pith. sign in

arxiv: 1906.10766 · v1 · pith:MBFGQNYDnew · submitted 2019-06-25 · 💻 cs.NI

A Framework for Qualitative Communications Using Big Packet Protocol

Pith reviewed 2026-05-25 15:42 UTC · model grok-4.3

classification 💻 cs.NI
keywords qualitative communicationspacket washbig packet protocolpartial packet deliverynetwork congestion handlingdata plane operationschunk based payloads
0
0 comments X

The pith

Qualitative communication services allow partial packet delivery by selectively removing chunks instead of dropping entire packets.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper introduces qualitative communications that break packet payloads into chunks for finer bandwidth control. When networks are congested or have errors, forwarding nodes can perform Packet Wash to remove less significant chunks based on their relationships or importance levels. This enables timely partial delivery rather than full drops and retransmissions. The framework is built on the Big Packet Protocol to support this new operation in the data plane. A sympathetic reader would care because it promises more predictable performance in challenging network conditions.

Core claim

By defining qualitative communication services and implementing Packet Wash in forwarding nodes using the Big Packet Protocol, the approach allows selective chunk removal from packets upon error or congestion, based on chunk relationships or significance, resulting in partial yet timely delivery.

What carries the argument

Packet Wash, the operation in forwarding nodes that selectively removes chunks from the payload.

If this is right

  • Partial delivery reduces unpredictable delays from packet drops.
  • Finer granularity improves bandwidth utilization under constrained conditions.
  • The Big Packet Protocol provides the data plane technology to implement the directives.
  • Services can be tailored using predefined chunk significance levels.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Applications might need to be redesigned to handle and benefit from partial data deliveries.
  • Interoperability could require agreement on how chunk significance is encoded and interpreted across different networks.
  • Real deployments would need to measure whether partial packets actually lower overall retransmission overhead compared to standard drops.

Load-bearing premise

Forwarding nodes can detect and act on predefined chunk relationships or significance levels to remove chunks while still delivering useful partial payloads.

What would settle it

A measurement showing that in practice, partial deliveries from chunk removal do not reduce retransmission rates or improve timeliness compared to full packet drops.

Figures

Figures reproduced from arXiv: 1906.10766 by Cedric Westphal, Filip De Turck, Hamed Yousefi, Kiran Makhijani, Lijun Dong, Richard Li, Tim Wauters.

Figure 1
Figure 1. Figure 1: Packet wash drops some chunks in intermediate nodes 3 QUALITATIVE COMMUNICATION TECHNIQUES In this section, we introduce three techniques to realize qualitative communications in the network: (1) Packet Wash, (2) adaptive rate control, and (3) in-packet network coding. Although all techniques are dealing with Packet Wash operations in the forwarding nodes, their main focuses are on in-network operations, f… view at source ↗
Figure 2
Figure 2. Figure 2: In-packet network coding The proposed approach is illustrated using a simple example in [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 4
Figure 4. Figure 4: Idealized qualitative packet format the QoS level of the packet after a Packet Wash treatment, by in￾creasing the ToS to the next higher value [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: BPP packet format with BPP block et Frame HeaderHdrBlockBlock y [PITH_FULL_IMAGE:figures/full_fig_p005_5.png] view at source ↗
read the original abstract

In the current Internet architecture, a packet is a minimal or fundamental unit upon which different actions such as classification,forwarding, or discarding are performed by the network nodes.When faced with constrained or poor network conditions, a packet is subjected to undesirable drops and re-transmissions, resulting in unpredictable delays and subsequent traffic overheads in the network. Alternately, we introduce qualitative communication services which allow partial, yet timely, delivery of a packet instead of dropping it entirely. These services allow breaking down packet payloads into smaller units (called chunks), enabling much finer granularity of bandwidth utilization. We propose Packet Wash as a new operation in forwarding nodes to support qualitative services. Upon packet error or network congestion, the forwarding node selectively removes some chunk(s)from the payload based on the relationship among the chunks or the individual significance level of each chunk. We also present a qualitative communication framework as well as a Packet Wash directive implemented in a newly evolved data plane technology,called Big Packet Protocol (BPP)

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript proposes a qualitative communication framework based on the Big Packet Protocol (BPP) that breaks packet payloads into chunks to enable partial, timely delivery instead of full packet drops under congestion or errors. It introduces Packet Wash as a new forwarding-node operation that selectively removes chunks according to inter-chunk relationships or per-chunk significance levels, together with a Packet Wash directive syntax.

