DHL: Dynamic His o y Leng h o Packe O de
Reco e y in Time-Sensi i e Ne wo ks
How-Hang Liu ∗, Hosein K. Naza i ∗, Tobias Scheine ∗, S e an Senk ∗,
Giang T. Nguyen †, F ank H. P. Fi zek ‡
∗Deu sche Telekom Chai o Communica ion Ne wo ks, TU D esden, Ge many
†Chai o Hap ic Communica ion Sys ems, TU D esden, Ge many
‡Cen e o Tac ile In e ne wi h Human-in- he-Loop (CeTI), TU D esden, Ge many
E-mails: { i s name.las name}@ u-d esden.de∗†‡
Abs ac —The in eg a ion o 6G and Time-Sensi i e Ne wo k-
ing (TSN) is desi ed o p o ide bo h mobili y and de e minis ic
communica ion. In TSN, F ame Replica ion and Elimina ion o
Reliabili y (FRER) imp o es s eam esilience using edundan
pa hs. Howe e , he o iginal FRER wi h a ixed his o y leng h is
ine ec i e when acing a iable-delay links ha cause eo de ing
and bu s y a i als o packe s. We p opose he Dynamic His o y
Leng h (DHL) algo i hm ha dynamically adjus s he FRER
elimina ion bu e based on eal- ime link delay measu emen s.
We implemen and e alua e DHL in OMNeT++/INET, which
p o ides a comp ehensi e and high-accu acy model o TSN
swi ches. We compa e DHL wi h he FRER a ia ions. In a 100 ms
dual-link simula ion wi h la ency amps and a 10 ms ou age,
DHL educes duplica e packe deli e ies by 39 % compa ed o
baseline. In e ms o he 99 h pe cen ile in e -a i al in e als,
DHL shows an imp o emen o 4.3 ms compa ed o he so ing
and shaping algo i hm, allowing i o be e ma ch he sende ’s
1 ms ansmission in e al.
Index Te ms—Time-Sensi i e Ne wo king (TSN), F ame Repli-
ca ion and Elimina ion o Reliabili y (FRER), OMNeT++
I. INTRODUCTION
The ad en o 6G [1] has ans o med he indus ial land-
scape, d i ing Indus y 4.0 inno a ions by enabling new use
cases and e enue s eams beyond adi ional consume ma -
ke s. Eme ging applica ions, such as lexible manu ac u ing and
obo ics [2], demand ul a-low la ency, de e minis ic commu-
nica ion, and high eliabili y o ensu e seamless ope a ion. To
mee hese s ingen equi emen s, he in eg a ion o 6G mobile
communica ion wi h TSN [3] has eme ged as a p omising
solu ion, combining he mobili y o wi eless 6G ne wo ks
wi h he de e minis ic gua an ees o TSN. This syne gy o e s
signi ican bene i s o no el use cases bu emains an open
esea ch p oblem due o he challenges o main aining end- o-
end synch oniza ion and eliabili y ac oss he e ogeneous wi ed
and wi eless domains.
TSN, o iginally designed o wi ed ne wo ks, p o ides de-
e minis ic communica ion h ough s anda ds such as IEEE
802.1CB, which implemen s FRER [4]. FRER enhances e-
liabili y by duplica ing ames ac oss edundan links a a
duplica ion node and elimina ing duplica es a an elimina ion
node, as illus a ed in Fig. 1. This mechanism ensu es obus
deli e y in wi ed TSN en i onmen s, such as indus ial con ol
sys ems. Howe e , ex ending TSN p inciples o 6G ne wo ks
in oduces signi ican challenges. In 6G-TSN scena ios, whe e
he 6G ne wo k ac s as a i ual link wi hin he TSN domain,
wi eless channels in oduce unp edic able delays and po en ial
disconnec ions. These a ia ions can signi ican ly impai he
e ec i eness o FRER, as delayed o los ames dis up
he elimina ion p ocess, leading o packe loss o unin ended
duplica ion ha can deg ade applica ion pe o mance.
A common app oach o mi iga e delayed o los ames in
TSN sys ems is o employ la ge bu e s a swi ches o main ain
an ex ended his o y o sequence numbe s. While his s a egy
can imp o e eliabili y by accommoda ing delayed ames, i
equi es cos ly ha dwa e upg ades and inc eases p ocessing
imes due o la ge his o y leng hs, which may comp omise
he s ingen la ency equi emen s o 6G-TSN applica ions.
Fu he mo e, he li e a u e highligh s addi ional challenges
wi h FRER, including issues wi h ame eo de ing and bu s
ansmission unde ce ain condi ions [5]–[7], exace ba ing he
complexi y o ensu ing de e minis ic communica ion in 6G-
TSN en i onmen s.
