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526
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
526
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Seri
al P
erip
hera
l Int
erfa
ce (S
PI)
Full
Du
ple
x, 4
-wir
e, fl
exib
le c
lock
rat
e
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
522
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
522
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
5: S
essi
on
Laye
r
• Se
rvic
e: C
oo
rdin
atio
n o
f th
e d
ialo
gue
bet
wee
n a
pp
licat
ion
pro
gram
s
• Fu
nct
ion
s: S
essi
on
est
ablis
hm
ent,
man
agem
ent,
term
inat
ion
• Ex
amp
les:
RPC
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
518
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
518
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
1: P
hysi
cal L
ayer
• Se
rvic
e: T
ran
smis
sio
n o
f a r
aw b
it s
trea
m
ove
r a
com
mu
nic
atio
n c
han
nel
• Fu
nct
ion
s: C
on
vers
ion
of b
its
into
ele
ctri
cal o
r o
pti
cal s
ign
als
• Ex
amp
les:
X.2
1, E
ther
net
(cab
le, d
etec
tors
& a
mp
lifi e
rs)
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
514
8D
istr
ibut
ed S
yste
ms
Uw
e R
. Zim
mer
- T
he A
ustr
alia
n N
atio
nal U
nive
rsity
Syst
ems,
Net
wo
rks
& C
on
curr
ency
202
0
527
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
527
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Seri
al P
erip
hera
l Int
erfa
ce (S
PI)
©20
20U
RZ
iTh
At
liN
tilU
iit
527
f758
(h
t8
8
MISO
MOSI
SCK
CS
time
SetSa
mp
le Set
Set
Set
Set
Set
Set
Set
Sam
ple
Sam
ple
Sam
ple
Sam
ple
Sam
ple
Sam
ple
Sam
ple
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
Clo
ck p
has
e an
d
po
lari
ty n
eed
to
be
agre
ed u
po
n
523
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
523
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
6: P
rese
ntat
ion
Laye
r
• Se
rvic
e: P
rovi
sio
n o
f pla
tfo
rm in
dep
end
ent c
od
ing
and
en
cryp
tio
n
• Fu
nct
ion
s: C
od
e co
nve
rsio
n, e
ncr
ypti
on
, vir
tual
dev
ices
• Ex
amp
les:
ISO
co
de
con
vers
ion
, PG
P en
cryp
tio
n
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
519
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
519
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
2: D
ata
Link
Lay
er
• Se
rvic
e: R
elia
ble
tran
sfer
of f
ram
es o
ver
a lin
k
• Fu
nct
ion
s: S
ynch
ron
izat
ion
, err
or
corr
ecti
on
, flo
w c
on
tro
l
• Ex
amp
les:
HD
LC (h
igh
leve
l dat
a lin
k co
ntr
ol p
roto
col)
, LA
P-B
(lin
k ac
cess
pro
ced
ure
, bal
ance
d),
LAP-
D (l
ink
acce
ss p
roce
du
re, D
-ch
ann
el),
LLC
(lin
k le
vel c
on
tro
l), …
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
515
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
515
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Ref
eren
ces
for
this
cha
pter
[ Bac
on1
998 ]
Bac
on
, J
Co
ncu
rren
t Sys
tem
s A
dd
iso
n W
esle
y Lo
ngm
an
Ltd
(2n
d e
dit
ion
) 199
8
[ Ben
2006
] B
en-A
ri, M
Pr
inci
ple
s o
f Co
ncu
rren
t an
d D
is-
trib
ute
d P
rogr
amm
ing
seco
nd
ed
itio
n, P
ren
tice
-Hal
l 200
6
[ Sch
neid
er19
90 ]
Sch
nei
der
, Fre
d
Imp
lem
enti
ng
fau
lt-t
ole
ran
t ser
vice
s u
sin
g th
e st
ate
mac
hin
e ap
pro
ach
: a tu
tori
al
AC
M C
om
pu
tin
g Su
rvey
s 19
90
vol.
22 ( 4
) pp
. 299
-319
[ Tan
enb
aum
2001
] Ta
nen
bau
m, A
nd
rew
D
istr
ibu
ted
Sys
tem
s: P
rin
-ci
ple
s an
d P
arad
igm
s Pr
enti
ce H
all 2
001
[ Tan
enb
aum
2003
] Ta
nen
bau
m, A
nd
rew
C
om
pu
ter N
etw
ork
s Pr
enti
ce H
all,
2003
528
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
528
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
(SP
I)
Seri
al P
erip
hera
l Int
erfa
ce (S
PI)
pte
p(
)R
ecei
ve s
hift
regi
ster
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
fro
m S
TM32
L4x6
ad
van
ced
AR
M®-
bas
ed 3
2-b
it M
CU
s re
fere
nce
man
ual
: Fig
ure
420
on
pag
e 12
91
1 sh
ift r
egis
ter?
FIFO
s?
Dat
a co
nn
ecte
d to
an
inte
rnal
bu
s?
CR
C?
DM
A?
Spee
d?
524
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
524
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
7: A
pp
licat
ion
Laye
r
• Se
rvic
e: N
etw
ork
acc
ess
for
app
licat
ion
pro
gram
s
• Fu
nct
ion
s: A
pp
licat
ion
/OS
spec
ific
• Ex
amp
les:
API
s fo
r m
ail,
ftp
, ssh
, scp
, dis
cove
ry p
roto
cols
…
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
520
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
520
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
3: N
etw
ork
Lay
er
• Se
rvic
e: T
ran
sfer
of p
acke
ts in
sid
e th
e n
etw
ork
• Fu
nct
ion
s: R
ou
tin
g, a
dd
ress
ing,
sw
itch
ing,
co
nge
stio
n c
on
tro
l
• Ex
amp
les:
IP, X
.25
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
516
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
516
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
OSI
net
wo
rk r
efer
ence
mo
del
Stan
dar
diz
ed a
s th
eO
pen
Syst
ems
Inte
rcon
nect
ion
(OSI
) ref
eren
ce m
od
el b
y th
e In
tern
atio
nal
Sta
nd
ard
izat
ion
Org
aniz
atio
n (I
SO) i
n 1
977
• 7
laye
r ar
chit
ectu
re
• C
on
nec
tio
n o
rien
ted
Har
dy
imp
lem
ente
d a
nyw
her
e in
full
…
…b
ut i
ts c
once
pts
and
term
inol
ogy
are
wid
ely
use
d,
wh
en d
escr
ibin
g ex
isti
ng
and
des
ign
ing
new
pro
toco
ls …
529
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
529
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
(SP
I)R
ecei
ve s
hift
regi
ster
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
©20
20U
RZ
iTh
At
liN
tilU
iit
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
S1C
SSl
ave
sele
ctor
Mas
ter
Slav
e 1
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 2
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 3
MIS
O
MO
SI
SCK CS
MIS
O
MO
SI
SCK CS
S2 S3
Full
du
ple
x w
ith
1
ou
t of x
sla
ves
525
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
525
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Seri
al P
erip
hera
l Int
erfa
ce (S
PI)
Use
d b
y ga
zilli
on
s o
f dev
ices
… a
nd
it
’s n
ot e
ven
a fo
rmal
sta
nd
ard
!
Sp
eed
on
ly li
mit
ed b
y w
hat
b
oth
sid
es c
an s
urv
ive.
Usu
ally
pu
sh-p
ull
dri
vers
, i.e
. fas
t an
d r
elia
ble
, yet
no
t fri
end
ly to
wro
ng
wir
ing/
pro
gram
min
g.