Significance. If the required metadata mechanisms can be supplied, the framework could in principle support finer-grained bandwidth allocation and reduced retransmission overhead in constrained networks. The manuscript itself, however, contains no implementation, simulation, analysis, or measurement to quantify these benefits or demonstrate feasibility.

major comments (2)
  1. [Packet Wash section] § on Packet Wash (abstract and framework description): the selective removal of chunks presupposes that forwarding nodes can obtain chunk significance levels or inter-chunk relationships at line rate, yet no encoding, in-band header format, or out-of-band signaling protocol is defined that would allow a generic router to parse this information for arbitrary payloads without application-specific context.
  2. [Abstract] Abstract and overall framework presentation: the central claim that qualitative services yield 'much finer granularity of bandwidth utilization' and 'timely' partial delivery receives no supporting derivation, model, or empirical result; the manuscript remains a purely conceptual proposal.
minor comments (1)
  1. [Abstract] Abstract contains typographic errors: missing space after comma in 'classification,forwarding' and in 'chunk(s)from the payload'.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments highlighting the need for more concrete mechanisms and supporting analysis. We address each major comment below and indicate planned revisions where appropriate.

read point-by-point responses
  1. Referee: [Packet Wash section] § on Packet Wash (abstract and framework description): the selective removal of chunks presupposes that forwarding nodes can obtain chunk significance levels or inter-chunk relationships at line rate, yet no encoding, in-band header format, or out-of-band signaling protocol is defined that would allow a generic router to parse this information for arbitrary payloads without application-specific context.

    Authors: We agree that a concrete encoding is required for line-rate operation by generic routers. The manuscript introduces the Packet Wash directive within BPP but does not detail a specific in-band format or signaling protocol. To address this, the revised version will include an example metadata encoding (leveraging BPP's extensible header fields) that allows parsing of per-chunk significance and relationships without application-specific context. revision: yes

  2. Referee: [Abstract] Abstract and overall framework presentation: the central claim that qualitative services yield 'much finer granularity of bandwidth utilization' and 'timely' partial delivery receives no supporting derivation, model, or empirical result; the manuscript remains a purely conceptual proposal.

    Authors: The work is a conceptual framework proposal, so the claims follow from the architectural shift to partial delivery rather than full drops. No derivation, model, or results are present because the manuscript stops at framework definition. We will add a dedicated discussion section providing qualitative reasoning on the granularity benefits and explicitly stating that quantitative evaluation is planned as future work. revision: partial

Circularity Check

0 steps flagged

No circularity: conceptual framework proposal with no derivations or fitted quantities

full rationale

The manuscript is a high-level architectural proposal introducing qualitative communication services and the Packet Wash operation as new concepts. No equations, parameter fits, predictions, or derivation chains appear in the abstract or described content. The central claim (selective chunk removal based on significance/relationships) is presented as a directive for future implementation rather than a result derived from prior fitted inputs or self-citations. No self-definitional, fitted-input, or uniqueness-imported patterns are present; the work is self-contained as a framework suggestion.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 2 invented entities

The central claim rests on the introduction of new operations and services without empirical validation or detailed specifications in the abstract; the proposal depends on domain assumptions about chunk significance rather than new free parameters or invented physical entities.

axioms (1)
  • domain assumption Chunks within a packet have definable relationships or significance levels that allow selective removal without losing essential information.
    Invoked directly in the description of the Packet Wash operation upon error or congestion.
invented entities (2)
  • Packet Wash no independent evidence
    purpose: Selectively remove chunks from a packet payload based on significance or relationships during congestion or error
    New operation proposed to support qualitative services; no independent evidence supplied.
  • Big Packet Protocol (BPP) no independent evidence
    purpose: Evolved data plane technology to implement the qualitative communication framework and Packet Wash directive
    Newly evolved technology referenced as the implementation vehicle; no independent evidence supplied.

pith-pipeline@v0.9.0 · 5719 in / 1423 out tokens · 33174 ms · 2026-05-25T15:42:35.332992+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

27 extracted references · 27 canonical work pages

  1. [1]

    Ethernet Alliance

    2017. Ethernet Alliance. http://ethernetalliance.org/wp-content/uploads/2011/ 10/EA-Ethernet-Jumbo-Frames-v0-1.pdf. [Online]

  2. [2]

    Abdullayev, B

    J. Abdullayev, B. Shin, and D. Lee. 2015. A Dynamic Packet Fragmentation Ex- tension to High Throughput WLANs for Real-Time H264/AVC Video Streaming. In 10th International Conference on Future Internet . 1–4

  3. [3]

    Aditya and S

    S. Aditya and S. Katti. 2011. FlexCast: Graceful Wireless Video Streaming. In 17th Annual International Conference on Mobile Computing and Networking (Mo- biCom’11). 277–288. 6 A Framework for Qualitative Communications Using Big Packet Protocol NEAT’19, August 19, 2019, Beijing, China

  4. [4]

    Ahlswede, N

    R. Ahlswede, N. Cai, S. R. Li, and R. W. Yeung. 2000. Network information flow. IEEE Transactions on Information Theory 46, 4 (July 2000), 1204–1216

  5. [5]

    Bernet, P

    Y. Bernet, P. Ford, R. Yavatkar, F. Baker, L. Zhang, M. Speer, R. Braden, B. Davie, J. Wroclawski, and E. Felstaine. 2000. A Framework for Integrated Services Operation over Diffserv Networks. RFC 2998. (Nov. 2000)

  6. [6]

    Black, Ed

    D. Black, Ed. PMC, and P. Jones. 2015. Differentiated Services (Diffserv) and Real-Time Communication. IETF, RFC 2205, (Nov. 2015)

