Inside the Social Network's (Datacenter) Network

Roy, Arjun; Zeng, Hongyi; Bagga, Jasmeet; Porter, George; Snoeren, Alex C.

doi:10.1145/2785956.2787472

Cited by 608 publications

(273 citation statements)

References 27 publications

Supporting

Mentioning

250

Contrasting

Order By: Relevance

“…Fig. 7 depicts the performance comparison of various schemes for 10, 100, and 500 flows in pure MF and EF scenarios 5 achieved a high level of accuracy in both pure MF and pure EF cases. Also, OpenSample-TCP attained 100% in pure MF evaluation, and 90%-98% in EF experiment.…”

Section: B Detection Accuracymentioning

confidence: 99%

LightFDG: An Integrated Approach to Flow Detection and Grooming in Optical Wireless DCNs

AlGhadhban

Çelik

Shihada

et al. 2020

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

LightFDG is an integrated approach to flow detection (FD) and flow grooming (FG) in optical wireless data center networks (DCNs), which is interconnected via wavelength division multiplexing (WDM) based free-space optical (FSO) links. Since forwarding bandwidth-hungry elephant flows (EFs) and delay-sensitive mice flows (MFs) on the same path can cause severe performance degradation, the LightFDG optically grooms flows of each class into rack-to-rack (R2R) flows. Then, R2R-MF and R2R-EF flows are separately forwarded over lightpaths of separate MF and EF virtual topologies, respectively. Lightpaths are provisioned by jointly determining the capacity and route based on flows' arrival rate, size, and completion time request. To prevent EFs from congesting the MF lightpaths, high speed and accurate flow-detection mechanisms are also necessary for classifying EFs as soon as possible. Therefore, a fast-lightweight-andaccurate flow detection framework is developed by leveraging the transmission control protocol (TCP) behaviors. The proposed FD scheme has the flexibility of being implemented as in-network or centralized to classify flows of modifiable and unmodifiable hosts, respectively. Since the centralized scheme incurs considerable overhead, the processing and communication overhead is also mitigated by proposed techniques. Numerical results show that LightFDG outperforms traditional load balancers by about 3f or EFs and 10ˆfor MFs. Along with the developed overhead mitigation methods, the centralized scheme is shown to provide up to 62ˆlower overhead with 100% accuracy and with about 224ˆhigher detection speeds than the existing centralized solutions.

show abstract

Section: B Detection Accuracymentioning

confidence: 99%

LightFDG: An Integrated Approach to Flow Detection and Grooming in Optical Wireless DCNs

AlGhadhban

Çelik

Shihada

et al. 2020

IEEE Trans. Netw. Serv. Manage.

View full text Add to dashboard Cite

show abstract

“…Here, we use web search and data mining workloads (two realistic production DCN workloads which generally cover the pattern of most of the todays DCNs applications) to find the maximum value of H determined by Theorem 1. We use 10Gbps as a typical link capacity used in todays DCNs [8,11,12] to determine service rate of a flow with size x (x/10Gbps), and consider T cost = 100µ s which is a typical RTT delay in todays DCNs [4,13]. Fig.…”

Section: How Much Big Is the Threshold H In Todays Dcns?mentioning

confidence: 99%

To schedule or not to schedule: When no-scheduling can beat the best-known flow scheduling algorithm in datacenter networks

Abbasloo

Chao

2020

Computer Networks

View full text Add to dashboard Cite

Conventional wisdom for minimizing the average flow completion time (AFCT) in the datacenter network (DCN), where flow sizes are highly variable, would suggest scheduling every individual flow. However, we show that considering scheduling delay (including schedulers computational and communication delays), serving most of the flows without any scheduling and only in first-comefirst-served (FCFS) manner significantly improves their performance even when it is compared to the shortest remaining processing time (SRPT)known as optimum algorithm when scheduling delay is zero. To do so, we only require to have two coarse classes of flows categorized based on flows sizes (1st-class including flows smaller than a threshold, H, and 2nd-class including others) and serve 1stclass flows always before serving 2nd-class ones. To show that, we take SRPT scheduling algorithm accompanied by the global knowledge of flows, formulate impact of scheduling delay on its performance, and prove that for any flow size distribution and network load (< 1), there is always a threshold, H, which guarantees 1st-class flows achieve lower AFCT under FCFS compared to SRPT. Our numerically calculated results and extensive flow-level simulations show that on average, more than 90% of flows could be in 1st-class and consequently do not require any scheduling.

show abstract

“…All flows whose paths goes over e flows is usually a small fraction of the total number of flows although they carry significant volumes of traffic [3], [11]. 2 Depending on how network queues prioritize the transmission of data packets and how the end-points transmit traffic, a variety of network scheduling policies can be realized.…”

Section: Variablementioning

confidence: 99%

“…The results were averaged across the 20 runs, and the error bars show the standard deviation over the runs. The Facebook patterns were inferred from the CDF curves reported in [11]. of flows, we will focus on BWRHF and its further evaluation from here on.…”

Section: A Comparison Of Bwrh and Bwrhfmentioning

confidence: 99%

Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing

Noormohammadpour

Srivastava

Raghavendra

2019

2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

View full text Add to dashboard Cite

Flow routing over inter-datacenter networks is a well-known problem where the network assigns a path to a newly arriving flow potentially according to the network conditions and the properties of the new flow. An essential system-wide performance metric for a routing algorithm is the flow completion times, which affect the performance of applications running across multiple datacenters. Current static and dynamic routing approaches do not take advantage of flow size information in routing, which is practical in a controlled environment such as inter-datacenter networks that are managed by the datacenter operators. In this paper, we discuss Best Worst-case Routing (BWR), which aims at optimizing the tail completion times of long-running flows over inter-datacenter networks with nonuniform link capacities. Since finding the path with the best worst-case completion time for a new flow is NP-Hard, we investigate two heuristics, BWRH and BWRHF, which use two different upper bounds on the worst-case completion times for routing. We evaluate BWRH and BWRHF against several real WAN topologies and multiple traffic patterns. Although BWRH better models the BWR problem, BWRH and BWRHF show negligible difference across various system-wide performance metrics, while BWRHF being significantly faster. Furthermore, we show that compared to other popular routing heuristics, BWRHF can reduce the mean and tail flow completion times by over 1.5× and 2×, respectively.

show abstract

Inside the Social Network's (Datacenter) Network

Cited by 608 publications

References 27 publications

LightFDG: An Integrated Approach to Flow Detection and Grooming in Optical Wireless DCNs

LightFDG: An Integrated Approach to Flow Detection and Grooming in Optical Wireless DCNs

To schedule or not to schedule: When no-scheduling can beat the best-known flow scheduling algorithm in datacenter networks

Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing

Contact Info

Product

Resources

About