Le e aging Low-powe De ices o Cloud Se ices
in Communi y Ne wo ks
Nuno Apol´
onia, Roshan Seda , Felix F ei ag, Leand o Na a o
Uni e si a Poli `
ecnica de Ca alunya, Ba celonaTECH
Ba celona, Spain
{apolonia, seda , elix, leand o}@ac.upc.edu
Abs ac —Communi y ne wo ks a e IP ne wo ks cons an ly
being imp o ed ha e ol e in o la ge-scale compu ing pla o ms.
This has esul ed om he e o o adap he cloud compu ing
model owa ds se ices ha can ope a e and u ilize he esou ces
inside he communi y ne wo k. The ne wo k and i s in as uc-
u e a e con ibu ed by indi iduals, companies, o ganiza ions
and a e main ained by he communi y i sel . Communi y cloud
de ices a e o en low compu ing esou ce de ices, such as home
ga eways, wi h limi ed capabili ies. Cu en ly, hese de ices a e
con igu ed o un communi y se ices only. This has become a
d awback o u he adop ion because o con ibu o ’s di icul y
o also use he dona ed cloud de ice o p i a e pu poses. We
apply con aine -based i ualiza ion o he p oblem o esou ce
sha ing in low-capaci y de ices in o de o c ea e a mul i-pu pose
execu ion en i onmen in a single de ice. Thus, a single de ice
can be con igu ed o deli e o he use and he communi y a
mul i-pu pose en i onmen , such as pe sonal and public, isola ed
om one ano he , while p ese ing he communi y cloud se ices.
Ou compa a i e analysis wi h he cu en in as uc u e in
communi y ne wo ks gi es e idence ha he capabili y o he
de ices o un concu en se ices is main ained.
Keywo ds: i ualiza ion, communi y ne wo ks, cloud se -
ices, compu ing cons ained-de ices
I. INTRODUCTION
Communi y ne wo ks a e la ge-scale, sel -o ganised and
decen alised communica ion in as uc u es buil and ope a ed
by he communi y i sel . They a e open, ee and neu al IP
ne wo ks. As o now, hund eds o communi y ne wo ks a e
ope a ed ac oss he wo ld, which a e geog aphically dis ibu ed
in di e en pa s o he wo ld wi hou elying on any speci ic
social o economic easons. The la ge ne wo ks ha e om
500 o 28,000 nodes, such as Gui i.ne 1, FunkFeue 2, AWMN3,
F ei unk4. The in as uc u e is con ibu ed by indi iduals,
companies and o ganiza ions in a join e o .
Resou ce sha ing wi hin he communi y ne wo ks e e
in p ac ice o he sha ing o ne wo k bandwid h om each
de ice. This enables a ic om de ices o be ou ed h ough
o he s o i s des ina ion. The sha ing o se ices, such as ideo
s eaming, s o age, VoIP, which h ough cloud compu ing
ha e become common p ac ice in he In e ne , ha dly exis s
in communi y ne wo ks. The communi y cloud model could
sui o accommoda e se ices and/o esou ce sha ing among
communi y membe s.
The CONFINE p ojec 5was ini ia ed o ad ance he unde -
s anding o he communi y ne wo k model, o explo e he ways
1h p://gui i.ne
2h p://www. unk eue .a
3h p://www.awmn.g
4h p:// ei unk.ne /
5h p://con ine-p ojec .eu
o imp o ing he use s quali y o expe ience in a sha ed pla -
o m and o measu e he sus ainabili y o he ne wo k. Fo his
pu pose, he CONFINE p ojec has de eloped an in as uc u e
called Communi y-Lab [1], which p o ides an en i onmen o
pe o m communi y ne wo k ela ed expe imen s. The physical
de ices in he Communi y-Lab a e mini-PCs and a e low-
powe de ices. This complemen s he ene gy-e icien hos ing
o se ices and/o sha ing esou ces among o he communi y
membe s.
Cu en ly, he Communi y-Lab in as uc u e has a limi ed
numbe o physical de ices, he e o e he scalabili y o expe -
imen a ion is limi ed. Besides, all hese de ices a e con igu ed
o pe o m only communi y cloud se ices and his has become
a d awback o he de ice owne s. The esul is ha he owne s
o he de ices ha e been es ic ed om accessing esou ces o
hei p i a e pu poses. We add ess his limi a ion by c ea ing
an en i onmen in a single de ice, which can bene i bo h he
communi y and he de ice owne . Consequen ly, his p oduces
a mul i-pu pose en i onmen in a single de ice, such as one
en i onmen o he de ice owne and o he en i onmen s o
be sha ed wi h he communi y ne wo k.
Ou main con ibu ions include:
•The c ea ion o con aine -based esou ce i ualiza ion
on op o low-powe de ices, enabling a mul i-pu pose
en i onmen isola ed om each o he ;
•Use s can sha e a po ion o he de ice esou ces,
p ese ing he owne s mul i-se ice alloca ed i ual
space in he de ices;
•E alua ion o he pe o mance o de ices when un-
ning se ices on he i ual en i onmen s, and compa -
ison wi h he cu en se ings o he Communi y-Lab
de ices.
