Network calculus

In network calculus, a flow is modelled as cumulative functions {{math|A}}, where {{math|A(t)}} represents the amount of data (number of bits for example) sent by the flow in the interval {{math|[0,t)}}. Such functions are non-negative and non-decreasing. The time domain is often the set of non negative reals.

File:Network Calculus -- Single server.svg

$$

A: \mathbb R^+ \rightarrow \mathbb R^+

$$

\forall u,t \in \mathbb R^+: u < t \implies A(u) \leq A(t)

A server can be a link, a scheduler, a traffic shaper, or a whole network. It is simply modelled as a relation between some arrival cumulative curve {{math|A}} and some departure cumulative curve {{math|D}}. It is required that {{math|A ≥ D}}, to model the fact that the departure of some data can not occur before its arrival.

Given some arrival and departure curve {{math|A}} and {{math|D}}, the backlog at any instant {{math|t}}, denoted {{math|b(A,D,t)}} can be defined as the difference between {{math|A}} and {{math|D}}. The delay at {{math|t}}, {{math|d(A,D,t)}} is defined as the minimal amount of time such that the departure function reached the arrival function. When considering the whole flows, the supremum of these values is used.

File:Horizontal and vertical deviation.svg

$$

b(A,D,t) := A(t) - D(t)

$$

d(A,D,t) := \inf\left\{ d \in \mathbb R^+ ~s.t.~ D(t+d) \geq A(t) \right\}

$$

b(A,D) := \sup_{t \geq 0}\left\{ A(t) - D(t) \right\}

$$

d(A,D) := \sup_{t \geq 0}\left\{ \inf\left\{ d \in \mathbb R^+ ~s.t.~ D(t+d) \geq A(t) \right\} \right\}

In general, the flows are not exactly known, and only some constraints on flows and servers are known (like the maximal number of packet sent on some period, the maximal size of packets, the minimal link bandwidth). The aim of network calculus is to compute upper bounds on delay and backlog, based on these constraints. To do so, network calculus uses the min-plus algebra.

Network calculus makes an intensive use on the min-plus semiring (sometimes called min-plus algebra).

In filter theory and linear systems theory the convolution of two functions $f$ and $g$ is defined as

$$

(f \ast g) (t) := \int_{0}^{t} f(\tau) \cdot g(t-\tau) d\tau

In min-plus semiring the sum is replaced by the minimum respectively infimum operator and the product is replaced by the sum. So the min-plus convolution of two functions $f$ and $g$ becomes

$$

(f \otimes g) (t) := \inf_{0 \leq \tau \leq t}\left\{f(\tau) + g(t-\tau)\right\}

e.g. see the definition of service curves. Convolution and min-plus convolution share many algebraic properties. In particular both are commutative and associative.

A so-called min-plus de-convolution operation is defined as

$$

(f \oslash g) (t) := \sup_{\tau \ge 0}\left\{f(t+\tau) - g(\tau)\right\}

e.g. as used in the definition of traffic envelopes.

The vertical and horizontal deviations can be expressed in terms of min-plus operators.

$$

b(f,g) = (f \oslash g)(0)

$$

d(f,g) = \inf \{w : (f \oslash g)(-w) \le 0 \}

Cumulative curves are real behaviours, unknown at design time. What is known is some constraint. Network calculus uses the notion of traffic envelope, also known as arrival curves.

A cumulative function {{math|A}} is said to conform to an envelope {{math|E}} (also called arrival curve and denoted {{math|α}}) , if for all {{math|t}} it holds that

$$

E(t) \ge \sup_{\tau \ge 0} \{A(t+\tau) - A(\tau) \} = (A \oslash A)(t).

Two equivalent definitions can be given

{{NumBlk|:|

$$

\forall t,d \in \mathbb R^+: A(t+d)-A(t) \leq E(d)

|{{EquationRef|1}}}}

{{NumBlk|:|

$$

A \leq A \otimes E

|{{EquationRef|2}}}}

Thus, {{math|E}} places an upper constraint on flow {{math|A}}. Such function {{math|E}} can be seen as an envelope that specifies an upper bound on the number of bits of flow seen in any interval of length {{math|d}} starting at an arbitrary {{math|t}}, cf. eq. ({{EquationNote|1}}).

