A scalable, commodity data center network architecture

Al-Fares, Mohammad; Loukissas, Alexander; Vahdat, Amin

doi:10.1145/1402946.1402967

Cited by 1,995 publications

(1,141 citation statements)

References 18 publications

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“…However, even these expensive and specific equipment may only serve 50% of the bandwidth of the data center at increased cost. Furthermore, non-uniform bandwidth assignment among data center nodes results in issues in the hosted applications; these issues affect the performance of applications [3]. Hence, providing sufficient bandwidth to applications is a significant challenge for network administrators [4][5][6].…”

Section: Implementation Issues mentioning

confidence: 99%

Fairly Scheduled Bandwidth for the Data Centre Traffic

Kolhar¹,

Alameen²

2017

IJCA

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Maintaining the bandwidth across a data center to meet the service level agreement is a major challenge for network administrators. If the bandwidth is not scheduled according to application requirements, the applications will be executed with increased or decreased provisioning or moved to other data centers. Hence, we developed a bandwidth scheduling algorithm that operates according to application requirements and partitions the available bandwidth to accommodate the available traffic. We simulated this algorithm with the SimPy tool and found that the proposed algorithm performs better than the general allocation and partition schemes.

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Section: Implementation Issues mentioning

confidence: 99%

Fairly Scheduled Bandwidth for the Data Centre Traffic

Kolhar¹,

Alameen²

2017

IJCA

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“…As shown in Figure 3, it is our adopted network architecture [26] of physical machines deployed in the cloud. The architecture makes use of fat-tree topology and is composed of three tiers.…”

Section: Problem Formulationmentioning

confidence: 99%

An RTT-Aware Virtual Machine Placement Method

Wang

Ren

2017

Information

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Virtualization is a key technology for mobile cloud computing (MCC) and the virtual machine (VM) is a core component of virtualization. VM provides a relatively independent running environment for different applications. Therefore, the VM placement problem focuses on how to place VMs on optimal physical machines, which ensures efficient use of resources and the quality of service, etc. Most previous work focuses on energy consumption, network traffic between VMs and so on and rarely consider the delay for end users' requests. In contrast, the latency between requests and VMs is considered in this paper for the scenario of optimal VM placement in MCC. In order to minimize average RTT for all requests, the round-trip time (RTT) is first used as the metric for the latency of requests. Based on our proposed RTT metric, an RTT-Aware VM placement algorithm is then proposed to minimize the average RTT. Furthermore, the case in which one of the core switches does not work is considered. A VM rescheduling algorithm is proposed to keep the average RTT lower and reduce the fluctuation of the average RTT. Finally, in the simulation study, our algorithm shows its advantage over existing methods, including random placement, the traffic-aware VM placement algorithm and the remaining utilization-aware algorithm.

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“…We consider the path diversity between pairs of servers. We use three generic models: Fat-Tree [2], VL2 [20], and BCube [21]. For each model, we instantiate a representative topology with approximately 600 servers.…”

Section: Path Diversity In Data Center Networkmentioning

confidence: 99%

“…Network operators therefore aim to maximize the network utilization in order to improve the performance of these applications [12,3]. To achieve this goal, data center designs rely heavily on ECMP [2,20,21,37] to spread the load among multiple paths and reduce congestion. This form of load balancing is blind and naive, congestion can still occur inside the data center and lead to reduced performance.…”

Section: Introductionmentioning

confidence: 99%

Revisiting flow-based load balancing: Stateless path selection in data center networks

et al. 2013

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Hash-based load-balancing techniques are widely used to distribute the load over multiple forwarding paths and preserve the packet sequence of transport-level flows. Forcing a long-lived, i.e., elephant, flow to follow a specific path in the network is a desired mechanism in data center networks to avoid crossing hot spots. This limits the formation of bottlenecks and so improves the network use. Unfortunately, current per-flow load-balancing methods do not allow sources to deterministically force a specific path for a flow.In this paper, we propose a deterministic approach enabling end hosts to steer their flows over any desired load-balanced path without relying on any packet header extension. By using an invertible mechanism instead of solely relying on a hash function in routers, our method allows to easily select the packet's header field values in order to force the selection of a given load-balanced path without storing any state in routers.We perform various simulations and experiments to evaluate the performance and prove the feasibility of our method using a Linux kernel implementation. Furthermore, we demonstrate with simulations and lab experiments how MultiPath TCP can benefit from the combination of our solution with a flow scheduling system that efficiently distributes elephant flows in large data center networks.

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A scalable, commodity data center network architecture

Cited by 1,995 publications

References 18 publications

Fairly Scheduled Bandwidth for the Data Centre Traffic

Fairly Scheduled Bandwidth for the Data Centre Traffic

An RTT-Aware Virtual Machine Placement Method

Revisiting flow-based load balancing: Stateless path selection in data center networks

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