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

Towards Efficient, Work-Conserving, and Fair Bandwidth Guarantee in Cloud Datacenters

Bandwidth guarantee is a critical feature to enable performance predictability in cloud datacenters. This process is expected to achieve three requirements: work conservation, fairness, and simplicity. However, the distributed nature of datacenters raises significant challenges to attaining those requirements at the same time. In this paper, we propose an efficient approach that can satisfy the three requirements simultaneously. Our scheme takes advantage of multipath TCP (MPTCP) to generate explicit bandwidth guarantee (BG) traffic and work conservation (WC) traffic.We further prioritize the BG traffic over the WC traffic in the network fabric. Due to the priority setting, WC cannot harm bandwidth guarantees and thus is effectively supported. We show that the MPTCP fits this direction well but presents some new issues when the WC subfows own a low priority. We thus adapt the MPTCP to handle these issues through a customized scheduler (which strictly prioritizes BG subfow during packet scheduling) and adopting a large receive buffer. In addition, we enable tenants to share unused bandwidth fairly by managing the overall aggressiveness of the WC traffic. The proposed system can be easily implemented with commercial off-the-shelf servers and switches.We have implemented with the Linux kernel MPTCP for experiments. The extensive experiments in a small cluster (including one MapReduce experiment) and trace-driven simulations show that our scheme achieves the design goals effectively

Homa: A Receiver-Driven Low-Latency Transport Protocol Using Network Priorities (Complete Version)

Homa is a new transport protocol for datacenter networks. It provides exceptionally low latency, especially for workloads with a high volume of very short messages, and it also supports large messages and high network utilization. Homa uses in-network priority queues to ensure low latency for short messages; priority allocation is managed dynamically by each receiver and integrated with a receiver-driven flow control mechanism. Homa also uses controlled overcommitment of receiver downlinks to ensure efficient bandwidth utilization at high load. Our implementation of Homa delivers 99th percentile round-trip times less than 15{\mu}s for short messages on a 10 Gbps network running at 80% load. These latencies are almost 100x lower than the best published measurements of an implementation. In simulations, Homa's latency is roughly equal to pFabric and significantly better than pHost, PIAS, and NDP for almost all message sizes and workloads. Homa can also sustain higher network loads than pFabric, pHost, or PIAS.Comment: This paper is an extended version of the paper on Homa that was published in ACM SIGCOMM 2018. Material had to be removed from Sections 5.1 and 5.2 to meet the SIGCOMM page restrictions; this version restores the missing material. This paper is 18 pages, plus two pages of reference

Re-architecting datacenter networks and stacks for low latency and high performance

© 2017 ACM. Modern datacenter networks provide very high capacity via redundant Clos topologies and low switch latency, but transport protocols rarely deliver matching performance. We present NDP, a novel datacenter transport architecture that achieves near-optimal completion times for short transfers and high flow throughput in a wide range of scenarios, including incast. NDP switch buffers are very shallow and when they fill the switches trim packets to headers and priority forward the headers. This gives receivers a full view of instantaneous demand from all senders, and is the basis for our novel, high-performance, multipath-aware transport protocol that can deal gracefully with massive incast events and prioritize traffic from different senders on RTT timescales. We implemented NDP in Linux hosts with DPDK, in a software switch, in a NetFPGA-based hardware switch, and in P4. We evaluate NDP's performance in our implementations and in large-scale simulations, simultaneously demonstrating support for very low-latency and high throughput.This work was partly funded by the SSICLOPS H2020 project (644866)