In order to provide performance guarantees to traffic flows it is necessary to specify some minimal performance of the server (depending on reservations in the network, or scheduling policy, etc.). Service curves provide a means of expressing resource availability. Several kinds of service curves exists, like weakly strict, variable capacity node, etc. See

{{cite tech report |first1= Anne|last1= Bouillard|first2= Laurent|last2=Jouhet|first3=Eric|last3=Thierry |title= Service curves in Network Calculus: dos and don'ts|institution= INRIA|year= 2009|url=https://hal.inria.fr/inria-00431674|number=RR-7094}}

{{cite conference

| url = https://www.di.ens.fr/~bouillar/Publis/curves_wodes.pdf

| title = Comparison of Different Classes of Service Curves in Network Calculus

| last1 = Bouillard

| first1 = Anne

| first2 = Laurent

| last2 = Jouhet

| first3 = Éric

| last3 = Thierry

| conference = 10th International Workshop on Discrete Event Systems (WODES 2010)

| conference-url = http://ti1.control.tu-berlin.de/wodes2010/

| location = Technische Universität Berlin

}}

for an overview.

Let {{math|A}} be an arrival flow, arriving at the ingress of a server, and {{math|D}} be the flow departing at the egress.

The system is said to provide a simple minimal service curve {{math|S}} to the pair {{math|(A,B)}}, if for all {{math|t}} it holds that

$$

D(t) \ge (A \otimes S)(t).

Let {{math|A}} be an arrival flow, arriving at the ingress of a server, and {{math|D}} be the flow departing at the egress.

A backlog period is an interval {{math|I}} such that, on any {{math|t ∈ I}}, {{math|A(t)>D(t)}}.

The system is said to provide a strict minimal service curve {{math|S}} to the pair {{math|(A,B)}} iff, $\backslash forall\; s,t\; \backslash in\; \backslash mathbb\; R^+$, such that $s\; \backslash leq\; t$, if $(s,t]$ is a backlog period, then $D(t)-D(s)\; \backslash geq\; S(t-s)$.

If a server offers a strict minimal service of curve {{math|S}}, it also offers a simple minimal service of curve {{math|S}}.

Depending on the authors, on the purpose of the paper, different notations or even names are used for the same notion.

class="wikitable" |+ Main notations in network calculus
Notions name(s)	Notations	Comments
Cumulative curve	$R,\; A,\; F$	The first papers were using $R$, but $F$ is used for Flow, and $A$ for Arrival.
Input/output pair of curves	$(R\_\{in\},R\_\{out\})$ $(R,R^*)$, $(A,D)$, $(F^\{in\},F^\{out\})$	The input/output curve pair was initially denoted $(R,R^*)$. The naming $(A,D)$ stands for Arrival and Departure. Then naming $(F^\{in\},F^\{out\})$ names input and output flows.
Envelope, Arrival curve	$E,\backslash alpha$	Authors using the term 'Envelope' also use $E$, and conversely with 'Arrival curve' and $\backslash alpha$.
Service curve	$S,\; \backslash beta$	Authors in general use either both $E,\; S$ or both $\backslash alpha,\backslash beta$
Delay, Horizontal deviation	$d(A,D),\; h(A,D),\; hDev(A,D)$	The term 'horizontal deviation' emphasizes on the mathematical definition, whereas 'delay' emphasizes on the semantics.
Backlog, vertical deviation	$b(A,D),\; v(A,D),\; vDev(A,D)$	The term 'vertical deviation' emphasizes on the mathematical definition, whereas 'backlog' emphasizes on the semantics.
Convolution	$*,\; \backslash otimes$
Deconvolution	$\backslash oslash$

From traffic envelope and service curves, some bounds on the delay and backlog, and an envelope on the departure flow can be computed.

Let {{math|A}} be an arrival flow, arriving at the ingress of a server, and {{math|D}} be the flow departing at the egress. If the flow as a traffic envelope {{math|E}}, and the server provides a minimal service of curve {{math|S}}, then the backlog and delay can be bounded:

$$

b(A,D) \leq b(E,S)

$$

d(A,D) \leq d(E,S)

Moreover, the departure curve has envelope $E\text{'}\; =\; E\; \backslash oslash\; S$.

Moreover, these bounds are tight i.e. given some {{math|E}}, and {{math|S}}, one may build an arrival and departure such that

{{math|b(A,D) }} = {{math|b(E,S)}} and {{math|v(A,D)}}={{math|v(E,S)}}.

Consider a sequence of two servers, when the output of the first one is the input of the second one. This sequence can be seen as a new server, built as the concatenation of the two other ones.

Then, if the first (resp. second) server offers a simple minimal service $S\_1$ (resp. $S\_2$), then, the concatenation of both offers a simple minimal service $S\_\{e2e\}\; =\; S\_1\; \backslash otimes\; S\_2$.