In o de o alida e he p oposed app oach, we c ea e
a small scale physical Communi y-Lab in as uc u e using
se e al low-powe de ices oge he as compu e and s o age
de ices and, sepa a ely, deploy he Communi y-Lab con olle
in a i ual machine inside a desk op PC. In his expe imen al
sys em we deploy wo applica ions, Tahoe-LAFS [2], [3] and
Pee S eame [4], [5], as communi y cloud se ices and mea-
su e he pe o mance o hese applica ions in he en i onmen
gi en by ou app oach.
The es o he pape is o ganised as ollows. Sec ion II
explains he Communi y cloud and ela es o he CONFINE
p ojec , including he o ma ion o Communi y-Lab es bed
wi h i s unc ionali y and he echnologies ha a e being
deployed. Sec ion III desc ibes he sys em a chi ec u e and he
deploymen app oaches. Sec ion IV e e s o he expe imen al
se up used. The e alua ion and esul s a e p esen ed in sec ion
© 2016 Else ie . This manusc ip e sion is made a ailable unde he CC-BY-NC-ND 4.0 license
h p://c ea i ecommons.o g/licenses/by-nc-nd/4.0/
V. The ela ed wo k is desc ibed in sec ion VI. Conclusion and
u u e wo k is explained in sec ion VII.
II. COMMUNITY CLOUDS
Communi y clouds a e o med by a collabo a i e e o
o c ea e a compu ing pla o m whe e he in as uc u e is
sha ed be ween a numbe o o ganiza ions in o de o p o ide
a pla o m o common compu ing conce ns. One pa icula
objec i e is o p o ide a scalable compu ing pla o m o
conduc communi y ne wo k ela ed esea ch. In his sec ion,
we explain he sys em o e iew o he CONFINE Communi y-
Lab in as uc u e.
Fig. 1. Sys em O e iew o he Communi y-Lab Tes bed
A. CONFINE P ojec : Communi y Ne wo ks Tes bed o he
Fu u e In e ne
The CONFINE p ojec goal is o augmen he capabili ies
o communi y ne wo ks by p o iding a pla o m o he exis -
ing communi y ne wo k in which use s can use se ices wi h
ease [6], as i hey we e deploying in any commodi y cloud
pla o m. Membe s o he CONFINE communi y ne wo k
es bed a e p i ileged o ge a se o IP add esses (IP 4) in
o de o hem o be able o un mul iple se ices, as hey
may equi e. This enables membe s o un mul iple se ices
on op o he exis ing ne wo k, while sha ing he esou ces
wi h he communi y.
Communi y-Lab, shown in Fig. 1, is an in as uc u e
ha p o ides a se o ools allowing esea che s o easily
deploy, un, moni o and expe imen communi y cloud se -
ices, p o ocols and applica ions in a eal communi y IP
ne wo k (Gui i.ne , FunkFeue , AWMN and F ei unk) ins ead
o simula ed en i onmen s.
The pla o m is moni o ed by a single en i y named
Communi y-Lab con olle , which allows use s o lease he e-
sou ces om he ne wo k, and deploy hei expe imen s on he
selec ed nodes. Pa icula ly, use s can choose geog aphically
dis ibu ed compu ing esou ces h ough he con olle and a e
able o cus omize he deploymen acco ding o hei speci ic
equi emen s. In addi ion, use s a e allowed o choose he
app op ia e con igu a ions o he compu ing esou ces, i.e., o
ha e public IP 4 add esses, which can be used o communica e
wi hin he communi y ne wo k.
Each Communi y-Lab node can con ain se e al sli e s,
shown in Fig. 1, which a e g ouped a a highe le el in slices.
As such, a slice is de ined as a se o esou ces sp ead ac oss
se e al physical de ices in he es bed which allows use s o
un expe imen s o e i . A sli e is de ined as he pa i ion
o he esou ces (o i ual machine) o a communi y node
assigned o a speci ic slice.
The pu pose o he con olle is o manage and con ol
he es bed h ough simple ope a ions such as managing use s,
nodes, slices and sli e s. This con olle p o ides an agg e-
ga ion poin whe e membe s can egis e hei de ices as
Communi y-Lab nodes. In he web in e ace esea che s can
choose geog aphically dispe sed nodes o c ea e slices o
hei expe imen s. The nodes e ie e he gi en in o ma ion
o deploy local sli e s ac ing as con aine s in he de ices.
Whene e use s make a eques o deploy a new sli e he
con olle c ea es a Linux con aine on he node by alloca ing
he esou ces equi ed o un he new sli e . The e o e each
sli e uns on he node isola ed om one ano he .