1.8”
CO
LOR
TFT
LC
D d
isp
lay
fro
m A
daf
ruit
San
Dis
k m
arke
tin
g p
ho
to
521
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
521
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
4: T
rans
po
rt L
ayer
• Se
rvic
e: T
ran
sfer
of d
ata
bet
wee
n h
ost
s
• Fu
nct
ion
s: C
on
nec
tio
n e
stab
lish
men
t, m
anag
emen
t, te
rmin
atio
n, fl
ow
-co
ntr
ol,
mu
ltip
lexi
ng,
err
or
det
ecti
on
• Ex
amp
les:
TC
P, U
DP,
ISO
TP0
-TP4
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
517
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
517
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
Net
wo
rk
Dat
a lin
k
Phys
ical
Use
r d
ata
Use
r d
ata
OSI
Net
wo
rk L
ayer
s
542
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
542
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Fib
re C
hann
elM
app
ing
of F
ibre
Ch
ann
el to
OSI
laye
rs:
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
IP
Phys
ical
Use
r d
ata
Use
r d
ata
OSI
TCP/
IPO
SI
IP
Phys
ical
Ap
plic
atio
n
FC/I
P
FC-0
Ap
plic
atio
n
Fib
reC
hann
el
FC-4
FC-4
FC
-3FC
-3
FC-2
FC-1
Tran
spo
rtTr
ansp
ort
Net
wo
rkN
etw
ork
Ap
plic
atio
n
FC-3
Co
mm
on
se
rvic
e
FC-4
Pro
toco
l map
pin
g
FC-2
Ne
two
rk
FC-0
Ph
ysic
al
FC-1
Dat
a li
nk
538
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
538
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ethe
rnet
/ IE
EE 8
02.1
1
Wir
eles
s lo
cal a
rea
net
wo
rk (W
LAN
) dev
elo
ped
in th
e 90
’s
• Fi
rst s
tan
dar
d a
s IE
EE 8
02.1
1 in
199
7 (1
-2 M
bp
s o
ver
2.4
GH
z).
• Ty
pic
al u
sage
at 5
4 M
bp
s o
ver
2.4
GH
z ca
rrie
r at
20
MH
z b
and
wid
th.
• C
urr
ent s
tan
dar
ds
up
to 7
80 M
bp
s (8
02.1
1ac)
ove
r 5
GH
z ca
rrie
r at
160
MH
z b
and
wid
th.
• Fu
ture
sta
nd
ard
s ar
e d
esig
ned
for
up
to 1
00 G
bp
s o
ver
60 G
Hz
carr
ier.
• D
irec
t rel
atio
n to
IEEE
802
.3 a
nd
sim
ilar
OSI
laye
r as
soci
atio
n.
Car
rier
Sen
se M
ulti
ple
Acc
ess
wit
h C
ollis
ion
Avo
idan
ce (C
SMA
/CA
)
Dir
ect-
Sequ
ence
Spr
ead
Spec
trum
(D
SSS)
534
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
534
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
IP
Net
wo
rk
Phys
ical
OSI
App
leTa
lk o
ver
IP
Eth
erTa
lk L
ink
Acc
ess
Pro
toco
lLo
calT
alk
Lin
k A
cces
s Pr
oto
col
Toke
nTa
lk L
ink
Acc
ess
Pro
toco
lFD
DIT
alk
Lin
k A
cces
s Pr
oto
col
IEEE
802
.3Lo
calT
alk
Toke
n R
ing
IEEE
802
.5FD
DI
Ap
ple
Talk
Fili
ng
Pro
toco
l (A
FP)
Ro
uti
ng
Tab
le
Mai
nte
nan
ce P
rot.
AT
Up
dat
e B
ased
Ro
uti
ng
Pro
toco
lA
T Tr
ansa
ctio
n
Pro
toco
lN
ame
Bin
din
g Pr
oto
col
AT
Ech
o
Pro
toco
l
AT
Dat
a St
ream
Pro
toco
lA
T Se
ssio
n P
roto
col
Zo
ne
Info
Pro
toco
lPr
inte
r A
cces
s Pr
oto
col
Dat
agra
m D
eliv
ery
Pro
toco
l (D
DP)
Ap
ple
Talk
Add
ress
Res
olu
tio
n Pr
oto
col (
AA
RP)
530
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
530
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
(SP
I)R
ecei
ve s
hift
regi
ster
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
©20
20U
RZ
iTh
At
liN
tilU
iit
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
S1C
SSl
ave
sele
ctor
Mas
ter
Slav
e 1
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 2
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 3
MIS
O
MO
SI
SCK CS
MIS
O
MO
SI
SCK CS
S2 S3
Co
ncu
rren
t sim
ple
x w
ith
y o
ut o
f x s
lave
s
543
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
543
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Infi n
iBan
d
• D
evel
op
ed in
the
late
90’
s
• D
efi n
ed b
y th
e In
fi n
iBan
d T
rad
e A
sso
ciat
ion
(IB
TA) s
ince
199
9.
• C
urr
ent s
tan
dar
ds
allo
w fo
r 25
Gb
ps
per
lin
k.
• Sw
itch
ed fa
bri
c to
po
logi
es.
• C
on
curr
ent d
ata
links
po
ssib
le (c
om
mo
nly
up
to 1
2 3
00 G
bp
s).
• D
efi n
es o
nly
the
dat
a-lin
k la
yer a
nd
par
ts o
f th
e n
etw
ork
laye
r.
• Ex
isti
ng
dev
ices
use
co
pp
er c
able
s (i
nst
ead
of o
pti
cal fi
bre
s).
Mo
stly
use
d in
su
per
-co
mp
ute
rs a
nd
clu
ster
s b
ut a
pp
licab
le to
sto
rage
arr
ays
as w
ell.
Ch
eap
er th
an E
ther
net
or
Fib
reC
han
nel
at h
igh
dat
a-ra
tes.
Sm
all p
acke
ts (o
nly
up
to 4
kB
) an
d n
o s
essi
on
co
ntr
ol.
539
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
539
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Blu
eto
oth
Wir
eles
s lo
cal a
rea
net
wo
rk (W
LAN
) dev
elo
ped
in th
e 90
’s w
ith
dif
fere
nt f
eatu
res
than
802
.11:
• Lo
wer
po
wer
co
nsu
mp
tio
n.
• Sh
ort
er r
ange
s.
• Lo
wer
dat
a ra
tes
(typ
ical
ly <
1 M
bp
s).
• A
d-h
oc
net
wo
rkin
g (n
o in
fras
tru
ctu
re r
equ
ired
).
Co
mb
inat
ion
s o
f 802
.11
and
Blu
eto
oth
OSI
laye
rsar
e p
oss
ible
to a
chie
ve th
e re
qu
ired
feat
ure
s se
t.
535
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
535
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ethe
rnet
/ IE
EE 8
02.3
Loca
l are
a n
etw
ork
(LA
N) d
evel
op
ed b
y X
ero
x in
the
70’s
• 10
Mb
ps
spec
ifica
tio
n 1
.0 b
y D
EC, I
nte
l, &
Xer
ox
in 1
980.
• Fi
rst s
tan
dar
d a
s IE
EE 8
02.3
in 1
983
(10
Mb
ps
ove
r th
ick
co-a
x ca
ble
s).
• cu
rren
tly
1 G
bp
s (8
02.3
ab) c
op
per
cab
le p
ort
s u
sed
in m
ost
des
kto
ps
and
lap
top
s.
• cu
rren
tly
stan
dar
ds
up
to 1
00 G
bp
s (I
EEE
802.
3ba
2010
).
• m
ore
than
85
% o
f cu
rren
t LA
N li
nes
wo
rld
wid
e (a
cco
rdin
g to
the
Inte
rnat
ion
al D
ata
Co
rpo
rati
on
(ID
C))
.