File:Network Calculus -- Sequence of servers.svg

The proof does iterative application of the definition of service curves $X\; \backslash ge\; A\; \backslash otimes\; S\_1$, $D\; \backslash ge\; X\; \backslash otimes\; S\_2$ and some properties of convolution, isotonicity ($D\; \backslash geq\; (\; X\; \backslash otimes\; S\_2)\; \backslash otimes\; S\_1$), and associativity ($D\; \backslash geq\; X\; \backslash otimes\; (S\_2\; \backslash otimes\; S\_1)$).

The interest of this result is that the end-to-end delay bound is not greater than the sum of local delays:

$d(E,S\_2\; \backslash otimes\; S\_1)\; \backslash leq\; d(E,S\_1)\; +\; d(E\; \backslash oslash\; S\_1,\; S\_2)$.

This result is known as Pay burst only once (PBOO).

There are several tools based on network calculus. A comparison can be found in.{{cite journal

| last1 = Zhou

| first1 = Boyang

| last2 = Howenstine

| first2 = Isaac

| last3 = Limprapaipong

| first3 = Siraphob

| last4 = Cheng

| first4 = Liang

| title = A Survey on Network Calculus Tools for Network Infrastructure in Real-Time Systems

| journal = IEEE Access

| volume = 8

| publisher = IEEE

| date = December 14, 2020

| pages = 223588–223605

| language = english

| doi = 10.1109/ACCESS.2020.3043600

| bibcode = 2020IEEEA...8v3588Z

| doi-access = free

}}

There exist several tools and library devoted to the min-plus algebra.

• The [http://realtimeatwork.com/minplus-playground# Network calculus interpreter] is an on-line (min,+) interpreter.
• [https://nancy.unipi.it Nancy] is a C# library implementing min-plus and max-plus operations.{{cite journal

| last1 = Zippo

| first1 = Raffaele

| last2 = Stea

| first2 = Giovanni

| title = Nancy: an efficient parallel Network Calculus library

| journal = SoftwareX

| volume = 19

| publisher = Elsevier

| date = June 2022

| page = 101178

| language = english

| doi = 10.1016/j.softx.2022.101178

| arxiv = 2205.11449

| bibcode = 2022SoftX..1901178Z

| doi-access = free

}}

• The MIN-plus ExpRession VErification (Minerve) is a Coq library used to check validity of min-plus operations.

{{cite conference

| title = Verifying min-plus computations with coq

| first1 = Lucien

| last1 = Rakotomalala

| first2 = Marc

| last2 = Boyer

| first3 = Pierre

| last3 = Roux

| year = 2021

| conference = 13th NASA Formal Methods Symposium (NFM 2021)

| conference-url = https://shemesh.larc.nasa.gov/nfm2021

| doi = 10.1007/978-3-030-76384-8

}}

All these tools and library are based on the algorithms presented in.

{{cite journal

| last1 = Bouillard

| first1 = Anne

| last2 = Thierry

| first2 = Eric

| title = An Algorithmic Toolbox for Network Calculus

| journal = Discrete Event Dynamic Systems: Theory and Applications

| volume = 18

| pages = 3–49

| date = 2008

| url = http://dl.acm.org/citation.cfm?id=2872494

| doi = 10.1007/s10626-007-0028-x

| s2cid = 14643542

}}

• The [http://discodnc.cs.uni-kl.de DiscoDNC] is an academic Java implementation of the network calculus framework.

{{cite conference

| url = http://disco.informatik.uni-kl.de/discofiles/publicationsfiles/BS14.pdf

| title = The DiscoDNC v2 – A Comprehensive Tool for Deterministic Network Calculus

| first1 = Steffen

| last1 = Bondorf

| first2 = Jens B.

| last2 = Schmitt

| year = 2014

| conference = 8th International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS 2014)

| conference-url = https://duckduckgo.com/l/?kh=-1&uddg=http%3A%2F%2Fvaluetools.org%2F2014%2F

