IP subnet SSSS SS

Traffic Management Hedera and HONE 17

Traffic Management Challenges High volumes of “east-west traffic” Low bisection bandwidth Volatile traffic patterns Elephant flows TCP incast Naïve application programmers Performance problems due to stragglers Difficulty of collecting measurement data 18

Traffic Management Opportunities Low latencies within the data center –Small TCP round-trip times –Easier to use central controller End-to-end control –Applications, servers, and switches Greater visibility –Monitoring on the end hosts and soft switches Green-field deployments VM placement and migration Simple, symmetric topologies 19

Discussion Granularity of monitoring and control –Individual flows? –Larger traffic aggregates? End host vs. network –Where to measure? –Where to exercise control? Integrating end hosts with the controller 20