Car
rier
Sen
se M
ulti
ple
Acc
ess
wit
h C
ollis
ion
Det
ecti
on (C
SMA
/CD
)
531
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
531
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
(SP
I)R
ecei
ve s
hift
regi
ster
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Master
Slave
©20
20U
RZ
iTh
At
liN
tilU
iit
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Clo
ck g
ener
ator
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
rM
ISO
MIS
O
MO
SIM
OSI
SCK
SCK
NSS
CS
Slav
e se
lect
or
Mas
ter
Slav
e 1
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 2
Rec
eive
shi
ft re
gist
er
Tran
smit
shift
reg
iste
r
Slav
e 3
MIS
O
MO
SI
SCK CS
MIS
O
MO
SI
SCK CS
Co
ncu
rren
t d
aisy
ch
ain
ing
wit
h a
ll sl
aves
544
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
544
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Dis
trib
utio
n!
Mo
tiva
tio
nPo
ssib
ly …
… fi
ts a
n e
xist
ing
phys
ical
dis
trib
utio
n (e
-mai
l sys
tem
, dev
ices
in a
larg
e cr
aft,
…).
… h
igh
perf
orm
ance
du
e to
po
ten
tial
ly h
igh
deg
ree
of p
aral
lel p
roce
ssin
g.
… h
igh
relia
bilit
y/in
tegr
ity
du
e to
red
un
dan
cy o
f har
dw
are
and
so
ftw
are.
… s
cala
ble.
… in
tegr
atio
n o
f h
eter
oge
neo
us
dev
ices
.
Dif
fere
nt s
pec
ifi ca
tio
ns
will
lead
to s
ub
stan
tial
ly d
iffe
ren
t dis
trib
ute
d d
esig
ns.
540
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
540
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Toke
n R
ing
/ IE
EE 8
02.5
/
Fib
re D
istr
ibut
ed D
ata
Inte
rfac
e (F
DD
I)
• “T
oke
n R
ing
“ d
evel
op
ed b
y IB
M in
the
70’s
• IE
EE 8
02.5
sta
nd
ard
is m
od
elle
d a
fter
the
IBM
To
ken
Rin
g ar
chit
ectu
re(s
pec
ifi ca
tio
ns
are
slig
htl
y d
iffe
ren
t, b
ut b
asic
ally
co
mp
atib
le)
• IB
M T
oke
n R
ing
req
ues
ts a
re s
tar
top
olo
gy a
s w
ell a
s tw
iste
d p
air
cab
les,
wh
ile IE
EE 8
02.5
is u
nsp
ecifi
ed in
top
olo
gy a
nd
med
ium
• Fi
bre
Dis
trib
ute
d D
ata
Inte
rfac
e co
mb
ines
a to
ken
rin
g ar
chit
ectu
re
wit
h a
du
al-r
ing,
fi b
re-o
pti
cal,
ph
ysic
al n
etw
ork
.
Un
like
CSM
A/C
D, T
oken
rin
g is
det
erm
inis
tic
(wit
h r
esp
ect t
o it
s ti
min
g b
ehav
iou
r)
FD
DI i
s de
term
inis
tic
and
failu
re r
esis
tant
No
ne
of t
he
abo
ve is
cu
rren
tly
use
d in
per
form
ance
ori
ente
d a
pp
licat
ion
s.
536
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
536
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ethe
rnet
/ IE
EE 8
02.3
O
SI r
elat
ion
: PH
Y, M
AC
, MA
C-c
lien
t
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
OS
Ire
fere
nce
model
Applic
ation
Pre
senta
tion
Sessio
n
Tra
nsport
Ne
two
rk
Data
lin
k
Physic
al
IEE
E 8
02.3
refe
rence
model
MA
C-c
lient
Media
Access (
MA
C)
Physic
al (P
HY
)
Upper-
layer
pro
tocols
IEE
E 8
02-s
pecific
IEE
E 8
02.3
-specific
Media
-specific
532
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
532
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
IP
Net
wo
rk
Phys
ical
Use
r d
ata
Use
r d
ata
OSI
Tran
spo
rt
Ap
plic
atio
n
TCP/
IPO
SI
545
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
545
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Wha
t ca
n b
e d
istr
ibut
ed?
• St
ate
C
om
mo
n o
per
atio
ns
on
dis
trib
ute
d d
ata
• Fu
ncti
on
Dis
trib
ute
d o
per
atio
ns
on
cen
tral
dat
a
• St
ate
& F
unct
ion
C
lien
t/se
rver
clu
ster
s
• no
ne o
f tho
se
Pu
re r
eplic
atio
n, r
edu
nd
ancy
541
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
541
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Fib
re C
hann
el
• D
evel
op
ed in
the
late
80’
s.
• A
NSI
sta
nd
ard
sin
ce 1
994.
• C
urr
ent s
tan
dar
ds
allo
w fo
r 16
Gb
ps
per
lin
k.
• A
llow
s fo
r th
ree
dif
fere
nt t
op
olo
gies
:
Poi
nt-t
o-po
int:
2 ad
dre
sses
Arb
itra
ted
loop
(sim
ilar
to to
ken
rin
g): 1
27 a
dd
ress
es
det
erm
inis
tic,
rea
l-ti
me
cap
able
Sw
itch
ed fa
bric
: 224
ad
dre
sses
, man
y to
po
logi
es a
nd
co
ncu
rren
t dat
a lin
ks p
oss
ible
• D
efi n
es O
SI e
qu
ival
ent l
ayer
s u
p to
the
sess
ion
leve
l.
Mo
stly
use
d in
sto
rage
arr
ays,
b
ut a
pp
licab
le to
su
per
-co
mp
ute
rs a
nd
hig
h in
tegr
ity
syst
ems
as w
ell.
537
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
537
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ethe
rnet
/ IE
EE 8
02.3
O
SI r
elat
ion
: PH
Y, M
AC
, MA
C-c
lien
t
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
App
licat
ion
Pres
enta
tion
Sess
ion
Tran
spor
t
Net
wor
k
Dat
a lin
k
Phys
ical
Net
wor
k
Dat
a lin
k
Phys
ical
Use
r da
taU
ser
data
OSI
Net
wor
k La
yers
802.3
MA
C
Physic
al m
ediu
m-
independent la
ye
r
MA
C C
lient
MII
Physic
al m
ediu
m-
dependent la
yers
MD
I
802.3
MA
C
Physic
al m
ediu
m-
independent la
ye
r
MA
C C
lient
MII
Physic
al m
ediu
m-
dependent la
yers
MD
I
PH
Y
Lin
k m
edia
,sig
nal encodin
g, and
transm
issio
n r
ate
Tra
nsm
issio
n r
ate
MII =
Mediu
m-independent in
terf
ace
MD
I =
Mediu
m-d
ependent in
terf
ace -
the lin
k c
onnecto
r
Lin
k
533
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
533
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Net
wor
k pr
otoc
ols
& s
tand
ards
Ap
plic
atio
n
Pres
enta
tio
n
Sess
ion
Tran
spo
rt
Net
wo
rk
Dat
a lin
k
Phys
ical
Ap
ple
Talk
Fili
ng
Pro
toco
l (A
FP)
Ro
uti
ng
Tab
le
Mai
nte
nan
ce P
rot.