}}

• The [http://www.mpa.ethz.ch/ RTC Toolbox] is an academic Java/MATLAB implementation of the Real-Time calculus framework, a theory quasi equivalent to network calculus.{{cite conference

| url = https://doi.org/10.1109/ISCAS.2000.858698

| title = Real-Time Calculus for Scheduling Hard Real-Time Systems

| last1 = Thiele

| first1 = Lothar

| first2 = Samarjit

| last2 = Chakraborty

| first3 = Martin

| last3 = Naedele

| conference = IEEE International Symposium on Circuits and Systems (ISCAS) 2000

| conference-url = https://doi.org/10.1109/ISCAS.2000.857009

| location = Geneva, Switzerland

| doi = 10.1109/ISCAS.2000.858698

}}

• The [http://kom.aau.dk/~henrik/old-control/CyNC_2.0/ CyNC]{{cite conference

| title= CyNC: A MATLAB/SimuLink Toolbox for Network Calculus

| url = http://dl.acm.org/citation.cfm?id=1345263.1345340

| first1= Henrik

| last1= Schioler

| first2= Hans P.

| last2= Schwefel

| first3= Martin B.

| last3= Hansen

| year= 2007

| conference= 2nd International Conference on Performance Evaluation Methodologies and Tools (ValueTools '07)

}} tool is an academic MATLAB/Symulink toolbox, based on top of the [http://www.mpa.ethz.ch/Rtctoolbox RTC Toolbox]. The tool was developed in 2004-2008 and it is currently used for teaching at Aalborg university.

• The [http://www.realtimeatwork.com/software/rtaw-pegase RTaW-PEGASE] is an industrial tool devoted to timing analysis tool of switched Ethernet network (AFDX, industrial and automotive Ethernet), based on network calculus.

{{cite conference

| url = http://www.realtimeatwork.com/wp-content/uploads/TR_SAE_Aerotech_2011.pdf

| title = PEGASE, A Robust and Efficient Tool for Worst Case Network Traversal Time

| first1 = Marc

| last1 = Boyer

| first2 = Jörn

| last2 = Migge

| first3 = Marc

| last3 = Fumey

| year = 2011

| conference = SAE 2011 AeroTech Congress & Exhibition

}}

• [https://github.com/Kathess/DYRECTsn DYRECTsn] is a Python-based academic tool for dynamic flows in Time-Sensitive Networking (TSN). It includes offline optimization of the network, as well as online admission control for real-time flows.{{cite book

| last1 = Maile

| first1 = Lisa

| last2 = Hielscher

| first2 = Kai-Steffen

| last3 = German

| first3 = Reinhard

| year = 2024

| chapter = Combining Static and Dynamic Traffic with Delay Guarantees in Time-Sensitive Networking

| editor-last1 = Kalyvianaki

| editor-first1 = Eleni

| editor-last2 = Paolieri

| editor-first2 = Martina

| title = Performance Evaluation Methodologies and Tools

| series = Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

| volume = 539

| pages = 117–132

| publisher = Springer, Cham

| doi = 10.1007/978-3-031-48885-6_8

| isbn = 978-3-031-48884-9

}}

• The [http://websites.isae.fr/wopanets/ WOPANets] is an academic tool combining network calculus based analysis and optimization analysis.

{{cite conference

| title = WOPANets: A tool for WOrst case Performance Analysis of embedded Networks

| first1 = Ahlem

| last1 = Mifdaoui

| first2 = H.

| last2 = Ayed

| year = 2010

| conference = 15th IEEE International Workshop on Computer Aided Modeling, Analysis and Design of Communication Links and Networks (CAMAD)

| conference-url = http://camad.it.ubi.pt/

|doi = 10.1109/CAMAD.2010.5686958}}

• The DelayLyzer is an industrial tool designed to compute bounds for Profinet networks.

{{cite conference

| title = DelayLyzer: A Tool for Analyzing Delay Bounds in Industrial Ethernet Networks

| first1 = Mark

| last1 = Schmidt

| first2 = Sebastian

| last2 = Veith

| first3 = Michael

| last3 = Menth

| first4 = Stephan

| last4 = Kehrer

| year = 2014

| conference = 17th Int. GI/ITG Conf. on Measurement, Modelling, and Evaluation of Computing Systems and Dependability and Fault Tolerance (MMB & DFT 2014)

| conference-url = http://www.mmb2014.de/

| doi = 10.1007/978-3-319-05359-2_19

}}

• [http://cng1.iet.unipi.it/wiki/index.php/Deborah DEBORAH] is an academic tool devoted to FIFO networks.

{{cite conference

| title = DEBORAH: A Tool for Worst-Case Analysis of FIFO Tandems

| first1 = Luca

| last1 = Bisti

| first2 = Luciano

| last2 = Lenzini

| first3 = Enzo

| last3 = Mingozzi

| first4 = Giovanni

| last4 = Stea

| year = 2012

| conference = International Symposium On Leveraging Applications of Formal Methods, Verification and Validation

| conference-url = http://www.isola-conference.org/isola2010/

| doi = 10.1007/978-3-642-16558-0_15

}}

• [https://github.com/annebouillard/NetCalBounds NetCalBounds] is an academic tool devoted to blind & FIFO tandem networks.

