RFQ: Redemptive Fair Queuing

Gulati, Ajay; Varman, Peter

doi:10.1007/978-3-540-87744-8_41

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…• Fair Queueing: The requests are partitioned by RTT and the two queues Q 1 and Q 2 are served using a proportional share bandwidth allocator (like WF2Q [21], SFQ [22], RFQ [23]) that divides the server capacity in the specified ratio of C min : ∆C. The total capacity of the server is C min + ∆C, but by sharing a single physical server we hope to leverage the benefits of statistical multiplexing.…”

Section: Recombining Algorithmsmentioning

confidence: 99%

Decomposing Workload Bursts for Efficient Storage Resource Management

Varman

Doshi

2011

IEEE Trans. Parallel Distrib. Syst.

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Abstract-The growing popularity of hosted storage services and shared storage infrastructure in data centers is driving the recent interest in resource management and QoS in storage systems. The bursty nature of storage workloads raises significant performance and provisioning challenges, leading to increased resource requirements, management costs, and energy consumption. We present a novel workload shaping framework to handle bursty workloads, where the arrival stream is dynamically decomposed to isolate its bursts, and then rescheduled to exploit available slack. We show how decomposition reduces the server capacity requirements and power consumption significantly, while affecting QoS guarantees minimally. We present an optimal decomposition algorithm RTT and a recombination algorithm Miser, and show the benefits of the approach by evaluating the performance of several storage workloads using both simulation and Linux implementation.

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Section: Recombining Algorithmsmentioning

confidence: 99%