IP
Net
wo
rk
Phys
ical
OSI
Tran
spo
rt
Ap
plic
atio
n
TCP/
IPA
pple
Talk
AT
Up
dat
e B
ased
R
ou
tin
g Pr
oto
col
AT
Tran
sact
ion
Pr
oto
col
Nam
e B
ind
ing
Pro
t.A
T Ec
ho
Pr
oto
col
AT
Dat
a St
ream
Pr
oto
col
AT
Sess
ion
Pr
oto
col
Zo
ne
Info
Pr
oto
col
Prin
ter
Acc
ess
Pro
toco
l
Dat
agra
m D
eliv
ery
Pro
toco
l (D
DP)
Ap
ple
Talk
Add
ress
Res
olu
tio
n Pr
oto
col (
AA
RP)
Eth
erTa
lk L
ink
Acc
ess
Pro
toco
lLo
calT
alk
Lin
k A
cces
s Pr
oto
col
Toke
nTa
lk L
ink
Acc
ess
Pro
toco
lFD
DIT
alk
Lin
k A
cces
s Pr
oto
col
IEEE
802
.3Lo
calT
alk
Toke
n R
ing
IEEE
802
.5FD
DI
558
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
558
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
()
()
ab
Ca
Cb
<"
&
Imp
licat
ion
s:
()
()
()
()
()
Ca
Cb
ba
ab
ab
<&
""
0J
z=
()
()
Ca
Cb
ab
ab
ba
&"
"/
JJ
z=
=^
^h
h
()
()
()
Ca
Cb
Cc
ca
<&
"J
=^
h
()
()
()
Ca
Cb
Cc
ca
<<
&"
J^
h
554
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
554
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
[Lam
po
rt 1
978]
()
()
ab
Ca
Cb
<"
&
wit
h a
b"
bei
ng
a ca
usa
l rel
atio
n b
etw
een
a a
nd
b,
and
(
)C
a,
()
Cb
are
the
(vir
tual
) tim
es a
sso
ciat
ed w
ith
a a
nd
b
ab
" if
f:•
a h
app
ens
earl
ier
than
b in
the
sam
e se
qu
enti
al c
on
tro
l-fl
ow
or
• a
den
ote
s th
e se
ndin
g ev
ent o
f mes
sage
m,
wh
ile b
den
ote
s th
e re
ceiv
ing
even
t of t
he
sam
e m
essa
ge m
or
• th
ere
is a
tran
sitiv
e ca
usal
rel
atio
n b
etw
een
a a
nd
b:
ae
eb
n1
""
""
f
No
tio
n o
f co
ncu
rren
cy:
ab
ab
ba
&"
"/
JJ
z^
^h
h
550
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
550
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Sync
hro
nize
a ‘r
eal-
tim
e’ c
lock
(bi-
dir
ecti
ona
l)
Res
etti
ng
the
clo
ck d
rift
by
regu
lar
refe
ren
ce ti
me
re-s
ynch
ron
izat
ion
:
Max
imal
clo
ck d
rift
d d
efi n
ed a
s:
()
()
Ct
Ct
-1
11
21
21
##
dd
++
-t
t-
^^
hh
‘rea
l-ti
me’
clo
ck is
ad
just
ed
forw
ard
s &
bac
kwar
ds
Cal
enda
r ti
me
t 're
al-t
ime'
C 'm
easu
red
tim
e'
syn
c.sy
nc.
syn
c.
ref.
tim
e
ref.
tim
e
ref.
tim
e
real
clo
ck
idea
lcl
ock
546
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
546
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Co
mm
on
des
ign
crit
eria
Ach
ieve
De-
coup
ling
/ hig
h d
egre
e o
f lo
cal a
uto
no
my
Coo
pera
tion
rat
her
than
cen
tral
co
ntr
ol
Co
nsi
der
Rel
iabi
lity
Co
nsi
der
Sca
labi
lity
Co
nsi
der
Per
form
ance
559
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
559
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
()
()
ab
Ca
Cb
<"
&
Imp
licat
ion
s:
()
()
()
()
()
Ca
Cb
ba
ab
ab
<&
""
0J
z=
()
()
Ca
Cb
ab
ab
ba
&"
"/
JJ
z=
=^
^h
h
()
()
()
()
()
Ca
Cb
Cc
ca
ac
ac
<&
""
0J
z=
=^
h
()
()
()
()
()
Ca
Cb
Cc
ca
ac
ac
<<
&"
"0
Jz
=^
h
555
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
555
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
()
()
ab
Ca
Cb
<"
&
Imp
licat
ion
s:
()
()
?C
aC
b<
&
()
()
?C
aC
b&
=
()
()
()
?C
aC
bC
c<
&=
()
()
()
?C
aC
bC
c<
<&
551
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
551
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Sync
hro
nize
a ‘r
eal-
tim
e’ c
lock
(fo
rwar
d o
nly)
Res
etti
ng
the
clo
ck d
rift
by
regu
lar
refe
ren
ce ti
me
re-s
ynch
ron
izat
ion
:
Max
imal
clo
ck d
rift
d d
efi n
ed a
s:
()
()
Ct
Ct
-1
11
21
21
##
d+
-t
t-
^h
‘rea
l-ti
me’
clo
ck is
ad
just
ed
forw
ard
s o
nly
Mon
oton
ic t
ime
t 're
al-t
ime'
C 'm
easu
red
tim
e'
syn
c.sy
nc.
syn
c.
ref.
tim
e
ref.
tim
e
ref.
tim
e
idea
lcl
ock
547
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
547
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Som
e co
mm
on
phe
nom
ena
in d
istr
ibut
ed s
yste
ms
1. U
npre
dict
able
del
ays
(co
mm
un
icat
ion
) A
re w
e d
on
e ye
t?
2. M
issi
ng o
r im
prec
ise
tim
e-ba
se C
ausa
l rel
atio
n o
r te
mp
ora
l rel
atio
n?
3. P
arti
al fa
ilure
s L
ikel
iho
od
of i
nd
ivid
ual
failu
res
incr
ease
s
Lik
elih
oo
d o
f co
mp
lete
failu
re d
ecre
ases
(in
cas
e o
f a g
oo
d d
esig
n)
560
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
560
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
Tim
e as
der
ived
fro
m c
ausa
l rel
atio
ns:
25
tim
e0
510
1520
2530
3540
45
21
20
P 1
26
27
29
22
29
P 2 P 3
31
35
36
23
24
2526
27
30
31
33
34
3536
37
3031
32
33
34
353637
40
3839
2728
30
37
38
Mes
sage
20
22 26
22233333
24
227
30
4
27
2242
29
22225
8
2222222222222225 292292292929222929292929292929292999
9
26
272272722727272777777777777
30
3
26
27272727272777777777
0 23333
31
36
36
31
3333333333
35
3
35 338
37
33
34333333
33
3535
444343433344
35
Eve
nts
in c
on
curr
ent c
on
tro
l fl o
ws
are
no
t ord
ered
.
No
glo
bal
ord
er o
f tim
e.
556
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
556
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Vir
tual
(lo
gica
l) ti
me
()
()
ab
Ca
Cb
<"
&
Imp
licat
ion
s:
()
()
()
Ca
Cb
ba
<&
"J
()
()
Ca
Cb
ab
&z
=
()
()
()
?C
aC
bC
c<
&=
()
()
()
?C
aC
bC
c<
<&
552
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
552
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Dis
trib
uted
cri
tica
l reg
ions
wit
h sy
nchr
oni
zed
clo
cks
• 6
tim
es:
6 r
ecei
ved
Req
ues
ts: A
dd to
loca
l Req
ues
tQu
eue
(ord
ered
by
tim
e)6
rec
eive
d R
elea
se m
essa
ges:
Del
ete
corr
esp
on
din
g Re
qu
ests
in lo
cal R
equ
estQ
ueu
e
1. C
reat
e O
wn
Req
ues
t an
d a
ttac
h cu
rren
t tim
e-st
amp
.A
dd O
wn
Req
ues
t to
loca
l Req
ues
tQu
eue
(ord
ered
by
tim
e).
Send
Ow
nRe
qu
est t
o a
ll p
roce
sses
.