{{cite journal

| last1 = Bouillard

| first1 = Anne

| last2 = Stea

| first2 = Giovanni

| title = Exact worst-case delay in FIFO-multiplexing feed-forward networks

| journal = IEEE/ACM Transactions on Networking

| volume = 23

| issue = 5

| pages = 1387–1400

| date = October 2015

| url = http://dl.acm.org/citation.cfm?id=2872494

| doi = 10.1109/TNET.2014.2332071 | hdl = 11568/501671

| s2cid = 14216975

| hdl-access = free

}}

{{cite journal

| last1 = Bouillard

| first1 = Anne

| last2 = Éric

| first2 = Thierry

| title = Tight performance bounds in the worst-case analysis of feed-forward networks

| journal = Discrete Event Dynamic Systems

| volume = 26

| issue = 3

| pages = 383–411

| date = September 2016

| doi = 10.1007/s10626-015-0213-2

| s2cid = 40699209

| url = https://hal.inria.fr/hal-01583622/file/jdeds-lp.pdf

}}

• [https://github.com/nokia/NCBounds NCBounds] is a network calculus tool in Python, published under BSD 3-Clause License. It considers rate-latency servers and token-bucket arrival curves. It handles any topology, including cyclic ones.{{cite conference

| title = Stability and performance bounds in cyclic networks using network calculus

| first1 = Anne

| last1 = Bouillard

| year = 2019

| conference = 17th International Conference on Formal Modeling and Analysis of Timed Systems

| conference-url = https://lipn.univ-paris13.fr/formats2019/

}}

• The Siemens Network Planner ([https://www.siemens.com/global/en/home/products/automation/industrial-communication/profinet/portfolio/sinetplan.html SINETPLAN]) uses network calculus (among other methods) to help the design of a PROFINET network.{{cite conference

| title = The need for shaping non-time-critical data in PROFINET networks

| first1 = Sven

| last1 = Kerschbaum

| first2 = Kai-Steffen

| last2 = Hielscher

| first3 = Reinhard

| last3 = German

| year = 2016

| conference = 14th IEEE International Conference on Industrial Informatics (INDIN)

| conference-url = https://ieee-indin2016.sciencesconf.org/

| doi = 10.1109/INDIN.2016.7819151

}}

• [https://gitlab.isae-supaero.fr/l.thomas/xtfa experimental modular TFA] (xTFA) is a Python code, support of the PhD thesis of Ludovic Thomas

{{cite thesis

|last= Thomas

|first= Ludovic

|date= September 2022

|title= Analysis of the side-effects on latency bounds of combinations of scheduling, redundancy and synchronization mechanisms in time-sensitive networks.

|type= Doctorat de l'université de Toulouse}}

• [https://github.com/Huawei-Paris-Research-Center/panco Panco] is a Python code that computes network calculus bounds with linear programming methods.
• [https://github.com/adfeel220/Saihu-TSN-Analysis-Tool-Integration Saihu] is a Python interface that integrates three worst-case network analysis tools: xTFA, DiscoDNC, and [https://github.com/Huawei-Paris-Research-Center/panco Panco].
• [https://projects.csail.mit.edu/ccac/ CCAC] is an SMT-solver based tool to verify the performance properties of congestion control algorithms (CCAs) using a network-calculus-like model
• [https://github.com/soniaakash/Performance-Analysis-and-Optimisation-Tools-for-AFDX-network AFDX Performance Analysis Tool] is a group of tools developed for analysis and optimisation of AFDX network with FIFO, SPQ, DRR and WRR scheduling, written in C++, in support of the PhD thesis of Aakash SONI {{Cite thesis |last=Soni |first=Aakash |title=Real-time performance analysis of a QoS based industrial embedded network |date=2020-05-06 |degree=thesis |publisher=Toulouse, INPT |url=https://theses.fr/2020INPT0047 |language=fr}}

[https://plassart.github.io/WoNeCa/ WoNeCa workshop] is a Workshop on Network Calculus. It is organized every two years to bring together researchers with an interest in the theory of network calculus as well as those who want to apply existing results to new applications. The workshop also serves to promote the network calculus theory to researchers with an interest in applied queueing models.

