PPV - Per Packet Value
What is the PPV?

What is the PPV?

PPV Simulator: go

The proposed framework

  • Defines resource sharing policies for all situations by throughput-Packet Value functions
  • Proposes a Packet Marker at the edge of the network, which marks a Packet Value on each packet, based on the throughput-PV function of that flow.
  • Within the network, Resource Nodes only need maximize the total transmitted Packet Value. This maximization results in implementing the policies, without the need for any flow awareness.

Per Packet Value Concept

  • The Packet Value represents the gain of the operator when the packet is delivered. It expresses the relative importance of one packet to another. [Value/bit]
  • The aim of the network, and every Resource Node within is to maximize the total Packet Value of the transmitted packets.
  • The Congestion Threshold Value separates the packets with PVs that get transmitted from the ones that get dropped (at a Resource Node)
    • resulting from the combination of available capacity, amount of offered traffic and the Packet Value composition of the offered traffic
    • increases as the congestion increases
  • The framework complements E2E Congestion Control
    • PPV enforces fairness, only low controlled loss has to be provided by E2E Congestion Control
    • Even incompatible CCs can coexist in a network implementing PPV

Packet Marker

  • Requirement on packet marking:
    • if all packets below a Congestion Threshold Value are dropped
    • then the throughput of the remaining packets shall be as defined by the throughput-PV function at this threshold
  • An example implementation (per flow)
    • Quantize the throughput-PV functions
    • Associate a token bucket to each quantized region (PV as defined, incoming token rate is the throughput of this region, size is token rate * typical buffer size of Resource Nodes)
    • When a packet of a flow arrives, select the token bucket with the highest PV, where there are enough tokens (packet size)

Resource Node

  • Task is to maximize the total transmitted Packet Value
  • The simplest algorithm is to always serve packets with highest PV first
    • Non-practical for typical flows as it results in out of order delivery
  • A simple FIFO implementation is possible,
    • when the queue becomes full drop the packet with the smallest Packet Value first
  • If different packets have different resource demands that can be taken to account when maximizing the total transmitted Packet Value
    • Packet Values cannot be directly compared, but must be normalized by the cost of their transmission (r)
    • We define the Effective Packet Value of a packet as its Packet V alue divided by its transmission cost (r)

See Also

  • Zhiruo Cao et al.: "Rainbow fair queueing: theory and applications", Elsevier Computer Networks 47 (2005) pp 367-392 (link)



Laki, S., Gombos, G., Nádas, S., & Turányi, Z. (2017, July). "Take your own share of the PIE", In Proceedings of the Applied Networking Research Workshop (pp. 27-32). ACM. (video presentation)
Sándor Laki, Gergő Gombos, Péter Hudoba, Szilveszter Nádas, Zoltán Kiss, Gergely Pongrácz, Csaba Keszei: "Scalable Per Subscriber QoS with Core-Stateless Scheduling", (2018), ACM SIGCOMM 2018 Industrial Demos, (pdf, demo video)
Ferenc Fejes, Sándor Laki, Gergő Gombos, Szilveszter Nádas, Zoltán Kiss: "Decoupling Delay and Resource Sharing Targets with Efficient Core-Stateless AQM", (2019), ACM SIGCOMM 2019 Demos, (pdf)
Szilveszter Nádas,Gergő Gombos, Ferenc Fejes, Sándor Laki: "Towards Core-Stateless Fairness on Multiple Timescales", (2019), ANRW (pdf)
Ferenc Fejes, Gergő Gombos, Sándor Laki, Szilveszter Nádas: "On the Incompatibility of Scalable Congestion Controls over the Internet", (2020), FIT
Szilveszter Nádas, Gergő Gombos, Ferenc Fejes, Sándor Laki: "A Congestion Control Independent L4S Scheduler", (2020), ANRW
Szilveszter Nádas, Balázs Varga, Ferenc Fejes, Gergő Gombos, Sándor Laki: "On Congestion Control (un)fairness", (2020), IETF109 ICCRG

  • News

  • 2020.05

    Our paper on A Congestion Control Independent L4S Scheduler has been accepted for publication at the ACM/IRTF Applied Networking Research Workshop 2020 (ANRW’20) that will be held together with the IETF-108 meeting.

  • 2020.05

    Our paper On the incompatibility of scalable congestion controls over the Internet has been accepted for publication at the 2nd Workshop on the Future of Internet Transport held in co-location with IFIP Networking 2020.

  • 2019.11

    Our paper entitled "Who will Save the Internet from the Congestion Control Revolution?" has been accepted for publication at the Workshop on Buffer Sizing, Stanford University, CA, USA. The workshop program seems very exciting.

  • 2019.08

    Our demo (Decoupling Delay and Resource Sharing Targets with Efficient Core-Stateless AQM) was presented at ACM SIGCOMM 2019, Beijing, China.

  • 2019.06

    Our paper on Towards Core-Stateless Fairness on Multiple Timescales has been accepted for publication at ACM/IRTF ANRW 2019.

  • 2018.07

    The IETF-102 meeting has just started with more than 1000 participants in Montreal, QC, Canada. Our paper is being presented at ANRW'18, a satelite conference of the IETF meeting tomorrow. (presentation)

  • 2018.06

    Our industrial demo ("Scalable Per Subscriber QoS with Core-Stateless Scheduling") submitted together with Ericsson has been accepted for presentation at SIGCOMM 2018.

The Team

Szilveszter Nádas

Ericsson Research, Hungary

Sándor Laki, PhD

Eötvös Loránd University, Hungary

Gergő Gombos, PhD

Eötvös Loránd University, Hungary

Ferenc Fejes

Eötvös Loránd University, Hungary

Péter Hudoba

Eötvös Loránd University, Hungary

Contact Us

Sándor Laki: lakis at inf dot elte dot hu

Szilveszter Nádas: ...