2. D
elay
by
L2 ( L
bei
ng
the
tim
e it
take
s fo
r a
mes
sage
to r
each
all
net
wo
rk n
od
es)
3. W
hile
To
p (R
equ
estQ
ueu
e) ≠
Ow
nRe
qu
est:
dela
y u
nti
l new
mes
sage
4. E
nter
an
d le
ave
crit
ical
reg
ion
5. S
end
Rele
ase-
mes
sage
to a
ll p
roce
sses
.
548
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
548
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Tim
e in
dis
trib
uted
sys
tem
s
Two
alt
ern
ativ
e st
rate
gies
:
Bas
ed o
n a
shar
ed t
ime
Syn
chro
nize
clo
cks!
Bas
ed o
n se
que
nce
of e
vent
s C
reat
e a
virt
ual t
ime!
561
Dis
trib
ute
d S
yste
ms
© 2
020
Uw
e R
. Zim
mer
, The
Aus
tral
ian
Nat
iona
l Uni
vers
ity
page
561
of 7
58 (c
hapt
er 8
: “D
istr
ibut
ed S
yste
ms”
up
to p
age
641)
Dis
trib
uted
Sys
tem
s
Imp
lem
enti
ng a
vir
tual
(lo
gica
l) ti
me
1.
:P
C0
ii
6=
2.
:P
i6 6
loca
l eve
nts
: CC
1i
i=
+;
6 s
end
eve
nts
: CC
1i
i=
+; S
end
(mes
sage
, Ci);
6 r
ecei
ve e
ven
ts: R
ecei
ve (m
essa
ge, C
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574
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 574 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
22
26
22 2333 24
227
30
4
27
2242
2922292299
22225
8
22222222222225
292229292922229292929292929292922929999
9
26 272727272222772277777777777
3
26 272722722727777777
0
0
2 333333
31
36
36
31
3 333333333
35
3
35
333837
22
21
220
33
34333333333
3535P1
P2
P1
4443434333444 35
P0
3
330
3 31
0
P3
0
303033
12
• Observer-process P0 (any process) creates a snapshot token ts and saves its local state s0.
• P0 sends ts to all other processes.
570
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 570 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states
A consistent global state (snapshot) is defi ne by a unique division into:
• “The Past” P (events before the snapshot):( ) ( )e P e e e P2 1 2 1" &/! !
• “The Future” F (events after the snapshot):( ) ( )e F e e e F1 1 2 2" &/! !
566
Distributed Systems
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Distributed Systems
Electing a central coordinator (the Bully algorithm)Any process P which notices that the central coordinator is gone, performs:
1. P sends an Election-message to all processes with higher process numbers.
2. P waits for response messages. If no one responds after a pre-defined amount of time: P declares itself the new coordinator and sends out a Coordinator-message to all.
If any process responds, then the election activity for P is over and P waits for a Coordinator-message
All processes Pi perform at all times:
• If Pi receives a Election-message from a process with a lower process number, it responds to the originating process and starts an election process itself (if not running already).
562
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 562 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed critical regions with logical clocks• 6 times: 6 received Requests:
Add to local RequestQueue (ordered by time) Reply with Acknowledge or OwnRequest
• 6 times: 6 received Release messages: Delete corresponding Requests in local RequestQueue
1. Create OwnRequest and attach current time-stamp. Add OwnRequest to local RequestQueue (ordered by time). Send OwnRequest to all processes.
2. Wait for Top (RequestQueue) = OwnRequest & no outstanding replies3. Enter and leave critical region4. Send Release-message to all processes.
575
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 575 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
22
26
22 233 24
27
30
4
27
24
29
222225
8
222222222222225
2929292922922222922929229292929229292929999
9
26 2722727272727272277777777726 2722722727272722777777777
2 3333
6
363 33333333 3
35
333837
33
4434343344 35
P0
3
220
3030
31330
3
33
313131
P0
21
220
P1
P2
3636555 33
3433333
5555333335533335333335333335335333303033
12
• Pi6 which receive ts (as an individual token-message, or as part of another message):
• Save local state si and send si to P0.
• Attach ts to all further messages, which are to be sent to other processes.
• Save ts and ignore all further incoming ts‘s.
571
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 571 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states How to read the current state of a distributed system?
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
20 22
26
22 233333 24
227
330
4
27
224
29
222225
8
22222222222222225
2292929292222292229292929292929292299999
9
26 272722727272727227777777777
0
26 27277227227277777
0
2 3333333333333333333333333333333333333333333 34433434343434334343343343444
31
31 35
444444 37
333333333 35
3338
35
34
6
3333333333333333333333333333333333
3335353533535353535353533535555 36
P0
32
30
330
30
12
333337
444440
388888
Instead: some entity probes and collects local states. What state of the global system has been accumulated?
Sorting the events into past and future events.
567
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 567 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states How to read the current state of a distributed system?
25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
P3
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
Message
20 22
26
22 2333333 24
227
330
4
27
2242
29
22225
8
2222222222222225
29292929292922292929292929292292292929
9
26 27227272727272727777777777 30
3
26 2727227272277777
0
2 3333
31
36
36
31
3 33333333
35
3
35
333837
33
343333333
3535
4434433344 35
This “god’s eye view” does in fact not exist.
563
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 563 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed critical regions with logical clocks
Analysis• No deadlock, no individual starvation, no livelock.
• Minimal request delay: N 1- requests (1 broadcast) + N 1- replies.
• Minimal release delay: N 1- release messages (or 1 broadcast).
• Communications requirements per request: N3 1-^ h messages (or N 1- messages + 2 broadcasts).
• Clocks are kept recent by the exchanged messages themselves.
Assumptions: • No messages are lost violation leads to stall.
576
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 576 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
22
26
22 23333 24
227
330
4
27
2242
29
222225
8
22222222222222225
92992929292922929222292292292922929999
9
26 272272727222727777777777726 272722727277777777
2 33333
6
363 3333333333 3
35
33837
33
4443434333444 35
P0
3
220
3030
31330
3
33
313131
P0
21
220
P1
P2
3636555 33
3433333333
55553333355333333353333333535353333303033
12
• Pi6 which previously received ts and receive a message m without ts:
• Forward m to P0 (this message belongs to the snapshot).
572
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 572 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states How to read the current state of a distributed system?
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
20 22
26
22 233333 24
2227
4
33027
2242
29
22225
8
22222222222222225
29229922229292922929292929292922999
9
26 2722722727272727227777777
0
26 2727222727277777777
0
2 3333333333333333333333333333333333333333333333333 3433434343343334343433433434444
31
31 35
3744444
35
338
35
34
636
333333333333333333333333333333333333333
333333333535333355555
P0
32
30
330
30
12
33337
444440
388888
Instead: some entity probes and collects local states. What state of the global system has been accumulated?
Event in the past receives a message from the future!Division not possible Snapshot inconsistent!
568
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 568 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states How to read the current state of a distributed system?
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
22
26
22 233333 24
227
330
4
27
2242
29
22225
8
22222222222222225
29292929292929222229229292229292999
9
26 272272727222727777777777726 272722727277777777
6 33837
P0
P3 25
21
2
P1
P2 20
444440322 3333 363 33333333 3
33
4434433344 353535335553
3030
31330
3
3
3
333333333333333333
3331331331303033
12
36
35 36
39
33337337337337373337337333777 336
6
35
3837
33
34343434334333433434343434334434344444 33337
444440
38888
36
5
3
55
3
353535
Instead: some entity probes and collects local states. What state of the global system has been accumulated?
564
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 564 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed critical regions with a token ring structure
1. Organize all processes in a logical or physical ring topology
2. Send one token message to one process
3. 6 times, 6processes: On receiving the token message:1. If required the process enters and leaves a critical section (while holding the token).2. The token is passed along to the next process in the ring.