• [https://itc36.itc-conference.org/woneca.html WoNeCa7], was held in Trondheim, Norway as a part of the [https://itc36.itc-conference.org 36th International Teletraffic Congress] (ITC 36).
• [https://plassart.github.io/WoNeCa/2022/ WoNeCa6], hosted by EPFL, is scheduled on September 8 and 9th, 2022 in Lausanne, Switzerland. Call for presentation [http://2022.woneca.org here].
• [https://disco.cs.uni-kl.de/index.php/woneca-2020 WoNeCa5] was held virtually due to the COVID-19 pandemic on October 9, 2020.
• [https://disco.cs.uni-kl.de/index.php/woneca-2018 WoNeCa4] was organized in conjunction with the 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB2018) on February 28, 2018, in Erlangen, Germany.
• [https://disco.cs.uni-kl.de/index.php/woneca-2016 WoNeCa3] was held in as a part of the MMB & DFT 2016 conference on April 6, 2016, in Müster, Germany.
• [https://disco.cs.uni-kl.de/index.php/woneca-2014 WoNeCa2] was held within the MMB & DFT 2014 conference on March 19, 2014, in Bamberg, Germany.
• [http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=18210 WoNeCa1] was hosted by University of Kaiserslautern and was held as a part of MMB2012 on March 21, 2012, in Kaiserslautern, Germany.

In 2018, [https://archive.itc-conference.org/itc30/en/workshops/netcal.html International Workshop on Network Calculus and Applications] (NetCal 2018) was held in Vienna, Austria as a part of the 30th [https://itc-conference.org International Teletraffic Congress] (ITC 30).

In 2024, the [https://www.dagstuhl.de/en/seminars/seminar-calendar/seminar-details/24141 network calculus Dagstuhl seminar (24141)] was held from 1 April to 4 April in Dagstuhl, Germany.

;Books, Surveys, and Tutorials on Network Calculus

• C.-S. Chang: Performance Guarantees in Communications Networks, Springer, 2000.
• J.-Y. Le Boudec and P. Thiran: [https://leboudec.github.io/netcal/ Network Calculus: A Theory of Deterministic Queuing Systems for the Internet], Springer, LNCS, 2001 (available online).
• A. Bouillard, M. Boyer, E. Le Corronc: [https://www.wiley.com/Deterministic+Network+Calculus:+From+Theory+to+Practical+Implementation-p-9781119563419 Deterministic Network Calculus: From Theory to Practical Implementation], Wiley-ISTE, 2018
• Y. Jiang and Y. Liu: Stochastic Network Calculus, Springer, 2008.
• A. Kumar, D. Manjunath, and J. Kuri: Communication Networking: An Analytical Approach, Elsevier, 2004.
• S. Mao and S. Panwar: A survey of envelope processes and their applications in quality of service provisioning, IEEE Communications Surveys and Tutorials, 8(3):2-20, July 2006.
• M. Fidler: [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5415864 Survey of deterministic and stochastic service curve models in the network calculus], IEEE Communications Surveys and Tutorials, 12(1):59-86, January 2010.
• C. Lin, Y. Deng, and Y. Jiang: On applying stochastic network calculus, Frontiers Computer Science, 7(6): 924-942, 2013
• M. Fidler and A. Rizk: [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6868978 A guide to the stochastic network calculus], IEEE Communications Surveys and Tutorials, 17(1):92-105, March 2015.
• L. Maile, K. Hielscher and R. German: [https://ieeexplore.ieee.org/document/9123308 Network Calculus Results for TSN: An Introduction], IEEE Information Communication Technologies Conference(1): 131-140, May 2020.

;Related books on the max-plus algebra or on convex minimization

• R. T. Rockafellar: Convex analysis, Princeton University Press, 1972.
• F. Baccelli, G. Cohen, G. J. Olsder, and J.-P. Quadrat: Synchronization and Linearity: An Algebra for Discrete Event Systems, Wiley, 1992.
• V. N. Kolokol'tsov, Victor P. Maslov: Idempotent Analysis and Its Applications, Springer, 1997. {{ISBN|0792345096}}.

