Processor-sharing queues: some progress in analysis
Queueing Systems: Theory and Applications
Processor Sharing Queueing Models of Mixed Scheduling Disciplines for Time Shared System
Journal of the ACM (JACM)
New directions in traffic measurement and accounting
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Size-based scheduling to improve web performance
ACM Transactions on Computer Systems (TOCS)
Trends and differences in connection-behavior within classes of internet backbone traffic
PAM'08 Proceedings of the 9th international conference on Passive and active network measurement
NETWORKING'10 Proceedings of the 9th IFIP TC 6 international conference on Networking
Size-based scheduling to improve the performance of short TCP flows
IEEE Network: The Magazine of Global Internetworking
WWIC'12 Proceedings of the 10th international conference on Wired/Wireless Internet Communication
A spike-detecting AQM to deal with elephants
Computer Networks: The International Journal of Computer and Telecommunications Networking
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Size-based scheduling is a promising solution to improve the response time of small flows (mice) that have to share bandwidth with large flows (elephants). To do this, one important task is to track the size of the ongoing flows at the router. However, most of the proposed size-based schedulers either employ the trivial way of tracking the size information of all flows, or require changes at end-hosts. Hence, either they are not scalable or they increase complexity. This paper proposes a new way of performing size-based scheduling in a practical and scalable fashion, by identifying and 'de-prioritizing' elephants only at times of high load. We exploit TCP's behaviour by using a mechanism that detects a window of packets -- called spikes -- when the buffer length exceeds a certain threshold. This spike-detection is used to identify elephant flows and thereafter de-prioritize them. Two-level processor-sharing (TLPS) scheduling is employed to schedule flows in two queues, one with the high-priority flows, and the other with the de-prioritized flows. We perform studies, using both analyses and simulations, to highlight the properties of the spike-detection mechanism. We show that, the proposed mechanism not only improves the response time of mice flows in a scalable way, but also gives better response times to other flows by treating them preferentially as long as they do not overload the high-priority queue.