Assumptions: • Token is not lost violation leads to stall.
(a lost token can be recovered by a number of means – e.g. the ‘election’ scheme following)
577
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 577 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
20 22
26
22 23333 24
2227
330
4
27
224
P3
P1
P2
29
222225
8
22222222222222225
92992929292922929222292292292922929999
9
26 272272727222727777777777726 272722727277777777
2 33333
0 5
363 33333333 3 3837
33
44434343433344 5
P0
3
P0
3030
3130
3
33
3131
35 36
39
7 3
363
35
38375
31
P
5555555333335533333333335333535353333
3433333333
666666 3666666666363633366666666636363636663636363636366666666333333333
33333333333333
303033
12
• Pi6 which receive ts (as an individual token-message, or as part of another message):
• Save local state si and send si to P0.
• Attach ts to all further messages, which are to be sent to other processes.
• Save ts and ignore all further incoming ts‘s.
573
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 573 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Snapshot algorithm
• Observer-process P0 (any process) creates a snapshot token ts and saves its local state s0.
• P0 sends ts to all other processes.
• Pi6 which receive ts (as an individual token-message, or as part of another message):
• Save local state si and send si to P0.
• Attach ts to all further messages, which are to be sent to other processes.
• Save ts and ignore all further incoming ts‘s.
• Pi6 which previously received ts and receive a message m without ts:
• Forward m to P0 (this message belongs to the snapshot).
569
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 569 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states How to read the current state of a distributed system?
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31 35 36
23 24 25 26 27 30 31 33 34 35 36 37
30 31 32 33 34 35 36 37 4038 39
27 28 30 37 38
20 22
26
22 23333 24
227
330
4
27
224
29
22225
8
22222222222222225
292929292929292222292292922292999
9
26 2722727272227277777777777
3
26 272722727277777777
0
2 3333
31
36
36
31
3 3
35
3
35
3837
33
343333333
3535
4344 35
P0
3
3
30
3
3
33337
444440
388888
12
3131
33333333443434333344 353544 3
Instead: some entity probes and collects local states. What state of the global system has been accumulated?
Connecting all the states to a global state.
565
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 565 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed critical regions with a central coordinator
A global, static, central coordinator Invalidates the idea of a distributed system
Enables a very simple mutual exclusion scheme
Therefore:
• A global, central coordinator is employed in some systems … yet …
• … if it fails, a system to come up with a new coordinator is provided.
590
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 590 of 758 (chapter 8: “Distributed Systems” up to page 641)
or accept Contention (Print_Job : in Job_Type; Server_Id : in Task_Id) do if Print_Job in AppliedForJobs then if Server_Id = Current_Task then Internal_Print_Server.Start_Print (Print_Job); elsif Server_Id > Current_Task then Internal_Print_Server.Cancel_Print (Print_Job); Next_Server_On_Ring.Contention (Print_Job; Server_Id); else null; -- removing the contention message from ring end if; else Turned_Down_Jobs := Turned_Down_Jobs + Print_Job; Next_Server_On_Ring.Contention (Print_Job; Server_Id); end if; end Contention; or terminate; end select; end loop; end Print_Server;
586
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 586 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
A distributed server (load balancing)
Server
Server
Server Server
Server
Server
Server
Ser
Client
Server
erver
Server erver
ver
Server
Serve
Ser
errrr SSSSSS
Se r Se
SerSeSSSS v
Server
rver
Client
582
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 582 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Consistent distributed statesWhy would we need that?
• Find deadlocks.
• Find termination / completion conditions.
• … any other global safety of liveness property.
• Collect a consistent system state for system backup/restore.
• Collect a consistent system state for further pro-cessing (e.g. distributed databases).
• …
578
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 578 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2 23 24 25 26 35 36 37
4038 39
27 28 37 38
0
244
27
2242
29
222225
8
292929229292922292922929292929292999
222222222222225
9
2626
P 25
2P2
P3
20 22
26
22 233333
3338
P0
35 36
39
7 3
35
338
32822721P1
P00 12
• Save ts and ignore all further incoming ts‘s.
591
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 591 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Transactions
Concurrency and distribution in systems with multiple, interdependent interactions?
Concurrent and distributedclient/server interactions
beyond single remote procedure calls?
587
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 587 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
A distributed server (load balancing)
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Job_Completed (Results)
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Job_Completed (Results)
583
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 583 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
A distributed server (load balancing)
ServerClient ServerClient
579
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 579 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2
31
23 24 25 26 27 30 31 33 37
30 31 32 33 34 40
27 28 30
20 22
6
22
P1
2333 24
227
25
5
26 330
4
27
2242
29
222225
8
22222222222222225
2292929292222292229292929292929292299999
9
26 772727272727277777777726 27272727272727272722277777777
P1
P0
PP
P
333337
444440P3 2
1
P2
P
P
PP
0
3133313331
322 33333 333333333
33
4443434333443
3030
31330
3
33333333333333
303033
12
• Finalize snapshot
592
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 592 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
TransactionsDefi nition (ACID properties):
• Atomicity: All or none of the sub-operations are performed. Atomicity helps achieve crash resilience. If a crash occurs, then it is possible to roll back the system to the state before the transaction was invoked.
• Consistency: Transforms the system from one consistent state to another consistent state.
• Isolation: Results (including partial results) are not revealed unless and until the transaction commits. If the operation accesses a shared data object, invocation does not interfere with other operations on the same object.
• Durability: After a commit, results are guaranteed to persist, even after a subsequent system failure.
588
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 588 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
A distributed server (load balancing)with Ada.Task_Identification; use Ada.Task_Identification;
task type Print_Server is
entry Send_To_Server (Print_Job : in Job_Type; Job_Done : out Boolean); entry Contention (Print_Job : in Job_Type; Server_Id : in Task_Id);
end Print_Server;
584
Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 584 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
A distributed server (load balancing)
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client Ring of servers
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client Ring of servers
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Distributed Systems
Distributed states Running the snapshot algorithm:
P3 25
time0 5 10 15 20 25 30 35 40 45
21
20
P1
26 27 29
22
29
P2 23 24 25 26 27 30
30 31 32
27 28 30
26
2333 24
227
4
33027
2242
29
222225
8
292929292922929222929292929292929299
222222222222222225
9
26 72722722777777777726 272227272727272777777777
P0
1
220 2222
1
P3
P2
P
2P1
P0
3223
3030
330
3
3
0
303033
12
Sorting the events into past and future events.
Past and future events uniquely separated Consistent state
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Distributed Systems
TransactionsDefi nition (ACID properties):
• Atomicity: All or none of the sub-operations are performed. Atomicity helps achieve crash resilience. If a crash occurs, then it is possible to roll back the system to the state before the transaction was invoked.
• Consistency: Transforms the system from one consistent state to another consistent state.
• Isolation: Results (including partial results) are not revealed unless and until the transaction commits. If the operation accesses a shared data object, invocation does not interfere with other operations on the same object.
• Durability: After a commit, results are guaranteed to persist, even after a subsequent system failure.
isis possibp leiisii possibibpossibiblell
How to ensure consistency
in a distributed system?
Actual isolation and
effi cient concurrency?
Shadow copies?
Actual isolation or the appearance of isolation?
sub operations are performedsub operattions ai rere perforperforffffffffperfoferforffff medmedmedmedddededd
Atomic operations spanning multiple processes?
What hardware do we
need to assume?