To ackle hese issues, we p opose a no el FRER elimina ion
algo i hm, namely DHL. DHL dynamically adjus s he his o y
leng h in he bu e on he ly, only inc eases he leng h when
i is absolu ely equi ed. To p ecise adjus men o he his o y
leng h DHL con inuously measu e link condi ions ega ding
delay. Op ionally, DHL can imco po a e so ing and shaping
unc ions a he elimina ion node. These mi iga e ame eo de -
ing and bu s ansmission [5]–[7]. We in eg a ed he algo i hm
in o OMNeT++ by ex ending a TSN module. This enables
e icien 6G-TSN sys em e alua ion. We alida ed i using
li e a u e-based scena ios [7]. These included a ying link
delays and simula ed link ailu es. Ou esul s show educed
duplica ion a es 39 %. They also indica e ewe ou -o -o de
ames and less ecei ing ji e wi h he educ ion a es 40 %
and 35 %, espec i ely.
To acili a e eplica ing he p oposed DHL in u u e e-
sea ch we ha e ex ended he open-sou ce oolki in OMNeT++
©2025 IEEE. Pe sonal use o his ma e ial is pe mi ed. Pe mission om IEEE mus be ob ained o all o he uses, in any cu en o u u e media, including
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euse o any copy igh ed componen o his wo k in o he wo ks.
Sende Recei e
Swi ch 1 Swi ch 2
Sequence
Reco e y
Func ion
(SRF)
Sequence
Gene a ion
Func ion
Fas Pa h
Slow Pa h
123
1'
2'
3'
TPID
(2 by es)
Rese ed
(2 by es)
SeqNum
(2 by es)
R-Tag
1
2
3
Fig. 1. This igu e illus a es he in eg a ion o a nex -gene a ion mobile
ne wo k wi h TSN. I highligh s a basic FRER wo k low: he duplica ion node
add ags and duplica es each packe using a sequence-gene a ion mechanism,
while he elimina ion node applies sequence- eco e y logic o iden i y and
disca d any duplica e packe s.
and eleased he sou ce code o he esea ch communi y:
h ps://gi hub.com/TUDComne sTSN/FRER_so ing_shaping.
II. BACKGROUND AND RELATED WORK
In his sec ion, we will p o ide a b ie o e iew o he
common algo i hms u ilized in he Sequence Reco e y Func-
ion (SRF). Nex , we highligh he scena ios ha lead o he
c acks in FRER, speci ically ocusing on eo de ing and bu s
ansmission. Following ha , we p esen a gene al pe spec i e
on he cu en esea ch ocuses ela ed o 5G and FRER, as
well as he exis ing implemen a ions o FRER in OMNeT++.
As shown in Fig. 1, he sequence gene a ion unc ion a -
aches a 6-by e edundancy ag (R- ag) o he 802.1Q heade .
The TPID is 0xF1C1 [4], wi h a ese ed ield o u u e
use. The las 2 by es hold he sequence numbe , iden ical o
duplica e packe s. The SRF can use ei he he Ma ch Reco e y
Algo i hm (MRA) o Vec o Reco e y Algo i hm (VRA) o
emo e duplica e packe s by sequence numbe . This pape
ocuses solely on he MRA; he VRA is ou o scope.
The undamen al concep o MRA is illus a ed in Fig. 2. The
MRA p ima ily s o es he highes sequence numbe ecei ed
and compa es i wi h he nex incoming sequence numbe . I
he incoming numbe ma ches he highes sequence numbe , he
MRA disca ds he duplica e packe s; o he wise, i o wa ds he
packe s as usual [4]. Fo example, as shown in Fig. 2, he sende
ansmi s packe s a egula in e als. I is impo an o no e ha
po 1 is connec ed o a as e link, while po 2 expe iences
g ea e delays. A ime uni 2, he MRA ecei es bo h packe 1
and packe 1’ om he di e en po s, success ully elimina ing
he duplica e. Simila ly, a ime uni 8, ano he duplica e
elimina ion occu s o he packe wi h sequence numbe 4.
Howe e , he MRA is limi ed when packe s expe ience la ge
delays. Fo ins ance, a ime uni 5, he highes sequence
numbe acknowledged is 4. I packe 2’ a i es la e om he
slowe pa h, he MRA will no disca d i , as i is s ill conside ed
Sende
Ing ess po 1
Ing ess po 2
MRA (Leng h 2)
Eg ess po 3
1Time Uni 2 3 4 5 6 7 8 9 10 11
1 2 3 4 5 7 8 9 10 11
1234567 8910
Packe s Los
1' 2' 3' 4' 5'
1 1'
123
Elimina e Duplica e
2 3 4 2'
4 2'
4 3'
3'
4 4'
Elimina e Duplica e
7 5' 8 6' 9 7'
7 5' 8 6' 9 7' 10
Bu s Duplica e
6' 7'
6
Fig. 2. Illus a ion o he MRA algo i hm in FRER. Ing ess po s 1 and 2,
along wi h Eg ess po 3, co espond o he po s on swi ch 2 depic ed in Fig. 1.