Linux con aine s gua an ee isola ion in e ms o secu i y
and esou ces howe e he hos ke nel sys em is sha ed be-
ween all con aine s. In his way, use s can deploy many sli e s
in a single node o un many se ices concu en ly.
To be pa o he Communi y-Lab in as uc u e he de ices
equi e o ope a e a speci ic ope a ing sys em, based on Open-
W 6con igu ed o p o ide au oma ically an open ne wo k
connec ion wi h he Communi y-Lab con olle , becoming pa
o he es bed o he expe imen s. These de ices se e as he
in as uc u e laye o he Communi y-Lab and mos a e low-
esou ce de ices which can be a o dable o ha e a he edges
o hese ypes o ne wo ks.
B. CLOUDY: Communi y Cloud Dis ibu ion
Cloudy Dis ibu ion7(Cloudy OS) has been c ea ed unde
he CLOMMUNITY p ojec 8 o p o ide communi y ne wo ks
an easy way o manage and deploy cloud in as uc u es and
in e aces o se ice disco e y and deploymen . The esul is
ha any use can enjoy he bene i s o cloud se ices which
a e eely a ailable in he communi y wi hou elying on any
speci ic cloud in as uc u e. The Cloudy OS is a ee and open
sou ce so wa e and is a cus omized e sion o Debian Linux.
By de aul , i comes wi h an ins alla ion o inc9VPN daemon
which c ea es a secu ed p i a e o e lay ne wo k be ween hos s
on he In e ne . Wi h he help o inc VPN, ne wo ked nodes
can communica e secu ely wi h each o he .
In addi ion, Cloudy OS uses A ahi10 (o Se 11 in la es
e sions), which is a ze o-con igu a ion ne wo king implemen-
a ion, o publish and disco e he se ices in he communi y.
Fo he simplici y o se ice disco e y, he Cloudy OS p o ides
an in e ace ha e ches he se ices in he o e lay and lis s
he se ices in o de o he use s o easily connec hem.
C. Vi ualiza ion Sys ems
Mos o he Communi y ne wo k de ices ha a e used in
he Communi y-Lab in as uc u e a e low-powe de ices such
as Home ga eways, se -up boxes, esea ch de ices. Howe e
hese de ices a e capable o unning mul iple communi y
cloud se ices simul aneously. Fo ins ance, he Cloudy OS
comes wi h a ew p e-ins alled se ices such as Tahoe-LAFS 12
dis ibu ed ile s o age sys em and Pee S eame 13: P2P ideo
6h p://openw .o g
7h p://cloudy.communi y
8h p://clommuni y-p ojec .eu
9h p://www. inc- pn.o g
10h p://www.a ahi.o g
11h ps://www.se dom.io
12h p:// ahoe-la s.o g
13h p://pee s eame .o g
s eaming amewo k. As we discussed p e iously, hese de-
ices a e con igu ed o se e only communi y cloud se ices.
We can say ha , as an en y-poin , i ualiza ion can gi e us he
means o c ea e mul i-pu pose en i onmen s in a single de ice.
The e o e, we can s udy wo main i ualiza ion echniques
and measu e he sys em beha iou o each case in e ms
o pe o mance and complexi y. Use s can choose one o
hese mechanisms conside ing he complexi y o he pla o m
con igu a ions, sys em pe o mance and he ha dwa e suppo
ha he de ices ha e.
One ype o i ualiza ion sys em is called Vi ual machines
(o machine emula ion) such as QEMU which is an open
sou ce machine emula o , used o un i ual machines on
op o an ope a ing sys em such as Linux. I is also capable
o di ec i ualiza ion when using he KVM (Ke nel-based
Vi ual Machine) ke nel module in Linux and ha ing ha dwa e
compa ible wi h i ualiza ion echnology. O he wise, i can
only emula e machines, and hus he i ual machines c ea ed
canno di ec ly access some o he ha dwa e which can p o ide
a be e gues pe o mance.
Ano he i ualiza ion echnology, also a ailable wi h mos
Linux ke nels, is called Linux Con aine s (LXC), and i is
compa able o o he i ualiza ion echnologies. Howe e i
may lack some o he secu i y and isola ion me hods ha
o he i ualiza ion echnologies ha e, such as OpenVZ.14
Also, i can be mo e ligh weigh since i uses he al eady in
place ea u es o he Linux ke nels ha adop ed his ype o
i ualiza ion. I sepa a es he use con ex o each con aine
and main ains a sha ed link o he hos ke nel in o de o un
mul iple sys ems in an OS-Le el i ualiza ion me hod.
III. SYSTEM ARCHITECTURES
The a chi ec u e o ou p oposed sys em includes wo
app oaches o i ualiza ion. In he i s app oach we used
a i ual machine (QEMU) in o de o sepa a e he con ex
in which a se ice can be deployed. In he second app oach
we used a LXC based app oach in which he i ualiza ion is
ligh weigh in o de o ha e a be e pe o mance while unning
se ices.