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Distributed Systems
A distributed server (load balancing)task body Print_Server is begin loop select
accept Send_To_Server (Print_Job : in Job_Type; Job_Done : out Boolean) do
if not Print_Job in Turned_Down_Jobs then
if Not_Too_Busy then Applied_For_Jobs := Applied_For_Jobs + Print_Job; Next_Server_On_Ring.Contention (Print_Job, Current_Task); requeue Internal_Print_Server.Print_Job_Queue;
else Turned_Down_Jobs := Turned_Down_Jobs + Print_Job; end if;
end if; end Send_To_Server;
(...)
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Distributed Systems
A distributed server (load balancing)
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Send_To_Group (Job) Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Send_To_Group (JTT ob)
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Distributed Systems
Snapshot algorithm
Termination condition?
Either
• Make assumptions about the communication delays in the system.
or
• Count the sent and received messages for each process (include this in the lo-cal state) and keep track of outstanding messages in the observer process.
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)
Read (C)
P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
R
W
eaRe
Re
W
P1 P2 P3
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
Serialization graph is cyclic.
Not serializable
602
Distributed Systems
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
Re
Re
W
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
• The order between processes also leads to a global order of processes.
Serializable
598
Distributed Systems
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Write (B)
ead (A)(A)(A(A(A)(A)(AAAA)A)A)AA)AA)))) WR
P1 P2
Serializable
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Distributed Systems
Transactions
A closer look inside transactions:
• Transactions consist of a sequence of operations.
• If two operations out of two transactions can be performed in any order with the same fi nal effect, they are commutative and not critical for our purposes.
• Idempotent and side-effect free operations are by defi nition commutative.
• All non-commutative operations are considered critical operations.
• Two critical operations as part of two different transactions while affecting the same object are called a confl icting pair of operations.
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Distributed Systems
Transaction schedulers
Three major designs:
• Locking methods:Impose strict mutual exclusion on all critical sections.
• Time-stamp ordering:Note relative starting times and keep order dependencies consistent.
• “Optimistic” methods:Go ahead until a confl ict is observed – then roll back.
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)
Read (C)
P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
R
W
eaRe
Re
W
P1 P2 P3
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
• The order between processes does no longer lead to a global order of processes.
Not serializable
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A) Write (B)P2
P3
Write (B)
Order
Re
W
P1 P2
• Two confl icting pairs of operations with different orders of executions.
Not serializable.
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Distributed Systems
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Distributed Systems
Transactions
A closer look at multiple transactions:
• Any sequential execution of multiple transactions will fulfi l the ACID-properties, by defi nition of a single transaction.
• A concurrent execution (or ‘interleavings’) of multiple transactions might fulfi l the ACID-properties.
If a specifi c concurrent execution can be shown to be equivalent to a specifi c sequential execution of the involved transactions then this specifi c interleaving is called ‘serializable’.
If a concurrent execution (‘interleaving’) ensures that no transaction ever encounters an inconsistent state then it is said to ensure the appearance of isolation.
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Distributed Systems
Transaction schedulers – Locking methodsLocking methods include the possibility of deadlocks careful from here on out …
• Complete resource allocation before the start and release at the end of every transaction:
This will impose a strict sequential execution of all critical transactions.
• (Strict) two-phase locking:Each transaction follows the following two phase pattern during its operation:
• Growing phase: locks can be acquired, but not released.
• Shrinking phase: locks can be released anytime, but not acquired (two phase locking) or locks are released on commit only (strict two phase locking).
Possible deadlocks
Serializable interleavings
Strict isolation (in case of strict two-phase locking)
• Semantic locking: Allow for separate read-only and write-locks
Higher level of concurrency (see also: use of functions in protected objects)
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Distributed Systems
Achieving serializability For the serializability of two transactions it is necessary and suffi cient
for the order of their invocations of all confl icting pairs of operations to be the same
for all the objects which are invoked by both transactions.
• Defi ne: Serialization graph: A directed graph; Vertices i represent transactions Ti; Edges T Ti j" represent an established global order dependency between all confl icting pairs of operations of those two transactions.
For the serializability of multiple transactions it is necessary and suffi cient
that the serialization graph is acyclic.
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
Re
Re
W
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
• The order between processes also leads to a global order of processes.
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Distributed Systems
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Distributed Systems
Achieving serializability
For the serializability of two transactions it is necessary and suffi cient for the order of their invocations
of all confl icting pairs of operations to be the same for all the objects which are invoked by both transactions.
(Determining order in distributed systems requires logical clocks.)
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Distributed Systems
Transaction schedulers – Time stamp orderingAdd a unique time-stamp (any global order criterion) on every transaction upon start. Each involved object can inspect the time-stamps of all requesting transactions.
• Case 1: A transaction with a time-stamp later than all currently active transactions applies: the request is accepted and the transaction can go ahead.
• Alternative case 1 (strict time-stamp ordering): the request is delayed until the currently active earlier transaction has committed.
• Case 2: A transaction with a time-stamp earlier than all currently active transactions applies: the request is not accepted and the applying transaction is to be aborted.
Collision detection rather than collision avoidance No isolation Cascading aborts possible.
Simple implementation, high degree of concurrency– also in a distributed environment, as long as a global event order (time) can be supplied.
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
Write (B)ead (C)ead (CWrite (A) RReReRe
ead (A)ad (A)dd (A)d (A(A)d (A)d (A)(A)(A)(A(A)(A)(A)(AA)AA)A)AAAA) WR
P1 P2P3
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
Serialization graph is acyclic.
Serializable
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Read (C)
Order
Write (B)ead (C)ead (C(Write (A) RReRRRee
ead (A)ad (A)dd (A)d (Ad (A)d (A)d (A)(A)((A)((A(A(A)(A)A)A)A)A)A)A)) WR
P1 P2P3
• Three confl icting pairs of operations with the same order of execution (pair-wise between processes).
• The order between processes also leads to a global order of processes.
Serializable
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Distributed Systems
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Distributed Systems
Serializability
time0 5 10 15 20 25 30 35 40 45
Write (A)P1
Write (C)
Read (A)
Write (B)
P2
P3
Write (B)
Order
Re W
• Two confl icting pairs of operations with the same order of execution.
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Distributed Systems
Two phase commit protocolPhase 2: Implement results
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Server
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Server
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Client
Coord.
ver
rver
rver
ver
rver
Everybody destroys shadows
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
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Client
Coord.
ver
rver
rver
ver
rver
Setup & Start operations
Shadow copy
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
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Server Server
Server
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Client
erver
Server Server
erver
erver
ver
Client
See e SerSe
ServerSeSe
Se
Se
rver SerSSSSSSSS vSe
rverSerS
ererveSeS
ver
verrv
rver
erve
rver
Distributed Transaction
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Distributed Systems
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Distributed Systems
Transaction schedulers – Optimistic control
Three sequential phases:
1. Read & execute:Create a shadow copy of all involved objects and perform all required operations on the shadow copy and locally (i.e. in isolation).
2. Validate:After local commit, check all occurred interleavings for serializability.
3. Update or abort:
3a. If serializability could be ensured in step 2 then all results of involved transactions are written to all involved objects – in dependency order of the transactions.
3b. Otherwise: destroy shadow copies and start over with the failed transactions.
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Distributed Systems
Two phase commit protocolPhase 2: Implement results
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Server
Server
Server
Server
Server
Server
Server
Server
Server
Client
Coord.
ver
rver
rver
ver
rver
Everybody reports "Committed"
619
Distributed Systems
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Distributed Systems
Two phase commit protocolPhase 1: Determine result state
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Server
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Client
Coord.
ver
rver
rver
ver
rver
Coordinator requests and assembles votes:"Commit" or "Abort"
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Distributed Systems
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
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Server
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Server Server
Server
Server
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Client
ver
rver
rver
ver
rver
Determine coordinator
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Distributed Systems
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Distributed Systems
Transaction schedulers – Optimistic control
Three sequential phases:
1. Read & execute:Create a shadow copy of all involved objects and perform all required operations on the shadow copy and locally (i.e. in isolation).