Ing ess po s 1 and 2 a e connec ed o he as link and slow link, espec i ely.
Eg ess po 3 is a e he ope a ion o MRA and is connec ed o he ecei e .
We index o iginal packe s by iand deno e hei duplica es by i′.
alid despi e he ac ha packe 2 was al eady accep ed a ime
uni 2.
A u he challenge a ises o bo h MRA and VRA [5]–
[7] when he as link expe iences packe loss and subsequen
eco e y, causing alid sequence numbe s o be ecei ed and
o wa ded om bo h he as and slow links. As obse ed a
ime uni s 9 and 10, a e he SRF, he sequence numbe s
o wa ded by he eg ess po a e ou o o de (5’, 8, 6’, 9).
In his scena io, he eg ess po o wa ds a bu s o packe s.
O iginally, he sende ansmi ed one packe pe ime uni ,
bu now wo packe s a i e in a single ime uni . This occu s
because some packe s (5, 6) a e los on he as link, and
hei duplica e packe s (5’, 6’) a e e en ually ecei ed om he
ing ess po 2, highe sequence numbe packe s (8, 9) con inue
o a i e om he ing ess po 1 simul aneously. As a esul ,
alid packe s om bo h ing ess po s may be accep ed wi hin
he same ime uni . No e ha he bu s and diso de si ua ion o
VRA in he igu e did no occu ; howe e , i he his o y leng h
eaches 4, hen he bu s issue will a ise.
Resea ch on in eg a ing 5G/6G wi h FRER can be g ouped
in o wo main di ec ions. The i s di ec ion includes building
a eal ha dwa e es bed o a ious use case scena ios, such as
au onomous mobile obo s [8], milling p ocess applica ions [9],
and oil ield ope a ions in pe ochemical con ex s [10]. The sec-
ond di ec ion includes designing scheduling algo i hms o se-
lec ing and ou ing a ic ac oss mul iple edundan pa hs. Such
algo i hms, o example, can be applied in space– e es ial
ne wo ks [11] o in- ehicle ne wo ks [12]. In addi ion o de el-
oping es beds and designing scheduling algo i hms, Aijaz [13]
has implemen ed a simula ion app oach o e alua e FRER
wi h 5G. This esea ch ocuses speci ically on he 5G domain,
discussing duplica ion and elimina ion poin s ac oss a ious 5G
componen s and p o ocol laye s.
Unlike he p e iously men ioned s udies, ou ocus is speci -
ically on eco e y algo i hms o FRER. To he bes o ou
knowledge, he only s udy add essing issues in FRER eco e y
algo i hms is [7], which applies ne wo k calculus on abs ac
models o e alua e he wo s -case impac o adding so ing
and shaping unc ions a e he elimina ion unc ion. Howe e ,
he p esen ed app oach is based on a ixed his o y leng h
and lacks de ailed implemen a ion guidance. Fu he mo e, i s
shaping unc ion elies on ATS, which is a ely implemen ed
in comme cial ha dwa e due o i s complexi y.
Rega ding he OMNeT++ wi h he FRER implemen a ion,
only a ew s udies ha e been conduc ed in his a ea [5],
[14], and bo h we e eleased be o e he o icial in oduc ion o
FRER unc ionali y in he OMNeT++ INET lib a y. One s udy
implemen ed FRER in OMNeT++ wi h con ol-plane capabili-
ies [14], while ano he iden i ied issues in FRER p o ocols bu
did no add ess bu s y o eo de ed ansmissions [5].
In summa y, his wo k ocuses on he algo i hm in he SRF
o educe he accep ance o duplica e packe s. Mo eo e , we
implemen ed he so ing and shaping algo i hm a e he SRF
o add ess he diso de and bu s ansmission p oblems, based
on he mainline elease o he OMNeT++ INET lib a y o
FRER.
III. DHL – DYNAMIC HISTORY LENGTH
The bu e needs o s o e ba ches o packe s o eo de hem
and elimina e duplica ed packe s. The bu e ’s his o y leng h
has o mee wo design cons ain s. To minimize la ency, he
his o y leng h o he bu e has o be minimized. Howe e ,
sho his o y leng hs a e insu icien o accommoda e packe s
om di e en links wi h la ge la ency disc epancies, inc easing
he likelihood o duplica e packe s. The DHL in oduces he
idea o a iable his o y leng h o he bu e . DHL algo i hm
con inuously measu es he la ency ha each packe expe iences
om a ious links and adjus s he his o y leng h acco ding o
he disc epancies be ween hei la encies.
