Spotlight: Scalable Transport Layer Load Balancing for Data Center
Networks
release_nbnxlwc45rgovaj4ftehg6jsle
by
Ashkan Aghdai, Cing-Yu Chu, Yang Xu, David H. Dai, Jun Xu, H. Jonathan
Chao
2018
Abstract
Load Balancing plays a vital role in modern data centers to distribute
traffic among instances of network functions or services. State-of-the-art load
balancers such as Silkroad dispatch traffic obliviously without considering the
real-time utilization of service instances and therefore can lead to uneven
load distribution and suboptimal performance.
In this paper, we design and implement Spotlight, a scalable and distributed
load balancing architecture that maintains connection-to-instance mapping
consistency at the edge of data center networks. Spotlight uses a new stateful
flow dispatcher which periodically polls instances' load and dispatches
incoming connections to instances in proportion to their available capacity.
Our design utilizes distributed control plane and in-band flow dispatching and
thus scales horizontally in data center networks. Through extensive flow-level
simulation and packet-level experiments on a testbed, we demonstrate that
compared to existing methods Spotlight distributes the traffic more efficiently
and has near-optimum performance in terms of overall service utilization.
Moreover, Spotlight is not sensitive to utilization polling interval and
therefore can be implemented with low polling frequency to reduce the amount of
control traffic. Indeed, Spotlight achieves the mentioned performance
improvements using O(100ms) polling interval.
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