Jellyfish: Networking Data Centers Randomly

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Presentation transcript:

Jellyfish: Networking Data Centers Randomly Ankit Singla† , Chi-Yao Hong†, Lucian Popa*, P. Brighten Godfrey† † University of Illinois at Urbana–Champaign *HP Labs Oversubscription

Tow Goals of Data Center Design High throughput Incremental expansion Easily add/replace servers & switches Throughput: the amount of data exchanged/processed within a unit time Good scalalibity.Easily add/replace servers and switches

Incremental expansion Facebook doubled their data center scale in the last year (2010) You can add the servers, how about the network? Distributed systems: Hadoop Why it matters. Map-reduce heavlity rely on the networks

Today’s structured networks CLOS Three-stage hierarchical datacenter. Single failure Fat tree CLOS Fat tree

Structure constrains expansion 3-level fat trees, commodity switches: 24-port switches – 3,456 servers 32-port switches – 8,192 servers 48-port switches – 27,648 servers How to expand a datacenter with 32-port switches, 8,192 servers to 10,000 servers?

Solution No structure Jellyfish: random graph

Quantifying expandability Bisection bandwidth if the network is bisected into two partitions, the bisection bandwidth of a network topology is the bandwidth available between the two partitions.

Throughput: Jellyfish vs Fat tree Give the same budget for network devices, jellyfish can sustain 25% more servers than fattree

Why it works? It fully utilizes all available capacity

Example

Example: Fat tree

Example: Jellyfish

Jellyfish has short paths

Degree-diameter bounded graph Degree: the degree of a node is the number of nodes connected to this node. Diameter: the longest distance between a node pair Indicates the optimal case

Degree-diameter vs. Jellyfish

Routing and congestion control K-shortest path MPLS TE, OpenFlow(SDN) Congestion control TCP, Multipath TCP Routing is important. Not a structured topology, need more time to lookup the routing table. MPLS - pre-compute the path. OpenFlow - (SDN)

Cabling One of the main drawbacks of this work Discussion: possible solutions wireless datacenter Xia Zhou, et.al.. "Mirror mirror on the ceiling: Flexible wireless links for data centers." ACM SIGCOMM Computer Communication Review 42, no. 4 (2012): 443-454. Daniel Halperin, et.al.. "Augmenting data center networks with multi-gigabit wireless links." In ACM SIGCOMM Computer Communication Review, vol. 41, no. 4, pp. 38-49. ACM, 2011. Not work Large latency for small flows Short transmission range

Questions on Piazza Is the fat-tree topology the most widely used data center network topology? Why weren’t other network topologies as heavily emphasized in the paper? Are there any theoretical tradeoffs to Jellyfish since the physical and routing complications seemed to be mostly resolved with the author’s proposals?