A. Dynamic His o y Leng h
As shown in Algo i hm 1, DHL conside s he la ency o
measu emen links. When he e a e signi ican la ency di e -
ences be ween he links, he likelihood o accep ing a duplica e
sequence numbe inc eases. As a esul , we need o ex end he
his o y leng h. Con e sely, i he di e ences a e smalle , we
can educe he his o y leng h.
I his ea u e is enabled, he algo i hm is execu ed e e y τ
seconds o upda e he his o y leng h. In line 2, we compu e
he obse ed delay di e ence be ween he links, and in line
3, ansla e his span in o he equi ed window size acco ding
o he o mula in [5], whe e ˆ
Bis he p oposed new leng h o
he his o y window W. Line 4 en o ces a minimum capaci y
o wo, and lines 5–8 hen adjus he his o y leng h B. I
he upda ed ˆ
Bis smalle hen B, hen we educe he alue
smoo hly by conside ing he a e age o he upda ed ˆ
Band
p e ious alue Bin line 7. O he wise, line 7 g ows immedia ely
by assigning B←ˆ
B. Finally, lines 10–11 p une he exis ing
sliding window Wdown o he upda ed capaci y by epea edly
calling emo eF on (W)un il |W| ≤ B.
Algo i hm 1: Dynamic His o y Leng h
Inpu : B,W: cu en his o y window o s o ed
sequence numbe s, minDelay,maxDelay:
obse ed link-delay ex emes, J: Ji e , ∆ :
sende ’s in e -packe in e al (ms), τ: ime
in e al
Ou pu : upda ed window capaci y B, p uned his o y
window W
1E e y τseconds ( ime e en ):
2δ←(maxDelay −minDelay) + J// delay span
3ˆ
B← ⌈(δ×10−3)/∆ ⌉// needed slo s
4i ˆ
B < 2 hen
5ˆ
B←2// en o ce min window o 2
6i ˆ
B < B hen
7B← ⌊(B+ˆ
B)/2⌋// smoo h sh ink
8B←ˆ
B// g ow immedia ely
9i |W|> B hen
10 while |W|> B do
11 emo eF on (W)
B. In eg a ion o DHL in o OMNeT++
The cu en OMNeT++ INET (4.5.4) FRER implemen s
an ex ended MRA, which is a duplica e il e ing mechanism
using a sliding window Wo ixed his o y leng h B. Fo
each incoming packe , i checks whe he he packe ’s sequence
numbe is al eady in he window. I i is, he packe is d opped;
o he wise, he sequence numbe is added o he window. I he
window exceeds i s size limi , he oldes en y is emo ed.
Accep ed packe s a e hen o wa ded.
The co e de-duplica ion logic is implemen ed in he
S eamMe ge module. We ex end his unc ionali y in he
S eamMe ge So e module o suppo adap i e bu e -
ing and in-o de packe shaping. Th ee boolean pa ame-
e s con ol hese ea u es: dynamicBu e size enables he
bu e upda e logic in Algo i hm 1, enableReo de ing ac-
i a es he so ing algo i hm, and pe iodicEmission en-
ables bo h so ing and shaping. Two iming pa ame e s go -
e n he iming beha io : ime In e al (τ) igge s he
me ge Time sel -message o bu e upda es du ing ini ializa-
ion, while sende T ansmissionIn e al se s he in e al o
he eleaseTime , which con ols ansmission iming in he
shaping p ocess.
Link delays a e measu ed by imes amping each packe
a Swi ch1, using he ese ed ield in he R-Tag inse ed
by IEEE8021 TagEpdHeade Inse e . These imes amps a e
hen ead by S eamMe ge So e a Swi ch2. Du ing each
me ge Time e en , handled in he handleMessage unc ion,
we un Algo i hm 1 o adjus and p une he his o y leng h.
We o e ide he pushPacke unc ion o implemen he
so ing algo i hm. Duplica e de ec ion and d opping a e i s
TABLE I
LINK DELAY PHASES OVER TIME
Time (ms) Fas Link Slow Link
0–9 0 ms 0 ms
10–19 0 ms amps 1 →10 ms in 1 ms s eps
20–29 0 ms holds a 10 ms
30–39 0 ms amps 11 →20 ms in 1 ms s eps
40–49 0 ms holds a 20 ms
50–59 down (∞) holds a 20 ms
60–69 0 ms amps 20 →10 ms in 1 ms s eps
70–79 0 ms holds a 10 ms
80–89 0 ms amps 9 →0 ms in 1 ms s eps
90–100 0 ms 0 ms
handled by delega ing o S eamMe ge . I enableReo de ing
is se o ue, he unc ion ei he bu e s ou -o -o de packe s
o o wa ds he nex expec ed packe , inc emen ing i s coun e .