2. Validate:After local commit, check all occurred interleavings for serializability.
3. Update or abort:
3a. If serializability could be ensured in step 2 then all results of involved transactions are written to all involved objects – in dependency order of the transactions.
3b. Otherwise: destroy shadow copies and start over with the failed transactions.
How to create a consistent copy?
resulresulresulresulrerresuresureresulreesulesuleeesulesuleess ts ots of ts oftsttsts ofts ofts ofs os ooofoofofff involviinvininvolvinvoinvolvnnvolvnvolvvvolvvoolvvvvvved ed traeedededed trad trad tradd trad tttratrraaaansacnsactinnsnsactinsactinsactinsacnsansaaccctctictitiiioonsoonsonsons onsslt f i l d t tiHow to update all objects consistently?
(i e(i eiiiii in isin isi ii ii i olatioolatiol til tilll n))))
Full isolation and maximal concurrency!
Aborts happen after everything has been committed locally.
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Distributed Systems
Two phase commit protocolor Phase 2: Global roll back
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Client
Coord.
ver
rver
rver
ver
rver
Coordinator instructs everybody to "Abort"
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Distributed Systems
Two phase commit protocolPhase 2: Implement results
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Server
Server
Server
Server
Server
Server
Server
Server
Server
Client
Coord.
ver
rver
rver
ver
rver
Coordinator instructs everybody to "Commit"
616
Distributed Systems
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
0 Uwe R. Zimmer, The Australian National University page 616 of y 758 (chapter 8: “Distributed Systems” up to pag8
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Server
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Server
Server
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Server
Server
Client
Coord.
ver
rver
rver
ver
rver
Determine coordinator
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Distributed Systems
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Distributed Systems
Distributed transaction schedulersThree major designs:
• Locking methods: no abortsImpose strict mutual exclusion on all critical sections.
• Time-stamp ordering: potential aborts along the wayNote relative starting times and keep order dependencies consistent.
• “Optimistic” methods: aborts or commits at the very endGo ahead until a confl ict is observed – then roll back.
How to implement “commit” and “abort” operationsin a distributed environment?
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Distributed Systems
Two phase commit protocolor Phase 2: Global roll back
0 Uwe R. Zimmer, The Australian National University page 625 of y 758 (chapter 8: “Distributed Systems” up to pag8
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Server
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Server
Server
Server
Client
Coord.
ver
rver
rver
ver
rver
Everybody destroys shadows
621
Distributed Systems
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Distributed Systems
Two phase commit protocolPhase 2: Implement results
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Ser
er Server
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Client
Server
Ser
Server
Server
Server
Server
Client
Coord.
ver
rver
rverEverybody commits
617
Distributed Systems
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
0 Uwe R. Zimmer, The Australian National University page 617 of y 758 (chapter 8: “Distributed Systems” up to pag8
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Coord.
ver
rver
rver
ver
rver
Setup & Start operations
613
Distributed Systems
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Distributed Systems
Two phase commit protocolStart up (initialization) phase
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Server
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Server
Client
ver
rver
rver
ver
rver
Ring of servers
Data
638
Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Coordinator processes
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Coordinator processes
Server
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Client
Coord.
Coordinator also received two messages
and processes job
634
Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Distribute job
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Distribute job
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Coord.
Coordinator sends job both ways
630
Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Start-up (initialization) phase
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Start up (initialization) phase
Server
Server
Server
Server
Server Server
Server
Server
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Server
Client Ring of identical servers
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Distributed Systems
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Distributed Systems
Two phase commit protocolPhase 2: Report result of distributed transaction
0 Uwe R. Zimmer, The Australian National University page 626 of y 758 (chapter 8: Distributed Systems” up to pag8
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Server
Clien
Coord.
ver
rver
rver
Server
Server
nttt
C
ver
rverCoordinator reports to client: "Committed" or "Aborted"
639
Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Result delivery
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Result delivery
Server
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Coord.
Server
Server
ntttt
C
Coordinator delivers his local result
635
Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Distribute job
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Distribute job
Server
Server
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Server Server
Server
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Client
Coord.
Everybody received job (but nobody knows that)
631
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Distributed Systems
Redundancy (replicated servers)Start-up (initialization) phase
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Start up (initialization) phase
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client Determine coordinator
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Distributed Systems
Distributed transaction schedulersEvaluating the three major design methods in a distributed environment:
• Locking methods: No aborts.Large overheads; Deadlock detection/prevention required.
• Time-stamp ordering: Potential aborts along the way.Recommends itself for distributed applications, since decisions are taken locally and communication overhead is relatively small.
• “Optimistic” methods: Aborts or commits at the very end.Maximizes concurrency, but also data replication.
Side-aspect “data replication”: large body of literature on this topic (see: distributed data-bases / operating systems / shared memory / cache management, …)
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Distributed Systems
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Distributed Systems
Redundancy (replicated servers)
Event: Server crash, new servers joining, or current servers leaving.
Server re-confi guration is triggered by a message to all (this is assumed to be supported by the distributed operating system).
Each server on reception of a re-confi guration message:
1. Wait for local job to complete or time-out.
2. Store local consistent state Si.
3. Re-organize server ring, send local state around the ring.
4. If a state Sj with j i> is received then S Si j%
5. Elect coordinator
6. Enter ‘Coordinator-’ or ‘Replicate-mode’
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Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 636 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Redundancy (replicated servers)Processing starts
0 Uwe R. Zimmer, The Australian National University page 636 of y 758 (chapter 8: “Distributed Systems” up to page8
Processing starts
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Coord.
First server detects two job-messages☞ processes job
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Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 632 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Redundancy (replicated servers)Start-up (initialization) phase
0 Uwe R. Zimmer, The Australian National University page 632 of y 758 (chapter 8: “Distributed Systems” up to page8
Start up (initialization) phase
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Coord.
Coordinator determined
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Distributed Systems
© 2020 Uwe R. Zimmer, The Australian National University page 628 of 758 (chapter 8: “Distributed Systems” up to page 641)
Distributed Systems
Redundancy (replicated servers)Premise:
A crashing server computer should not compromise the functionality of the system(full fault tolerance)
Assumptions & Means:
• k computers inside the server cluster might crash without losing functionality.
Replication: at least k 1+ servers.
• The server cluster can reorganize any time (and specifi cally after the loss of a computer).
Hot stand-by components, dynamic server group management.
• The server is described fully by the current state and the sequence of messages received.
State machines: we have to implement consistent state adjustments (re-organization) and consistent message passing (order needs to be preserved).
[Schneider1990]
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© 2020 Uwe R. Zimmer, The Australian National University page 641 of 758 (chapter 8: “Distributed Systems” up to page 641)
Summary
Distributed Systems
• Networks• OSI, topologies
• Practical network standards
• Time• Synchronized clocks, virtual (logical) times
• Distributed critical regions (synchronized, logical, token ring)
• Distributed systems• Elections
• Distributed states, consistent snapshots
• Distributed servers (replicates, distributed processing, distributed commits)
• Transactions (ACID properties, serializable interleavings, transaction schedulers)
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Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Everybody (besides coordinator) processes
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Everybody (besides coordinator) processes
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Coord.
All server detecttwo job-messages
☞ everybody processes job
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Distributed Systems
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Distributed Systems
Redundancy (replicated servers)Coordinator receives job message
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Coordinator receives job message
Server
Server
Server
Server
Server Server
Server
Server
Server
Server
Client
Coord.
Server
Server
nttttt
C
Send Job
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Distributed Systems
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Distributed Systems
Redundancy (replicated servers)
Stages of each server:
Job message received by all active servers
Job processed locallyJob message received locally
Received Deliverable
Processed
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