;Deterministic network calculus

• R. L. Cruz: {{doi-inline|10.1109/18.61109|A Calculus for Network Delay. Part I: Network Elements in Isolation}} and {{doi-inline|10.1109/18.61110|Part II: Network Analysis}}, IEEE Transactions on Information Theory, 37(1):114-141, Jan. 1991.
• A. K. Parekh and R. G. Gallager: A Generalized Processor Sharing Approach to Flow Control : The Multiple Node Case, IEEE Transactions on Networking, 2 (2):137-150, April 1994.
• C.-S. Chang: Stability, Queue Length and Delay of Deterministic and Stochastic Queueing Networks, IEEE Transactions on Automatic Control, 39(5):913-931, May 1994.
• D. E. Wrege, E. W. Knightly, H. Zhang, and J. Liebeherr: Deterministic delay bounds for VBR video in packet-switching networks: Fundamental limits and practical tradeoffs, IEEE/ACM Transactions on Networking, 4(3):352-362, Jun. 1996.
• R. L. Cruz: SCED+: Efficient Management of Quality of Service Guarantees, IEEE INFOCOM, pp. 625–634, Mar. 1998.
• J.-Y. Le Boudec: Application of Network Calculus to Guaranteed Service Networks, IEEE Transactions on Information Theory, 44(3):1087-1096, May 1998.
• C.-S. Chang: On Deterministic Traffic Regulation and Service Guarantees: A Systematic Approach by Filtering, IEEE Transactions on Information Theory, 44(3):1097-1110, May 1998.
• R. Agrawal, R. L. Cruz, C. Okino, and R. Rajan: Performance Bounds for Flow Control Protocols, IEEE/ACM Transactions on Networking, 7(3):310-323, Jun. 1999.
• J.-Y. Le Boudec: Some properties of variable length packet shapers, IEEE/ACM Transactions on Networking, 10(3):329-337, Jun. 2002.
• C.-S. Chang, R. L. Cruz, J.-Y. Le Boudec, and P. Thiran: A Min, + System Theory for Constrained Traffic Regulation and Dynamic Service Guarantees, IEEE/ACM Transactions on Networking, 10(6):805-817, Dec. 2002.
• Y. Jiang: Relationship between guaranteed rate server and latency rate server, Computer Networks 43(3): 307-315, 2003.
• M. Fidler and S. Recker: Conjugate network calculus: A dual approach applying the Legendre transform, Computer Networks, 50(8):1026-1039, Jun. 2006.
• Eitan Altman, Kostya Avrachenkov, and Chadi Barakat: TCP network calculus: The case of large bandwidth-delay product, In proceedings of IEEE INFOCOM, NY, June 2002.
• J. Liebeherr: Duality of the Max-Plus and Min-Plus Network Calculus, Foundations and Trends in Networking 11(3-4): 139-282, 2017.

;Network topologies, feed-forward networks

• A. Charny and J.-Y. Le Boudec: Delay Bounds in a Network with Aggregate Scheduling, QoFIS, pp. 1–13, Sep. 2000.
• D. Starobinski, M. Karpovsky, and L. Zakrevski: Application of Network Calculus to General Topologies using Turn-Prohibition, IEEE/ACM Transactions on Networking, 11(3):411-421, Jun. 2003.
• M. Fidler: A parameter based admission control for differentiated services networks, Computer Networks, 44(4):463-479, March 2004.
• L. Lenzini, L. Martorini, E. Mingozzi, and G. Stea: Tight end-to-end per-flow delay bounds in FIFO multiplexing sink-tree networks, Performance Evaluation, 63(9-10):956-987, October 2006.
• J. Schmitt, F. Zdarsky, and M. Fidler: Delay bounds under arbitrary multiplexing: when network calculus leaves you in the lurch ..., Prof. IEEE Infocom, April 2008.
• A. Bouillard, L. Jouhet, and E. Thierry: Tight performance bounds in the worst-case analysis of feed-forward networks, Proc. IEEE Infocom, April 2010.

;Measurement-based system identification

• C. Cetinkaya, V. Kanodia, and E.W. Knightly: Scalable services via egress admission control, IEEE Transactions on Multimedia, 3(1):69-81, March 2001.
• S. Valaee, and B. Li: Distributed call admission control for ad hoc networks, Proc. of IEEE VTC, pp. 1244–1248, 2002.
• A. Undheim, Y. Jiang, and P. J. Emstad. Network Calculus Approach to Router Modeling with External Measurements, Proc. of IEEE Second International Conference on Communications and Networking in China (Chinacom), August 2007.
• J. Liebeherr, M. Fidler, and S. Valaee: A system-theoretic approach to bandwidth estimation, IEEE Transactions on Networking, 18(4):1040-1053, August 2010.
• M. Bredel, Z. Bozakov, and Y. Jiang: Analyzing router performance using network calculus with external measurements, Proc. IEEE IWQoS, June 2010.
• R. Lubben, M. Fidler, and J. Liebeherr: Stochastic bandwidth estimation in networks with random service, IEEE Transactions on Networking, 22(2):484-497, April 2014.