A e wa d, he emi InO de unc ion is called o pe o m shap-
ing. I pe iodicEmission is ue,emi InO de schedules he
eleaseTime o igge a e sende T ansmissionIn e al,
pacing packe deli e y o ma ch he sende ’s ansmission a e.
IV. EXPERIMENT SETUP
This sec ion p esen s he expe imen al se up o DHL, be-
ginning wi h he e alua ion scena io, ollowed by he key
measu emen me ics and simula ion se ings.
A. Simula ion Se up and Link Beha io
The simula ion opology adhe es o he s aigh o wa d s uc-
u e illus a ed in Fig. 1 wi h wo E he ne links be ween
Swi ch1 and Swi ch2. We emula e lossy wi eless links by
using wo pa allel E he ne connec ions be ween Swi ch 1
and Swi ch 2, whose la encies and ou ages a e d i en by
he Scena ioManage (con igu ed ia an XML ile). Ou
es ing scena io consis s o a o al simula ion ime o 100 ms,
du ing which he sende ansmi s packe s pe iodically a 1 ms
in e als ∆ h ough wo physical links. The condi ions o
hese links a e desc ibed in Table I. Fo he as link, he
connec ion emains s able bu expe iences a b eakdown o
10 ms in he middle o he simula ion. In con as , he slow
link’s la ency inc eases and emains a a pla eau o wo phases
un il i eaches 20 ms. A e ha , he la ency dec eases in wo
phases un il i ul ima ely eaches ze o. Acco ding o ou design
scena io, we se Jequals 10 ms, ep esen ing he empi ically
measu ed one-way delay a ia ion obse ed on he link.
B. Pe o mance Me ics
His o y leng h is conside ed as main pe o mance me ic
as i in luences bo h he Duplica e Ra io (Dup) and he Ou -
o -O de Ra io (OoO). The Dup measu es he pe cen age o
packe s whose sequence numbe s ma ch hose seen ea lie (i.e.,
duplica es). Meanwhile, he OoO quan i ies he ac ion o ad-
jacen packe pai s whose sequence numbe s do no inc emen
by exac ly one. In he speci ic case discussed in Sec ion II,
he ou -o -o de issue canno be a oided solely h ough he
012345678910
Ji e (ms)
0
20
40
60
Ra io (%)
Baseline OoO.
Baseline Dup.
DHL OoO.
DHL Dup.
So ing OoO.
So ing Dup.
Fig. 3. The ou -o -o de a io and duplica e a io a e p esen ed. Since he
esul s om he so ing plus shaping algo i hm a e he same as hose om he
so ing algo i hm, we did no include hem in his plo . The Ji e Jis only
used in he DHL.
use o his o y leng h. The e o e, we also equi e an addi ional
bu e , e e ed o as he so ing bu e , o ensu e in-sequence
ansmission. We will also p esen he leng h o he so ing
bu e in ou measu emen s. Finally, he in e -a i al in e al
is a c i ical me ic ha highligh s he bene i s o ou shaping
ea u e in mi iga ing bu s ansmissions.
V. EVALUATION RESULTS
In his sec ion, we examine he pe o mance o a ious
algo i hms.
A. Impac s on In-o de Deli e y
In Fig. 3, we p esen he ou -o -o de and duplica e a ios
compa ison be ween di e en algo i hms, including baseline,
ou p oposed DHL, so ing, and so ing plus shaping. The
baseline con igu a ion uses he de aul MRA algo i hm wi h
a ixed his o y leng h o 5.
The alue o Jin he DHL algo i hm signi ican ly in lu-
ences pe o mance, as i di ec ly a ec s he his o y leng h. An
inc ease in Jleads o a educ ion in bo h he OoO and he
Dup. In con as , he o he algo i hms, which do no u ilize J,
main ain cons an a ios. When Jis se o 10 ms, ou p oposed
DHL algo i hms demons a e a no able imp o emen in he
Dup, educing i om 39 % o 0 % compa ed o he baseline
algo i hm. Addi ionally, he ou -o -o de a io dec eases om
61 % o 21 % when compa ed o he baseline.
Howe e , when Jis below 5 ms, he pe o mance o he
DHL algo i hm is in e io o he baseline. This decline occu s
because, du ing he i s 10 ms o he simula ion, he packe
delays do no di e , which leads o he DHL algo i hm upda ing
he his o y leng h o less han i e. As a esul , he algo i hm
s uggles o elimina e duplica ion e ec i ely. The so ing algo-
i hm achie es bo h an OoO and Dup o 0 % due o i s s ic
acking o sequence numbe s. Since he so ing plus shaping
algo i hm yields he same esul s as he so ing me hod, we did
no include i in ou compa ison.
