Datacenter Wide- area Enterprise

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Transcription:

Datacenter Wide- area Enterprise

Client LOAD- BALANCER Can t choose path : ( Servers

Outline and goals A new architecture for distributed load-balancing joint (server, path) selection Demonstrate a nation-wide prototype Interesting preliminary results

OpenFlow Protocol (SSL)

Software Defined Networking Feature Feature Network OS Feature Feature OS Custom Hardware Feature OS Feature Feature OS Custom Hardware Feature Feature OS Feature Custom Hardware Feature Feature Custom Hardware OS Custom Hardware 6

Load Balancing is just Smart Routing

Load-balancing as a network primitive Load- balancing logic Load-balancing Load-balancing Load-balancing Load-balancing decision decision decision decision decision Network OS Custom Hardware Custom Hardware Custom Hardware Custom Hardware Custom Hardware 8

Aster*x Controller

http://www.openflow.org/videos

So far A new architecture for distributed load-balancing joint (server, path) selection Aster*x a nation-wide prototype Promising results that joint (server, path) selection might have great benefits

What next?

How big is the pie? Characterizing and quantifying the performance of joint (server, path) selection

Load- balancing Controller MININET- RT

Load- balancing Controller

Model Clients ISP CDN

Parameters Topology Intra- AS topologies BRITE (2000 topologies) CAIDA (1000 topologies) Rocketfuel (~100 topos.) 20-50 nodes Uniform link capacity

Parameters Servers 5-10 servers Random placement Service Simple HTTP service Serving 1 MB file Additional server- side computation

Parameters Clients 3-5 client locations Random placement Request pattern Poisson process Mean rate: 5-10 req/sec

Load- balancing strategies?

Design space Simple but suboptimal Disjoint- Shortest- Path Disjoint- Traffic- Engineering Complex but optimal Joint

Anatomy of a request-response Client Load- Balancer Server Request Choose Response Time Response 1 st byte Retrieve Response last byte Deliver Last byte ack

Disjoint-Shortest-Path CDN selects the least loaded server Load = retrieve + deliver ISP independently selects the shortest path

Disjoint-Traffic-Engineering CDN selects the least loaded server Load = retrieve + deliver ISP independently selects path to minimize max load Max bandwidth headroom

Joint Single controller jointly selects the best (server, path) pair Total latency = retrieve + estimated deliver

Disjoint-Shortest-Path vs Joint 100 Latency with Shortest-path (sec) 10 1 0.1 0.6 0.7 0.8 0.9 1 Latency with Ideal (sec) Disjoint- Shortest- Path performs ~2x worse than Joint

Disjoint-Traffic-Engg. vs Joint Latency with Disjoint-TE (sec) 1 0.9 0.8 0.7 0.6 0.6 0.7 0.8 0.9 1 Latency with Ideal (sec) Disjoint- Traffic- Engineering performs almost as well as Joint

Is Disjoint truly disjoint? Client Load- Balancer Server Request Choose Response Time Response 1 st byte Retrieve Response last byte Deliver Last byte ack Server response time contains network information

The bottleneck effect A single bottleneck resource along the path determines the performance.

The CDN-ISP game Clients ISP CDN

The CDN-ISP game System load monotonically decreases Both push system in the same direction

Summary of observations Disjoint-SP is ~2x worse than Joint Disjoint-TE performs almost as well as Joint (despite decoupling of server selection and traffic engineering) Game theoretic analysis supports the empirical observation

Questions How should I change the model to mimic a real CDN?

Questions How can I get real data? What network topologies should I use? How should I decide the no. of servers and their location? How should I decide the client request pattern?

Conclusion A new architecture for distributed load-balancing joint (server, path) selection Aster*x - a nation-wide prototype Interesting preliminary results Future Evaluation with real data

Let s chat more!

Sample topologies BRITE CAIDA