Evolution of cache replacement policies to track heavy-hitter flows

Žádník, Martin; Canini, Marco

doi:10.1145/1872007.1872046

Cited by 5 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The algorithm detects elephant flows with small memory space, whereas it cannot estimate the size of detected flows. Memory-aware heavy-hitter detection schemes may also be found [6,7,25,26].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

On‐line detection of persistently high packet‐rate flows via a sliding window scheme with random packet sampling

Takanori

Takine

2013

Int J Network Mgmt

View full text Add to dashboard Cite

SUMMARY We consider on‐line detection of persistently high packet‐rate flows. We assume that flow information is collected via a time‐based sliding window scheme with random packet sampling. In this framework, we propose a method of determining the threshold of the number of sampled packets, which guarantees the false negative ratio. We also formulate and solve the design problem of our scheme, where we aim to minimize the false positive ratio. We then conduct sampling experiments with public trace data and confirm that our method works well as designed. Copyright © 2013 John Wiley & Sons, Ltd.

show abstract

Section: Related Workmentioning

confidence: 99%

“…# of sampled pkts in SWs FRPi Min. # of sampled pkts in SWs FRPi Class 1 [15,21] 0.999 [11,15] 0.999 Class 2 [22,29] 0.933 [16,21] 0.966 Class 3 [30,36] 0.480 [22,26] 0.686 Class 4…”

Section: Backbone Backscattermentioning

confidence: 99%

On‐line detection of persistently high packet‐rate flows via a sliding window scheme with random packet sampling

Takanori

Takine

2013

Int J Network Mgmt

View full text Add to dashboard Cite

show abstract

ALFE: A replacement policy to cache elephant flows in the presence of mice flooding

Pan

Guo

Zhang

et al. 2012

2012 IEEE International Conference on Communications (ICC)

View full text Add to dashboard Cite

Flow Migration on Multicore Network Processors: Load Balancing While Minimizing Packet Reordering

Iqbal

Holt²,

Ryoo

et al. 2013

2013 42nd International Conference on Parallel Processing

View full text Add to dashboard Cite

Abstract-With ever increasing network traffic rates, multicore architectures for network processors have successfully provided performance improvements through high parallelism. However, naively allocating the network traffic to multiple cores without considering diversified application nature and flow locality results in issues such as packet reordering, load imbalance and inefficient cache usage. Consequently, these issues degrade the performance of latency sensitive network processors by dropping packets or delivering packets out of order. In this paper, we propose a packet scheduling scheme that considers the multiple dimensions of locality to improve the throughput of a network processor while minimizing out of order packets. Our scheduling policy tries to maintain packet order by maintaining the flow locality, minimizes the migration of flows from one core to another by identifying the aggressive flows, and partitions the cores among multiple services to gain instruction cache locality. The scheduler uses a novel low cost two-level caching scheme to identify top aggressive flows. Our light weight hardware implementation shows improvement of 60% in the number of packets dropped and 80% improvement in the out-of-order packet deliveries over previously proposed techniques.

show abstract

Evolution of cache replacement policies to track heavy-hitter flows

Cited by 5 publications

References 8 publications

On‐line detection of persistently high packet‐rate flows via a sliding window scheme with random packet sampling

On‐line detection of persistently high packet‐rate flows via a sliding window scheme with random packet sampling

ALFE: A replacement policy to cache elephant flows in the presence of mice flooding

Flow Migration on Multicore Network Processors: Load Balancing While Minimizing Packet Reordering

Contact Info

Product

Resources

About