In addi ion, he so ing and so ing plus shaping algo i hms
can u he dec ease bo h he OoO and he Dup o ze o. The
p ima y aim o hese algo i hms is o ensu e ha packe s a e
10 210 1100101
In e al (ms)
0.0
0.2
0.4
0.6
0.8
1.0
Empi ical CDF
Baseline
DHL
So ing
So ing+Shaping
Fig. 4. The empi ical cumula i e dis ibu ion unc ion (ECDF) o in e -
a i al in e als a he ecei e is used o compa e he pe o mance o he
ou algo i hms.
o wa ded in o de . Since bo h he so ing and so ing plus
shaping algo i hms yield he same ze o esul s, we ha e only
p esen ed he esul s o he so ing algo i hm he e.
B. Impac s on La ency
Fig. 4 illus a es he packe in e -a i al in e als o a ious
algo i hms. The expec ed in e -a i al a e is 1 ms, which
highligh s he ad an age o he so ing plus shaping algo i hm,
as i main ains mos packe s wi hin he 1 ms in e al. In
con as , he o he algo i hms expe ience bu s ansmissions.
No ably, he DHL algo i hm ou pe o ms he so ing algo i hm
by ansmi ing ewe bu s y packe s. This obse a ion indica es
ha app oxima ely 10 % o packe s om he DHL algo i hm
and a ound 20 % om he so ing algo i hm ha e in e -a i al
in e als o less han 1 ms.
To illus a e he ex en o la ge ou lie s, we epo he 99 h
pe cen ile (P99) o in e -a i al in e als. This P99 indica es
he maximum in e al below which 99 % o all packe s a i e.
The measu ed P99 alues a e as ollows: Baseline a 2.0 ms,
DHL a 1.3 ms, So ing a 1.6 ms, and So ing wi h Shaping
a 5.6 ms. No ably, DHL shows a 35 % educ ion compa ed o
he Baseline. Howe e , he e is a 10 ms ail due o a dis up ion
in he as link, du ing which he nex alid packe is ecei ed
only a e he link esumes. Addi ionally, bo h he so ing and
so ing wi h shaping algo i hms exhibi a 20 ms ail because
hey bu e ou -o -o de packe s un il he sequence numbe is
co ec ly inc emen ed.
C. Beha io o His o y Leng h Dynamics
Fig. 5 illus a es he link delay ( igh y-axis) de i ed om
he S eamMe ge So e module in Swi ch 2. The link delay
co esponds o ou con igu a ion ou lined in Table I. The nea ly
ze o alues esul om packe s ecei ed o e he as link, while
he wo phases o inc easing and dec easing delays o igina e
om he slow link. I ’s impo an o no e ha du ing simula ion
ime om 60 ms o 70 ms , he e is a g adual educ ion in
la ency om 20 ms o 10 ms. This esul s in ea lie packe s
expe iencing highe delays, while la e packe s ace lowe
delays, wi h bo h a i ing simul aneously a he 80 ms ma k.
0 10 20 30 40 50 60 70 80 90 100
Time (ms)
0
10
20
30
40
Size
Link delay (ms)
Baseline
DHL
So ing
So ing+Shaping
0
10
20
30
40
La ency (ms)
Fig. 5. This igu e displays he link delay ecei ed om he algo i hms, along
wi h he his o y leng h om he baseline and DHL algo i hms. Addi ionally,
i shows he bu e size o he so ing and so ing plus shaping algo i hms.
The baseline his o y leng h is se o 5, and he DHL acks
he link delay di e ences wi h an upda e equency o 10 ms.
As he la ency o he slow link inc eases, he his o y leng h
also inc eases. I is impo an o no e ha be ween 50 ms and
60 ms o he simula ion ime, he as link ails. Consequen ly,
he packe s a e hen only coming om he slow links, which
leads o a educ ion in he la ency di e ence obse ed in he
packe s. As a esul , he DHL dec eases in he ollowing 10 ms,
om 60 ms o 70 ms o simula ion ime.
Addi ionally, Fig. 5 p o ides in o ma ion abou he bu e
size, as bo h he so ing and so ing plus shaping algo i hms
c ea e a new bu e o s o e ou -o -o de packe s. S a ing a
60 ms in o he simula ion, bo h algo i hms bu e he ou -o -
o de packe s. The so ing algo i hms subsequen ly o wa d
hese packe s in a bu s a ound 80 ms. In con as , he so ing
plus shaping algo i hm eleases packe s a he same a e as he
sende ’s ansmission in e al. A he same ime, i ecei es
highe sequence numbe s and s o es he packe s in he bu e .
As a esul , he bu e o he so ing plus shaping algo i hm
emains s able. In summa y, we can see ha he his o y leng h
adap s acco ding o he link la ency and he usage o bu e size
in he so ing and so ing plus shaping algo i hms in Fig. 5.
