Cubic

Ha, Sangtae; Rhee, Injong; Xu, Lisong

doi:10.1145/1400097.1400105

Cited by 1,631 publications

(152 citation statements)

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“…Moreover, Tars revises the goal of the rate control in C3, making it consistent with the goal of the congestion control algorithms for Internet [? ], [13]. Although the timeliness issue is not totally addressed, Tars outperforms C3 with these improvement, as confirmed by the simulations based on the open source code of C3.…”

Section: Introductionmentioning

confidence: 54%

“…Aware of these challenges, an adaptive replica selection scheme C3 is proposed recently [12]. C3 piggybacks the queue-size of waiting keys and the service time from the servers to guide the replica ranking at clients, and introduce both the Cubic rate control algorithm [13] and backpressure mechanism to adapt the sending rate of keys at the clients to the observed receipt capacity of servers. In this way, C3 can adapt to the time-varying service rate across servers and avoid the herd behavior [12].…”

Section: Introductionmentioning

confidence: 99%

“…If the rates of all the replica servers of a key are limited, the key will be put into a backlog queue until the rate limitation of a replica server is released. The detailed rate control algorithm is borrowed from CUBIC [13]. Let rRate s be the number of values received from a server in a δ interval.…”

Section: Introductionmentioning

confidence: 99%

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Tars: Timeliness-Aware Adaptive Replica Selection for Key-Value Stores

Jiang

Fang

Xie

et al. 2017

2017 26th International Conference on Computer Communication and Networks (ICCCN)

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Abstract-In current large-scale distributed key-value stores, a single end-user request may lead to key-value access across tens or hundreds of servers. The tail latency of these key-value accesses is crucial to the user experience and greatly impacts the revenue. To cut the tail latency, it is crucial for clients to choose the fastest replica server as much as possible for the service of each key-value access. Aware of the challenges on the time varying performance across servers and the herd behaviors, an adaptive replica selection scheme C3 is proposed recently. In C3, feedback from individual servers is brought into replica ranking to reflect the time-varying performance of servers, and the distributed rate control and backpressure mechanism is invented. Despite of C3's good performance, we reveal the timeliness issue of C3, which has large impacts on both the replica ranking and the rate control, and propose the Tars (timeliness-aware adaptive replica selection) scheme. Following the same framework as C3, Tars improves the replica ranking by taking the timeliness of the feedback information into consideration, as well as revises the rate control of C3. Simulation results confirm that Tars outperforms C3.

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Section: Introductionmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tars: Timeliness-Aware Adaptive Replica Selection for Key-Value Stores

Jiang

Fang

Xie

et al. 2017

2017 26th International Conference on Computer Communication and Networks (ICCCN)

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“…The Cubic TCP algorithm [7] aims to avoid the shortcomings of Reno and achieve high data rates in networks with large BDP. At the same time, when Cubic detects a network with small BDP, it tries to mimic Reno's behaviour emulated by a mathematical model.…”

Section: ) Cubicmentioning

confidence: 99%

Evaluating the impact of SDN-induced frequent route changes on TCP flows

Carpa

Assunção

Glück

et al. 2017

2017 13th International Conference on Network and Service Management (CNSM)

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Abstract-Traffic engineering technologies such as MPLS have been proposed to adjust the paths of data flows according to network availability. Although the time interval between traffic optimisations is often on the scale of hours or minutes, modern SDN techniques enable reconfiguring the network more frequently. It is argued, however, that changing the paths of TCP flows too often could severely impact their performance by incurring packet loss and reordering. This work analyses and evaluates the impact of frequent route changes on the performance of TCP flows. Experiments carried out on a network testbed show that rerouting a flow can affect its throughput when reassigning it a path either longer or shorter than the original path. Packet reordering has a negligible impact when compared to the increase of RTT. Moreover, constant rerouting influences the performance of the congestion control algorithm. Designed to assess the limits on SDN-induced reconfiguration, a scenario where the traffic is rerouted every 0.1s demonstrates that the throughput can be as low as 35% of that achieved without rerouting.

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“…In literature we can find different solutions proposed to overcome the problem, and, in particular, different TCP variants have been proposed, since the UDP is simpler and there are not many variable aspects [9,10,11,12,13].…”

Section: Introductionmentioning

confidence: 99%