3,785 research outputs found
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
Endpoint-transparent Multipath Transport with Software-defined Networks
Multipath forwarding consists of using multiple paths simultaneously to
transport data over the network. While most such techniques require endpoint
modifications, we investigate how multipath forwarding can be done inside the
network, transparently to endpoint hosts. With such a network-centric approach,
packet reordering becomes a critical issue as it may cause critical performance
degradation.
We present a Software Defined Network architecture which automatically sets
up multipath forwarding, including solutions for reordering and performance
improvement, both at the sending side through multipath scheduling algorithms,
and the receiver side, by resequencing out-of-order packets in a dedicated
in-network buffer.
We implemented a prototype with commonly available technology and evaluated
it in both emulated and real networks. Our results show consistent throughput
improvements, thanks to the use of aggregated path capacity. We give
comparisons to Multipath TCP, where we show our approach can achieve a similar
performance while offering the advantage of endpoint transparency
Space Shuffle: A Scalable, Flexible, and High-Bandwidth Data Center Network
Data center applications require the network to be scalable and
bandwidth-rich. Current data center network architectures often use rigid
topologies to increase network bandwidth. A major limitation is that they can
hardly support incremental network growth. Recent work proposes to use random
interconnects to provide growth flexibility. However routing on a random
topology suffers from control and data plane scalability problems, because
routing decisions require global information and forwarding state cannot be
aggregated. In this paper we design a novel flexible data center network
architecture, Space Shuffle (S2), which applies greedy routing on multiple ring
spaces to achieve high-throughput, scalability, and flexibility. The proposed
greedy routing protocol of S2 effectively exploits the path diversity of
densely connected topologies and enables key-based routing. Extensive
experimental studies show that S2 provides high bisectional bandwidth and
throughput, near-optimal routing path lengths, extremely small forwarding
state, fairness among concurrent data flows, and resiliency to network
failures
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