D. Impac s on Packe Sequence
In Fig. 6, he e olu ion o he sequence numbe o e
ime du ing he simula ion is shown. This p o ides insigh s
in o how di e en algo i hms handle he sequence numbe ,
including he elimina ion o duplica es, wai ing o he co ec
sequence numbe o a i e, and he smoo h elease o packe s.
Since he sende ’s ansmission in e al is 1 ms, he sequence
numbe should ideally inc ease by one e e y 1 ms du ing
he simula ion. The baseline algo i hm s a s accep ing ou -
o -o de packe s a e 20 ms because i s his o y leng h o 5 is
insu icien o handle la e-a i ing packe s wi h lowe sequence
numbe s. This limi a ion esul s in equen " ee h" pa e ns in
he baseline algo i hm.
The DHL algo i hm add esses mos o hese ou -o -o de
issues, bu be ween 70 ms and 80 ms, i s ill s uggles. This is
because o iginal packe s (no duplica es) coming om bo h as

0 10 20 30 40 50 60 70 80 90 100
Time (ms)
0
20
40
60
80
100
Sequence Numbe
Baseline
DHL
So ing
So ing+Shaping
Fig. 6. This igu e illus a es how he sequence numbe changes o e ime,
de ailing he ope a ional beha io s o di e en algo i hms.
and slow links need o be accep ed and o wa ded. In oducing
a so ing algo i hm allows he sys em o bu e sequence
numbe s om 60 ms un il nea ly 80 ms, a which poin i
eleases he bu e ed packe s in a bu s once i ecei es he
packe s ha a i ed be o e 60 ms in sequence. Simila ly, he
so ing plus shaping algo i hm eleases he so ing bu e a an
in e al o 1 ms, in line wi h he sende ’s ansmission in e al.
This helps mi iga e he bu s ansmission issue.
VI. CONCLUSIONS AND FUTURE DIRECTIONS
This s udy in oduced DHL, an enhanced FRER elimina ion
algo i hm, ha join ly adap s i s his o y leng h sliding window
based on li e link-delay measu emen s. Addi ionally, we im-
plemen a s a e-o - he-a algo i hm o s ic sequencing ia
so ing and shaping. Ou OMNeT++/INET ex ension anspa -
en ly augmen s he exis ing S eamMe ge module, enabling
on- he- ly his o y leng h esizing, ou -o -o de packe bu e ing,
and paced emission wi hou al e ing exis ing FRER p imi i es
in INET. In e alua ion scena ios wi h dynamic la ency amps
on he slow-links un il 20 ms and a 10 ms as -link ou age, ou
DHL alone educed duplica e ames and ou -o -o de ames
by 39 % and 40 %, espec i ely. Addi ionally, DHL ou pe o ms
he so ing and shaping algo i hm ega ding he 99 h pe cen ile
o in e -a i al in e als, which is 1.3 ms compa ed o 5.6 ms.
This demons a es he ad an age o DHL in limi ing ji e o
he sende ’s 1 millisecond pacing.
This wo k pa es he way o explo ing mul i-s eam FRER,
ha dwa e-awa e ade-o s, and 6G scheduling in eg a ion [15].
Nex s eps include p o o yping on Sma NICs, adding mul i-
low p io i iza ion wi h shaping, and es ing unde ealis ic
6G–FRER a ic [16], [17]. By eleasing ou sou ce-code
h ps://gi hub.com/TUDComne sTSN/FRER_so ing_shaping,
we aim o suppo and ad ance communi y e o s owa d
achie ing de e minis ic, eliable communica ions in he
6G–TSN e a.
ACKNOWLEDGMENT
This wo k was unded by he Ge man Fede al Minis y
o Economic A ai s and Clima e Ac ion (BMWK), p ojec s
“TICCTEC” – g an 01MC22007A, “5G-OPERA” – g an
01MJ22008A, and “s ic5G” – g an 01MJ22018C, and by he
Ge man Resea ch Founda ion (DFG, Deu sche Fo schungs-
gemeinscha ) as pa o Ge many’s Excellence S a egy –
EXC 2050/1 – P ojec ID 390696704 – Clus e o Excellence
“Cen e o Tac ile In e ne wi h Human-in- he-Loop” (CeTI)
o Technische Uni e si ä D esden.
REFERENCES
[1] P. Schwen eck, G. T. Nguyen, H. Boche, W. Kelle e , and F. H. P.
Fi zek, “6G pe spec i e o mobile ne wo k ope a o s, manu ac u e s, and
e icals,” IEEE Ne w. Le ., ol. 5, no. 3, pp. 169–172, 2023.
[2] H. K. Naza i, J. Abich , S. Senk, H.-H. Liu, T. Scheine , G. T. Nguyen,
and F. H. P. Fi zek, “B idging he gap: 5G-TSN in eg a ion o indus ial
obo ic communica ion,” in P oc. Eu . Wi eless Con ., 2023, pp. 102–109.