A. Se ices Deploymen
The p oposed app oaches, le e aging i ualiza ion e-
sou ces, a e enhanced wi h di e en con ex s whe e owne s
can sha e (sha ed con ex ) only pa o he de ices esou ces
while also accessing hei own (p i a e) con ex , whe e hey
can un hei own independen se ices, as demons a ed in
Fig. 2.
B. QEMU deploymen app oach
Ou ini ial app oach includes a deploymen o i ual
machines wi h he use o QEMU, ins alled on op o he
Cloudy OS. This allows us o concu en ly un se ices while
s ill isola ing he de ice o be used by i s owne . In a physical
de ice we ins all Cloudy OS whe e we can execu e se e al
ins ances o QEMU c ea ing i ual en i onmen s in o de
o un mul iple se ices. As an example, Fig. 3 shows he
deploymen o his scena io using wo Communi y-Lab nodes
and i s sli e s as independen se ices on op o he Cloudy OS.
This is done in o de o gain con ol o e he de ice o enable
mul iple se ices unning om di e en use con ex s while
main aining he owne s’ abili y o execu e his own se ices.
14h p://open z.o g
Fig. 2. Example o wo de ice deploymen . De ices a e di ided in wo
con ex s o owne and sha ed o he CN. In sha ed con ex se e al sli e s un
as nes ed con aine s belonging o each slice deployed.
Fig. 3. Example o QEMU deploymen app oach. Two se ices unning
(se ing as Communi y-Lab nodes) on i ual machines. LXC uns om wi hin
he Communi y-Lab node o c ea e sli e s.
The pe o mance o QEMU is g ea ly inc eased when un-
ning i wi h ke nel in eg a ion (KVM) o i ualiza ion suppo
om he ha dwa e. This gua an ees ha each i ual machine
has highe pe o mance and some o he physical esou ces
can be di ec ly u ilized by he i ual machines. Howe e in
low-powe de ices such op ion may no be a ailable, ins ead
QEMU has o emula e he whole p ocess o he i ual machine
which hinde s he pe o mance o he i ual machine.
Unde his scena io wi hin ce ain condi ions (such as
KVM enabled o i ualiza ion suppo ) we can achie e a
sepa a ion o se ices and u ilize a physical de ice o be sha ed
be ween he owne and he communi y ne wo k. This ype o
deploymen is a quick and easy way o os e ing mul iple
se ices in a single de ice. Fu he mo e, his app oach can
be ai ly enough when se ices need highe isola ion om
he hos sys em by enhancing i s secu i y o when he se ice
pe o mance is no a ec ed.
C. Linux Con aine s deploymen app oach
Ou p oposed app oach includes a deploymen o Linux
con aine s (LXC). This allows unning concu en se ices
wi h a low o e head o he i ual esou ces and p ocesses.
LXC c ea es di e en use con ex s in he hos machine o
deploy sepa a e sys ems, bu sha es he same ke nel (OS-Le el
i ualiza ion)
In his app oach we conside he isola ion o he se ices
while s ill gua an eeing a highe pe o mance o se ices
since he e is no emula ion in ol ed. The i ualiza ion laye
conside ed is in he OS-Le el, whe e he hos ke nel is sha ed
be ween con aine s and he hos sys em. In Fig. 4 we show
an example o he deploymen o his app oach using he
Cloudy OS as he hos sys em and deploying a Communi y-
Lab node in a LXC con aine . I is wo h men ioning ha
he Communi y-Lab nodes deploy hei own sli e s as LXC
con aine s and wi h ou app oach his does no change. This is
p o ided by uning he con igu a ions o LXC o deploy nes ed
con aine s, while adding he AppA mo 15 secu i y policies o
he secu i y conce ns.
Fig. 4. Example o LXC deploymen app oach. One se ice unning (se ing
as Communi y-Lab node) on a con aine i ualiza ion occu ing in OS-le el.
Nes ed LXC uns om Communi y-Lab node only con igu a ion is needed o
un nes ed con aine s.
Wi h his app oach, we can use he de ice as a sha ed
en i onmen be ween he owne and he communi y cloud
en i onmen main aining he isola ion om each use con ex .
The secu i y issues ha a ise om such usage a e espec ully
handled by LXC o he Linux secu i y policies. The e o e he
con aine s ha e access o he hos ke nel which may p o e o
be a mino isola ion o some se ices, equi ing mo e isola ion
should be handled wi h he i ual machines app oach.
Unde his scena io we can achie e a ligh e isola ion and
a concu en access o he physical de ices. This makes he
se ices unning wi h highe pe o mance han wi h he QEMU
app oach.
I is ele an o men ion ha in his app oach he sys em
unning in he con aine s only ha e access o he hos ke nel
as such he hos ke nel equi es o be compa ible (o wi h
he equi ed ke nel modules loaded) in o de o co ec ly
un he sys em inside he con aine , i.e. he Communi y-Lab
nodes equi e ha he o e layFS ile sys em should be na i ely,
enabling i o deploy he eques ed sli e s on he de ices.
