Small-World Datacenters
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1 2 nd ACM Symposium on Cloud Computing Oct 27, 2011 Small-World Datacenters Ji-Yong Shin * Bernard Wong +, and Emin Gün Sirer * * Cornell University + University of Waterloo
2 Motivation Conventional networks are hierarchical Higher layers become bottlenecks Non-traditional datacenter networks are emerging Fat Tree, VL2, DCell and BCube Highly structured or sophisticated regular connections Redesign of network protocols CamCube (3D Torus) High bandwidth and APIs exposing network architecture Large network hops
3 Small-World Datacenters Regular + random connections Based on a simple underlying grid Achieves low network diameter Enables content routing Characteristics High bandwidth Fault tolerant Scalable
4 Small-World Networks Watts and Strogatz Multiple connections to neighbors on a ring + random connections Kleinberg Lattice + random links Probability of connecting a random pair decreases with dth power of distance between the pair in d-dimensional network Path length becomes O(log n) Watts and Strogatz 98 Kleinberg 00
5 Small-World Datacenter Design Possible topologies for 6 links per node Small World Ring (2 reg + 4 rand) Small World 2D Torus (4 reg + 2 rand) Small World 3D Hexagon Torus (5 reg + 1 rand) Direct connections from server to server No need for switches Software routing approach
6 Routing in Small-World Datacenters Shortest path Link state protocol (OSPF) Expensive due to TCAM cost Greedy geographical Find min distance neighbor Coordinates in lattice used as ID Maintain info of 3 hop neighbors Comparable to shortest path for 3DHexTorus
7 Content Routing in Small-Worlds Content routing Logical coordinate space and network to map data Logical and physical network do not necessarily match Geographical identity + simple regular network in SWDC Logical topology can be mapped physically Random links only accelerates routing SWDC can support DHT and key value stores directly Similar to CamCube
8 Packaging and Scaling SWDCs can be constructed from preconfigured, reusable, scalable components Reusable racks Regular links: only short cables necessary Random links: Predefined Blueprint Random number generator * Pre-cut wires based on known probability Ease of construction Connect rack-> cluster (or container) -> datacenter Switches, repeaters, or direct wires for inter-cluster connections *Image from
9 Evaluation Setup Simulation of 10,240 nodes in three settings: Small-World Datacenters (SWDC) CamCube SW Ring SW 2DTorus SW 3DHexagonal Torus CamCube 6 x 1GigE links per server Greedy routing NetFPGA Setup 64B packet 4.6 us 1KB packet 15 us Conventional hierarchical data centers (CDC) 1 x 1GigE link per server 10 GigE links among switches 3 layer switches (Uniform delays: 6us, 3.2 us, and 5us in each layer) Oversubscriptions: 5 and 10
10 Latency (us) Latency (us) Evaluation: Average Packet Latency Average Packet Latency: Uniform Random SW Ring SW 2DTorus SW 3DHexTorus 64B Packet Size 1KB Average Packet Latency: MapReduce SWDCs always outperform CamCube SWDCs can outperform CDC for MapReduce SWDC has multiple ports SWDC latencies are packet size dependent Limitations of software routers 64B Packet Size 1KB
11 Bandwidth (GBps) Bandwidth (GBps) Evaluation: Aggregate Bandwidth Aggregate Bandwidth: Uniform Random SW Ring SW 2DTorus SW 3DHexTorus 64B Packet Size 1KB Aggregate Bandwidth: MapReduce SWDCs outperform CamCube in general 1.5x - 3x better SWDCs outperform CDCs in general 1x - 16x better 64B Packet Size 1KB
12 Percentage of preserved connectivity Evaluation: Fault Tolerance Connectivity under random rack failure SW Ring SW 2DTorus SW 3DHexTorus CamCube Percentage of failed racks No switches to fail compared to CDCs Random links enable stronger connections
13 Related Concurrent Work Scafida and Jellyfish Rely on random connections Achieve high bandwidth Comparison to SWDC SWDCs have more regular links Routing can be simpler
14 Summary Unorthodox topology comprising a mix of regular and random links can yield: High performance Fault tolerant Easy to construct and scalable Issues of cost at scale, routing around failures, multipath routing, etc. are discussed in the paper
15 Path Length Extra: Path Length Comparison Average Path Length (10240 nodes, Errorbar = stddev) Shortest Greedy SW Ring SW 2DTorus SW 3DHexTorus CamCube
16 Extra: Load balance
17 Extra: Need for Hardware
18 Average Path Length Extra: Path Length Under Failure Shortest path length under random node failure SW Ring SW 2DTorus SW 3DHexTorus CamCube Percentage of failed nodes
19 Percentage of preserved path Extra: Fault Tolerance (node failure) Connectivity among live nodes under random correlated failure SW Ring SW 2DTorus SW 3DHexTorus CamCube Percentage of failed nodes No switches to fail compared to CDCs Random links enable stronger connections
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