Expeditus: Congestion-Aware Load Balancing in Clos Data Center Networks

Wang, Peng; Xu, Hong; Niu, Zhixiong; Han, Dongsu; Xiong, Yan

doi:10.1109/tnet.2017.2731986

Cited by 21 publications

(15 citation statements)

References 33 publications

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“…Expeditus [30] distributed congestionaware load balancing protocol three-level Clos topology web search and data mining workloads For mice flows, Expeditus outperforms ECMP by up to 45% in tail flow completion times and by up to 38% in mean flow completion time for elephant flows in 3-tier Clos networks.…”

Section: Discussionmentioning

confidence: 99%

“…Niagara [27] is another traffic-splitting solution for commodity switches which offers similar performance to MicroTe [28]. A promising distributed congestion-aware load balancing solution is proposed in [29], [30] and referred to as Expeditus. Expeditus is targeted at general 3-tier Clos topologies and conveys load balancing to network edge using local congestion monitoring.…”

Section: Scope and Related Workmentioning

confidence: 99%

“…Compared to OFLoad, other load balancing solutions like LABERIO [24], FlowBender [25], Presto [26], Niagara [27], or Expeditus [30] they either do not look into differentiating between the mice and elephant flows or they try to move the load balancing functionality at the network edge limiting the global view of the controller. Breaking the flows into sub-flows is another option adopted by some of the solutions.…”

Section: E Conceptual Comparison To Other Solutionsmentioning

confidence: 99%

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OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

Trestian

Katrinis

Muntean

2017

IEEE Trans. Netw. Serv. Manage.

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Abstract-The latest tremendous growth in the Internet traffic has determined the entry into a new era of mega-datacenters, meant to deal with this explosion of data traffic. However this big data with its dynamically changing traffic patterns and flows might result in degradations of the application performance eventually affecting the network operators' revenue. In this context there is a need for an intelligent and efficient network management system that makes the best use of the available bisection bandwidth abundance to achieve high utilization and performance. This paper proposes OFLoad, an OpenFlow-based dynamic load balancing strategy for datacenter networks that enables the efficient use of the network resources capacity. A real experimental prototype is built and the proposed solution is compared against other solutions from the literature in terms of load-balancing. The aim of OFLoad is to enable the instant configuration of the network by making the best use of the available resources at the lowest cost and complexity.

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Section: Discussionmentioning

confidence: 99%

Section: Scope and Related Workmentioning

confidence: 99%

Section: E Conceptual Comparison To Other Solutionsmentioning

confidence: 99%

See 1 more Smart Citation

OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

Trestian

Katrinis

Muntean

2017

IEEE Trans. Netw. Serv. Manage.

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“…Many researchers had proposed congestion-aware switching techniques to balance the data center loads. However, from the assessment, it is evident that most of the schemes suffer from the congestion mismatch in an asymmetric condition [12,18].…”

Section: Related Workmentioning

confidence: 99%

Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center

et al. 2019

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Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstances as well as the reduction of failures. However, under dynamic traffic, current load-balancing schemes use the fixed parameter setting, resulting in suboptimal performances. Therefore, we propose a multi-level dynamic traffic load-balancing (MDTLB) protocol, which uses an adaptive approach of parameter setting. The simulation results show that the MDTLB outperforms the state-of-the-art schemes in terms of both the flow completion time and throughput in typical data center applications.

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“…For example, flows from many hosts may pass through a ToR switch giving it further knowledge to perform scheduling and allocation optimizations. Some examples of this approach include RCP [86], PDQ [87], CONGA [106], Expeditus [107], and RackCC [108]. RCP and PDQ perform in-network rate allocation and assignment by allowing switches and end-hosts to communicate using custom headers, CONGA gets help from switches to perform flowlet based load balancing in leaf-spine topologies, Expeditus performs flow based load balancing by implementing custom Layer 2 headers and localized monitoring of congestion at the switches, and RackCC uses ToR switches as means to share congestion information among many flows between the same source and destination racks to help them converge faster to proper transmission rates.…”

Section: Scheme Benefits Drawbacksmentioning

confidence: 99%

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Noormohammadpour¹,

Raghavendra²

2017

Preprint

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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.

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Expeditus: Congestion-Aware Load Balancing in Clos Data Center Networks

Cited by 21 publications

References 33 publications

OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center

Datacenter Traffic Control: Understanding Techniques and Trade-offs

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