A main ea u e o ou p oposed deploymen scena io is he
in oduc ion o a i ual en i onmen in which se ices a e able
o un wi h di e en con ex s and main aining an isola ed pa
o he de ice o be used by he owne . As a esul when using
he Communi y-Lab node as a se ice each node egis e ed
in he Communi y-Lab con olle can deploy i s own sli e s
in he physical de ice wi hou in e e ing wi h o he se ices
o he owne usage. This enables sha ing o esou ces o a
communi y cloud en i onmen and main aining he owne s
exclusi e access o he de ice.
IV. EXPERIMENTAL SETUP
Fo ou expe imen al se up, we used ou physical esea ch
de ices wi h di e en con igu a ions. These de ices a e buil
wi h In el powe ed A om N2600 CPU p ocesso s. Two o hem
ha e 2 GB o RAM, 60 GB s o age and 2 GB o RAM, 120 GB
s o age, and he o he de ice has 4 GB o RAM wi h 500 GB o
s o age disk and linked o he communi y ne wo k (Gui i.ne ).
A desk op compu e se up wi h he P oxmox sys em16 and buil
wi h an In el(R) Co e(TM) i7-3770 CPU @ 3.40GHz (8 co es),
wi h 1TB o s o age disk and 16 GB o RAM was used o
15h p://wiki.appa mo .ne
16h ps://www.p oxmox.com
deploy a local Communi y-Lab con olle in a i ual machine
en i onmen . I was necessa y o use such deploymen in o de
o no a ec he pe o mance o he cu en Communi y-Lab
in as uc u e, which is in a p oduc ion s a e.
Fo ou expe imen s, we se up a eplica o he Communi y-
Lab es bed a chi ec u e, such as, one local con olle which
con ols he o e all sys em and a se o compu ing nodes
(Communi y-Lab nodes) ha can be used o deploy sli e s
om he con olle . In his case, he local con olle can be
deployed ei he in a con aine o in a sepa a e i ual machine
ins ance. Howe e , his depends on he use s’ equi emen s and
he esou ces which a e a ailable.
The eason o he laye ed i ualiza ion in he physical
de ices is ha we in end o augmen he cu en se ices o he
Cloudy OS such ha he use s can ha e a se ice ha deploys
Communi y-Lab nodes in an au oma ic manne . This allows
aking ad an age o he i ualiza ion en i onmen in o de
o use s o sha e hei esou ces h ough he Communi y-
Lab pla o m and ex ending he numbe o nodes p esen
in he Communi y-Lab. Fu he mo e we can examine he
applicabili y and measu e he e iciency o deploy communi y
cloud se ices in o de o unde s and he easibili y o sha ing
de ices in communi y ne wo ks while main aining he owne s’
space in he de ice.
Challenges: One o he main challenges when c ea ing
ou expe imen al en i onmen is o se up he Communi y-Lab
con olle in a local en i onmen using a i ual machine, and
using Cloudy OS as he base o hos ope a ing sys em. The
p ocess o deploymen o he Communi y-Lab con olle in a
local en i onmen can be a challenging ask o he common
communi y use . The CONFINE P ojec wiki17, howe e ,
con ains u o ials on how a use can manage o ins all he
con olle wi h ease. I is also no ed ha some o he s eps
a e dependen on he ope a ing sys em used, and ha i can
b eak he communica ion o e lay i no co ec ly con igu ed
(i.e. Tinc miscon igu a ion).
Ano he challenge aced is he ac ha he cu en
Communi y-Lab node sys em equi es speci ic Linux ke nel
modules. These mus be enabled in he hos sys em, and
wi hou i , he sli e s may no wo k as expec ed and he e o e
no unc ion co ec ly when deploying/ unning he sli e s.
V. EVALUATION
In he e alua ion o he p oposed app oach (LXC deploy-
men app oach) we used physical esea ch de ices connec ed
o Gui i.ne . These de ices a e low-powe , ha e less esou ces
compa ed o desk op PCs, a e mos ly he same de ices used
wi hin he Communi y-Lab in as uc u e and a e gene ally
simila o he sha ed de ices om communi y ne wo ks. These
de ices a e deployed wi h scena io LXC, p e iously desc ibed.