  7. [7]

    Cheng, F

    P. Cheng, F. Ren, R. Shu, and C. Lin. 2014. Catch the Whole Lot in an Action: Rapid Precise Packet Loss Notification in Data Centers. In 11th USENIX Conference on Networked Systems Design and Implementation (NSDI’14). 17–28

  8. [8]

    Dong and R

    L. Dong and R. Li. 2018. Enhance Information Derivation by In-Network Se- mantic Mashup for IoT Applications. In European Conference on Networks and Communications. 298–303

  9. [9]

    Dong and R

    L. Dong and R. Li. 2018. Information Exchange Oriented Clustering for Collabo- rative Vehicular System. In 27th Wireless and Optical Communication Conference . 1–5

  10. [10]

    Dong and R

    L. Dong and R. Li. 2018. Latency Guarantee for Multimedia Streaming Service to Moving Subscriber with 5G Slicing. In International Symposium on Networks, Computers and Communications. 1–7

  11. [11]

    Dong and R

    L. Dong and R. Li. 2019. Distributed Mechanism for Computation Offloading Task Routing in Mobile Edge Cloud Network. In International Conference on Computing, Networking and Communications (ICNC’19)

  12. [12]

    Fairhurst and ed

    G. Fairhurst and ed. F. Baker. 2015. IETF Recommendations Regarding Active Queue Management. https://www.rfc-editor.org/info/rfc7567

  13. [13]

    Frossard and O

    P. Frossard and O. Verscheure. 2001. Joint Source/FEC Rate Selection for Quality- optimal MPEG-2 Video Delivery. IEEE Transactions on Image Processing 10, 12 (Dec. 2001), 1815–1825

  14. [14]

    Ghasemi, H

    C. Ghasemi, H. Yousefi, K. G. Shin, and B. Zhang. 2018. A Fast and Memory- Efficient Trie Structure for Name-based Packet Forwarding. In IEEE ICNP. 302– 312

  15. [15]

    Ghasemi, H

    C. Ghasemi, H. Yousefi, K. G. Shin, and B. Zhang. 2018. MUCA: New Routing for Named Data Networking. In IFIP Networking. 289–297

  16. [16]

    Handley, C

    M. Handley, C. Raiciu, A. Agache, A. Voinescu, A. Moore, G. Antichi, and M. Wójcik. 2017. Re-architecting Datacenter Networks and Stacks for Low Latency and High Performance. In ACM Special Interest Group on Data Communication (SIGCOMM’17). 29–42

  17. [17]

    D. He, C. Westphal, and JJ Garcia-Luna-Aceves. 2018. Network Support for AR/VR and Immersive Video Application: A Survey. In ICETE SIGMAP

  18. [18]

    T. Ho, M. Medard, R. Koetter, D. R. Karger, M. Effros, J. Shi, and B. Leong. 2006. A Random Linear Network Coding Approach to Multicast. IEEE Transactions on Information Theory 52, 10 (Oct. 2006), 4413–4430

  19. [19]

    R. Li. 2018. Network 2030: Market Drivers and Prospects. https: //www.itu.int/en/ITU-T/Workshops-and-Seminars/201810/Documents/ Richard_Li_Presentation.pdf

  20. [20]

    R. Li, A. Clemm, U. Chunduri, L. Dong, and K. Makhijani. 2018. A New Framework and Protocol for Future Networking Applications. ACM SIGCOMM Workshop on Networking for Emerging Applications and Technologies (NEAT’18), 637–648

  21. [21]

    X. Liu, Q. Xiao, V. Gopalakrishnan, B. Han, F. Qian, and M. Varvello. 2017. 360◦ Innovations for Panoramic Video Streaming. In16th ACM Workshop on Hot Topics in Networks (HotNets’17). 50–56

  22. [22]

    Makhijani, R

    K. Makhijani, R. Li, and H. Elbakoury. 2019. Using Big Packet Protocol Frame- work to Support Low Latency based Large Scale Networks. 15th International Conference on Networking and Service (ICNS’19)

  23. [23]

    J. K. Sundararajan, D. Shah, M. Medard, M. Mitzenmacher, and J. Barros. 2009. Network Coding Meets TCP. In IEEE INFOCOM

  24. [24]

    The Fast Data Project. 2017. CICN. https://wiki.fd.io/view/Cicn. [Online]

  25. [25]

    J. Wang, C. McArdle, and L. P. Barry. 2016. Large-scale Optical Datacentre Networks Using Hybrid Fibre Delay Line Buffers and Packet Retransmission. In 18th International Conference on Transparent Optical Networks . 1–4

  26. [26]

    Westphal

    C. Westphal. 2017. Challenges in Networking to Support Augmented Reality and Virtual Reality. In IEEE ICNC

  27. [27]

    Zhang, A

    L. Zhang, A. Afanasyev, J. Burke, V. Jacobson, KC. claffy, P. Crowley, C. Pa- padopoulos, L. Wang, , and B. Zhang. 2014. Named Data Networking. ACM SIGCOMM Comput. Commun. Rev. 44, 3 (2014), 66–73. 7