[3] K. Zanbou i, M. Noo -A-Rahim, J. John, C. J. S eenan, H. V. Poo , and
D. Pesch, “A comp ehensi e su ey o wi eless ime-sensi i e ne wo king
(TSN): A chi ec u e, echnologies, applica ions, and open issues,” IEEE
Commun. Su eys Tu s., pp. 1–1, 2024.
[4] IEEE S anda ds Associa ion, IEEE S anda d o Local and Me opoli an
A ea Ne wo ks—F ame Replica ion and Elimina ion o Reliabili y, IEEE
S d. IEEE S d 802.1CB-2017, 2017.
[5] L. Maile, D. Voi lein, K.-S. Hielsche , and R. Ge man, “Ensu ing
eliable and p edic able beha io o IEEE 802.1CB ame eplica ion and
elimina ion,” in P oc. IEEE ICC, 2022, pp. 2706–2712.
[6] R. Ho mann, B. Nikoli´
c, and R. E ns , “Challenges and limi a ions o
IEEE 802.1CB-2017,” IEEE Embed. Sys . Le ., ol. 12, no. 4, pp. 105–
108, 2020.
[7] L. Thomas, A. Mi daoui, and J.-Y. Le Boudec, “Wo s -case delay bounds
in ime-sensi i e ne wo ks wi h packe eplica ion and elimina ion,”
IEEE/ACM T ans. Ne w., ol. 30, no. 6, pp. 2701–2715, 2022.
[8] J. Ansa i, T.-s. Hsiao, M. H. Ja a i, B. Va ga, J. Fa kas, I. Moldo án,
A. Göppe , and R. H. Schmi , “5G enabled lexible lineless assembly
sys ems wi h edge cloud con olled mobile obo s,” in P oc. IEEE
PIMRC, 2022, pp. 1419–1424.
[9] P. E. Kehl, J. Ansa i, M. Lo in, P. Mohan am, C.-C. E. Liu, J.-L. L.
Yeh, and R. H. Schmi , “5G-TSN in eg a ed p o o ype o eliable
indus ial communica ion using ame eplica ion and elimina ion o
eliabili y,” Elec onics, ol. 14, no. 4, 2025. [Online]. A ailable:
h ps://www.mdpi.com/2079-9292/14/4/758
[10] J. Gu, T. Chen, Y. Lu, X. Wu, and R. Wang, “Op imizing ame
eplica ion and elimina ion o eliabili y (FRER) p o ocol wi h pigeon-
inspi ed op imiza ion algo i hm,” in P oc. ICAIRC, 2024, pp. 842–846.
[11] G. Peng, S. Wang, T. Huang, F. Li, K. Zhao, Y. Huang, and Z. Xiong,
“Fas s: Enabling aul - ole an and ime-sensi i e scheduling in space-
e es ial in eg a ed ne wo ks,” IEEE J. Sel. A eas Commun., ol. 42,
no. 12, pp. 3551–3565, 2024.
[12] A. A. Syed, S. Ayaz, T. Leinmülle , and M. Chand a, “Faul - ole an
dynamic scheduling and ou ing o TSN-based in- ehicle ne wo ks,” in
P oc. IEEE VNC, 2021, pp. 72–75.
[13] A. Aijaz, “5G eplica es TSN: Ex ending IEEE 802.1CB capabili ies o
in eg a ed 5G/TSN sys ems,” in P oc. IEEE CSCN, 2024, pp. 108–112.
[14] D. E genç and M. Fische , “Implemen a ion and o ches a ion o IEEE
802.1CB FRER in OMNeT++,” in P oc. IEEE ICC Wo kshops, 2021,
pp. 1–6.
[15] H. K. Naza i, M. A. Ku , H.-H. Liu, S. Senk, G. T. Nguyen, and
F. H. P. Fi zek, “Inc emen al join scheduling and ou ing o 5G-TSN
in eg a ion,” in P oc. Eu . Wi eless Con ., 2023, pp. 110–116.
[16] H.-H. Liu, S. Senk, M. Ulb ich , H. K. Naza i, T. Scheine , M. Reisslein,
G. T. Nguyen, and F. H. P. Fi zek, “Imp o ing TSN simula ion accu acy
in OMNeT++: A ha dwa e-aligned app oach,” IEEE Access, ol. 12, pp.
79 937–79 956, 2024.
[17] S. Senk, T. Scheine , H. K. Naza i, H.-H. Liu, G. T. Nguyen, and
F. H. P. Fi zek, “5G-TSN lex ac: Expe ience a new ouch,” in P oc.
IEEE INFOCOM WKSHPS, 2024, pp. 1–3.