A. Expe imen s
Ou expe imen s we e pe o med in o de o e alua e he
p oposed deploymen , summa ized in Table I, by u ilizing
di e en se ices wi h di e en pu poses. In he i s e alu-
a ion scena io we used Tahoe-LAFS dis ibu ed s o age, and
a s o age benchma k applica ion o e alua e he impac o he
p oposed deploymen on he physical de ices. In he second
e alua ion scena io we used Pee S eame , a pee - o-pee ideo
s eaming applica ion, in o de o e alua e he impac on
se ices ha ha e ime sensi i e da a p ocessing. The hi d
17h p://wiki.con ine-p ojec .eu
TABLE I. SUMMARY OF OUR SCENARIOS AND SETTINGS
Scena io 1 2 3
Numbe o local 8 8 8
Communi y-Lab nodes
Numbe o sli e s 8 8 16
Se ices deployed Tahoe-LAFS Pee s eame Tahoe-LAFS
and Pee s eame
Pe o mance S o age Chunks Recei ed S o age benchma k
Me ics benchma k and Played-ou Chunks Recei ed
and Played-ou
e alua ion scena io combines bo h se ices and allows an
e alua ion o he concu ency o se ices wi hin he same
physical de ices wi h ou p oposed deploymen .
Fo each scena io we collec ed esul s and plo ed hem
agains he baseline alues. The baseline alues we e ob ained
by unning he same se o expe imen s on he Communi y-Lab
in as uc u e ( om ou g oups’ ea lie wo ks [7]) unde he
same se o con igu a ions. This gi es us he beha iou o he
p oposed sys em in e ms o pe o mance and use expe ience.
In he Tahoe-LAFS expe imen s we measu ed he pe o -
mance o ead and w i e ope a ions in o de o unde s and
he impac hese ype o ope a ions ha e on he p oposed
deploymen . In he Pee S eame expe imen s we measu ed
he a e age chunk a es (da a ha is ecei ed in he pee s side)
and a e age chunks played ou on pee s (da a ha is sen o be
wa ched in he pee s side) in o de o measu e he quali y o he
ideo s eam. In bo h cases we measu ed he CPU u iliza ion
o demons a e ha hese low-powe de ices can deli e he
mul i-pu pose execu ion en i onmen while main aining he
mul i-se ice communi y cloud model.
Fi s Scena io: In ou i s e alua ion scena io, we c ea ed
one sli e o each a ailable Commmuni y-Lab node (eigh
sli e s in o al) and each sli e unning he Cloudy OS. Fo
each o he sli e s we an a Tahoe ins ance, Tahoe-LAFS is a
se ice ha comes bundled wi h he Cloudy OS and is used
o dis ibu ed s o age.
The scena io was es ed in se e al uns using he same
con igu a ion o each, ex ending o an amoun o 3 hou s
each. We used se en sli e s as Tahoe-LAFS s o age ins ances
( hese ins ances se e as s o age o he iles w i en by any
clien ). One o hese sli e s an Tahoe’s In oduce (a publish-
subsc ibe hub esponsible o no i y clien s and s o age nodes
abou each o he ) and he eigh h sli e ope a es he Tahoe-
LAFS clien ins ance which can w i e o ead iles om a
moun ed olde ha accesses di ec ly he Tahoe-LAFS sys em.
This is done h ough he use o ssh s and use ke nel module18
allowing a olde on he Tahoe-LAFS sys em o become
a ailable on any compu e sys em seamlessly.
Fu he mo e we an a well-es ablished disk benchma k
applica ion, i.e. IOZone [8], o measu e he s o age ope a ions
o each node in o de o e alua e he p oposed deploymen and
compa e i wi h he pe o mance o he same se ices when
using he cu en Communi y-Lab, a p esen ime.
Resul s: Fig. 5 shows he measu emen s o he baseline
sys em co esponding o he cu en Communi y-Lab en i on-
men , and he same se o ope a ions on he p oposed de-
ploymen (named se 1). No e ha all ope a ions a e comple ed
when he ansac ions be ween ins ances a e inished he e o e
he esul s accoun wi h he pe o mance o all Communi y-
18h p:// use.sou ce o ge.ne /ssh s.h ml
Fig. 5. Pe o mance o Tahoe-LAFS se ice, baseline as he cu en
deploymen and se 1 as wi hin he p oposed deploymen on he i s e alua ion
scena io (ope a ions shown as a e age All, w i e, e-w i e, ead, e- ead,
among o he s). Rep esen ing a e age, and de ia ions o each ope a ion.
20 40 60 80 100 120 140 160 180
0
10
20
Time (min)
CPU U iliza ion(%)
Fig. 6. CPU u iliza ion on Tahoe-LAFS clien node in he i s e alua ion
scena io
Lab nodes used. In he p oposed deploymen he e a e wo
se ices unning on he same physical de ices he e o e each
Tahoe-LAFS sys em has concu en access o he esou ces
which is, as expec ed, e lec ed by a gene al lowe ope a ion
speed o all he ope a ions measu ed. Howe e his s ill
accomplishes he ope a ions wi h he app oxima ed speeds as
he baseline e alua ion.
The benchma k applica ion s esses he de ice esou ces
in o de o ind he maximum speed o ope a ions such as
eading/w i ing o iles. I is impo an o no ice ha while
ne wo k pa is an impo an p ocess in dis ibu ing iles
h oughou he ins ances, ou e alua ion accoun s mo e o he
esou ce usage locally. Thus, CPU u iliza ion is impo an o
unde s and he sys em beha iou in he p oposed deploymen .