;Stochastic network calculus

• O. Yaron and M. Sidi: Performance and Stability of Communication Networks via Robust Exponential Bounds, IEEE/ACM Transactions on Networking, 1(3):372-385, Jun. 1993.
• D. Starobinski and M. Sidi: Stochastically Bounded Burstiness for Communication Networks, IEEE Transactions on Information Theory, 46(1):206-212, Jan. 2000.
• C.-S. Chang: Stability, Queue Length and Delay of Deterministic and Stochastic Queueing Networks, IEEE Transactions on Automatic Control, 39(5):913-931, May 1994.
• R.-R. Boorstyn, A. Burchard, J. Liebeherr, and C. Oottamakorn: Statistical Service Assurances for Traffic Scheduling Algorithms, IEEE Journal on Selected Areas in Communications, 18(12):2651-2664, Dec. 2000.
• Q. Yin, Y. Jiang, S. Jiang, and P. Y. Kong: Analysis of Generalized Stochastically Bounded Bursty Traffic for Communication Networks, IEEE LCN, pp. 141–149, Nov. 2002.
• C. Li, A. Burchard, and J. Liebeherr: A Network Calculus with Effective Bandwidth, University of Virginia, Technical Report CS-2003-20, Nov. 2003.
• Y. Jiang: A basic stochastic network calculus, ACM SIGCOMM 2006.
• A. Burchard, J. Liebeherr, and S. D. Patek: A Min-Plus Calculus for End-to-end Statistical Service Guarantees, IEEE Transactions on Information Theory, 52(9):4105–4114, Sep. 2006.
• F. Ciucu, A. Burchard, and J. Liebeherr: A Network Service Curve Approach for the Stochastic Analysis of Networks, IEEE/ACM Transactions on Networking, 52(6):2300–2312, Jun. 2006.
• M. Fidler: An End-to-End Probabilistic Network Calculus with Moment Generating Functions, IEEE IWQoS, Jun. 2006.
• Y. Liu, C.-K. Tham, and Y. Jiang: A calculus for stochastic QoS analysis, Performance Evaluation, 64(6): 547-572, 2007.
• Y. Jiang and Y. Liu: Stochastic Network Calculus, Springer, 2008.

;Wireless network calculus

• M. Fidler: A Network Calculus Approach to Probabilistic Quality of Service Analysis of Fading Channels, Proc. IEEE Globecom, November 2006.
• K. Mahmood, A. Rizk, and Y. Jiang: On the Flow-Level Delay of a Spatial Multiplexing MIMO Wireless Channel, Proc. IEEE ICC, June 2011.
• K. Mahmood, M. Vehkaperä, and Y. Jiang: Delay Constrained Throughput Analysis of a Correlated MIMO Wireless Channel, Proc. IEEE ICCCN, 2011.
• K. Mahmood, M. Vehkaperä, and Y. Jiang: Delay constrained throughput analysis of CDMA using stochastic network calculus, Proc. IEEE ICON, 2011.
• K. Mahmood, M. Vehkaperä, and Y. Jiang: Performance of multiuser CDMA receivers with bursty traffic and delay constraints, Proc. ICNC, 2012.
• Y. Zhang and Y. Jiang: Performance of data transmission over a Gaussian channel with dispersion, Proc. ISWCS, 2012.
• H. Al-Zubaidy, J. Liebeherr, and A. Burchard: A (min, ×) network calculus for multi-hop fading channels, Proc. IEEE Infocom, pp. 1833–1841, April 2013.
• K. Zheng, F. Liu, L. Lei, C. Lin, and Y. Jiang: Stochastic Performance Analysis of a Wireless Finite-State Markov Channel, IEEE Trans. Wireless Communications 12(2): 782-793, 2013.
• J.-w. Cho and Y. Jiang: Fundamentals of the Backoff Process in 802.11: Dichotomy of the Aggregation, IEEE Trans. Information Theory 61(4): 1687-1701, 2015.
• M. Fidler, R. Lubben, and N. Becker: [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6940302 Capacity–Delay–Error Boundaries: A Composable Model of Sources and Systems], Transactions on Wireless Communications, 14(3):1280-1294, March 2015.
• F. Sun and Y. Jiang: A Statistical Property of Wireless Channel Capacity: Theory and Application, Proc. IFIP Performance, 2017.

{{Reflist}}

Category:Network performance

Category:Computer network analysis