Name
Abstract | ||
|---|---|---|
We present Taiji, a new system for managing user traffic for large-scale Internet services that accomplishes two goals: 1) balancing the utilization of data centers and 2) minimizing network latency of user requests.
Taiji models edge-to-datacenter traffic routing as an assignment problem---assigning traffic objects at the edge to the data centers to satisfy service-level objectives. Taiji uses a constraint optimization solver to generate an optimal routing table that specifies the fractions of traffic each edge node will distribute to different data centers. Taiji continuously adjusts the routing table to accommodate the dynamics of user traffic and failure events that reduce capacity.
Taiji leverages connections among users to selectively route traffic of highly-connected users to the same data centers based on fractions in the routing table. This routing strategy, which we term connection-aware routing, allows us to reduce query load on our backend storage by 17%.
Taiji has been used in production at Facebook for more than four years and routes global traffic in a user-aware manner for several large-scale product services across dozens of edge nodes and data centers.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3341301.3359655 | Proceedings of the 27th ACM Symposium on Operating Systems Principles |
Field | DocType | ISBN |
Edge node,Computer science,Latency (engineering),Traffic routing,Solver,Routing table,Constrained optimization,The Internet,Distributed computing | Conference | 978-1-4503-6873-5 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
12 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Chou | 1 | 16 | 1.69 |
| Tianyin Xu | 2 | 419 | 32.99 |
| Kaushik Veeraraghavan | 3 | 372 | 20.81 |
| Andrew Newell | 4 | 1 | 0.69 |
| Sonia Margulis | 5 | 14 | 1.30 |
| Lin Xiao | 6 | 1 | 0.35 |
| Pol Mauri Ruiz | 7 | 1 | 0.35 |
| Justin Meza | 8 | 419 | 18.08 |
| Kiryong Ha | 9 | 1 | 0.35 |
| Shruti Padmanabha | 10 | 2 | 0.69 |
| Kevin Cole | 11 | 1 | 0.35 |
| Dmitri Perelman | 12 | 120 | 7.40 |