Fig. 6 shows he a e age CPU u iliza ion du ing h ee hou s
o unning he IOZone benchma king applica ion in he Tahoe-
LAFS clien ins ance. I has consumed a ound 20% o CPU
ime on a e age du ing he comple e es . The clien node
pe o ms enc yp ion/dec yp ion and e asu e code compu a ion
on each ile block in he phase o w i ing and/o eading
o/ om he disk. Fu he mo e he Tahoe-LAFS clien ins ance
consumes mo e CPU ime as opposed o Tahoe-LAFS s o ages.
Second Scena io: In ou second e alua ion scena io, we
used he same sli e deploymen (one pe node), unning
concu en ly a Cloudy OS empla e. In each o hese sli e s,
we an a Pee S eame expe imen .
Fo his scena io, we an ou es s in di e en ime pe iods,
wi h 1 hou each un, in o de o accoun o di e en ne wo k
ac i i y. We used se en sli e s as pee s (each pee e ie es
da a om he ne wo k in o de o play ou he s eaming ideo
locally). Pee S eame uses an o e lay ne wo k o exchange
da a (known as chunks) be ween i s pee s. We also se up one

sli e o se e as he sou ce pee which dissemina es he sou ce
ideo pa i ioned in chunks (as de aul , one ame o he ideo
is one chunk) o be played ou by he o he pee s.
The Pee S eame sou ce pee ge s a li e came a s eam
and sends he chunks o he o e lay ne wo k be ween each
pee ha wa ches ha s eam. This esul s in each pee ying
o e ch chunks om o he pee s o play ou he con inuous
s eam and display i locally o he use s.
Fig. 7. A e age chunks ecei ed a e a pee s om Pee S eame execu ion
in he second e alua ion scena io. Baseline as he cu en deploymen in
Communi y-Lab.
Fig. 8. A e age play-ou a io a pee s om Pee S eame execu ion in he
second e alua ion scena io. Baseline as he cu en deploymen in Communi y-
Lab.
Resul s: Fig. 7 and Fig. 8 depic he measu emen s o he
a e age o chunks ha a pee can ecei e and he chunks
pe cen age ha we e sen o be played ou a e aged by all
pee s. As a baseline we ha e he cu en deploymen om
p e ious expe imen s wi h he Communi y-Lab es bed in
which he p oposed deploymen is able o each wi hou losing
oo much da a on a e age. I is also no ed ha because o
he sha ed esou ces he e is a minimum amoun o chunks
ha a e no ecei ed in he p oposed deploymen . These ime
sensi i e applica ions equi e ha da a should a i e on ime o
be displayed/p ocessed, i he da a does no appea in he ime
allo ed i is disca ded. The e o e in he p oposed deploymen
his amoun does no a y much om he baseline.
Fig. 9 shows he a e age measu emen s o CPU u iliza ion
du ing an hou , when he se ice uns con inuously. The
al e a ions we see in he CPU u iliza ion is in ac because
he Pee S eame neighbou hood size changes o e ime ( he
o e lay ne wo k is cons an ly upda ed e en when he e a e no
new pee s) and he e o e he u iliza ion o he esou ces change
when he ope a ions o edoing he opology o he ne wo k is
pe o med. Mo eo e he CPU u iliza ion on he sou ce node
is highe han on he pee nodes since i anscodes he ideo
s eam and pa i ions i in o chunks ha will be sen o he
10 20 30 40 50 60
5
10
15
20
Time (min)
CPU U iliza ion(%)
Fig. 9. CPU u iliza ion on Pee S eame (PS) sou ce node on second
e alua ion scena io
pee s. Thus he CPU u iliza ion on he pee s is conside ably
lowe and do no in e e e as much wi h o he se ices unning
concu en ly. This is a esul o he pee s unning a mo e
ligh weigh p ocess such as ga he ing and decoding o chunks.
Thi d Scena io: In ou hi d e alua ion scena io, we an
bo h se ices (Tahoe-LAFS and Pee S eame ) in sepa a e
slices, unning concu en ly in a Cloudy OS empla e on
he same local Communi y-Lab nodes. We measu ed he
pe o mance o ou p oposed app oach while unning di e en
se ices in a concu en way.
In his scena io we an he same numbe o expe imen s as
be o e, while cu ing down he Tahoe-LAFS es o 1 hou . I
also uses he same deploymen o sli e s as be o e, howe e ,
each physical de ice uns concu en ly ou sli e s each wi h
i s own se ice and g oups o wo om he same slice.
Fig. 10. Pe o mance o Tahoe-LAFS se ice, baseline as he cu en
deploymen and se 1 as wi hin he p oposed deploymen in hi d e alua ion
scena io (ope a ions shown as A e age All, w i e, e-w i e, ead, e- ead,
among o he s). Rep esen ing a e age, and de ia ions o each ope a ion.
Resul s: Fig. 10 shows he esul s om he cu en de-
ploymen in Communi y-Lab as baseline, agains he p oposed
deploymen in Se 1. I also shows ha when di e en concu -
en se ices a e unning on he same de ice, he impac on
he se ices a e no iceable, when he e is a highe load o he
sys em. Howe e , in a no mal usage o se ices he impac on
he ope a ions is a enua ed wi h ime, o wi h scheduling.
Fig. 11 and Fig. 12 show he esul s o he cu en de-
ploymen on he Communi y-Lab as a baseline agains he
p oposed deploymen esul s. We can see a no iceable, o
a ce ain deg ee, a ia ion o he chunks played ou which
a ec s he ideo quali y pe cei ed. This is due o he CPU
ime being sha ed among mo e p ocesses. Howe e , while
concu en se ices may di e , o ou esul s we can say
ha he loss is minimal when using he p oposed deploymen
agains he cu en Communi y-Lab deploymen .
The a e age CPU u iliza ion o he Tahoe-LAFS clien
ins ance is shown in Fig. 13. These measu emen s we e aken
Fig. 11. A e age chunks ecei ed a e a pee s when Tahoe-La s is also
unning ( hi d e alua ion scena io). Baseline as he cu en deploymen in
Communi y-Lab.
Fig. 12. A e age chunk playou a pee s when Tahoe-LAFS is also unning
( hi d e alua ion scena io). Baseline as he cu en deploymen in Communi y-
Lab.
10 20 30 40 50 60
100
200
Time (min)
CPU U iliza ion(%)
PS
Tahoe
Fig. 13. A e age CPU u iliza ion o Tahoe-LAFS and Pee S eame (PS) in
hi d e alua ion scena io
o e one hou pe iod in he hi d e alua ion scena io. The
igu e shows he CPU u iliza ion o he Tahoe-LAFS clien
ins ance is a ound 35% - 40% on a e age o e he cou se o
expe imen , meaning ha i uses a mos hal o one co e o
he de ice. This is a esul o he added p ocessing in he clien
ins ances while he s o age ins ances ha e a lowe p ocess
u iliza ion, pe o ming only ead and w i e ope a ions.
On he o he hand, he a e age CPU consump ion o
Pee S eame is nea ly i e imes highe han wha Tahoe-
LAFS uses. This is because while unning he las scena io we
also eco ded he ideo o he disk (in all pee s) in luencing
mo e he esou ce u iliza ion o he se ice in o de o ge he
mos u iliza ion o each se ice. The CPU u iliza ion on he
pee s emains lowe han in he sou ce pee and s ill easible
o be unning concu en ly wi h o he se ices.
B. Discussion
We could obse e ha he p oposed deploymen has an
impac on he se ice pe o mance. Howe e , we can say ha i
is minimal while achie ing mo e se ices wi hin one physical
de ice. We can also s a e ha bo h scena ios, LXC and QEMU,
can be used acco ding o he esou ces a ailable. QEMU
is sui able when se ices equi e highe secu i y ea u es,
highe isola ion o he ke nel sys em and when esou ces a e
no cons ained (high-powe de ices wi h ha dwa e-enabled
i ualiza ion). LXC a ge s low-capaci y de ices o achie e
concu ency be ween se ices.
The quali y impac ha he se ices ha e is minimum,
when using se ices ha do no equi e high demand o he
esou ces. In ou expe imen s he esou ce u iliza ion was key
o unde s and he impac and how we can op imize he sha ed
esou ces. The esul s o ou e alua ion indica e a iabili y on
he execu ion o concu en se ices. One o he ac o s o his
is he use con ex has o be changed o each p ocess. This
can esul in mino delays un il he se ice can ully u ilize
he CPU.
Mo eo e we can say ha using such deploymen s may
gua an ee isola ion o se ices and main ain mos ly he same
quali y o se ice. The e o e, ou app oach showed o be
easible o he cu en deploymen o de ices on communi y
ne wo ks wi h minimal pe o mance loss in he se ices. Also
achie ing use con ex isola ion on he de ices o mul iple
pu poses and gua an eeing he owne s isola ion and u iliza ion
o he de ices. Fu he s udy o achie e and op imize he
maximum amoun o con ex s o se ices wi hin a de ice will
be deal in u u e wo k.
VI. RELATED WORK
In his sec ion we e iew some wo ks which add ess
simila issues as his pape . In [9] he au ho s epo on
how he deploymen o he cloud model on op o IP-based
communi y ne wo ks in he case o Gui i.ne was unde aken.
They elabo a e a sys em o he p oposi ion ha he use s
can bene i om cloud-based se ices inside o he ne wo k
wi hou ha ing o consume hem om he In e ne . Ins ead hey
can u ilize he esou ces ha al eady exis in hei communi y
ne wo k, while also g an ing access o cloud-based se ices.
The a ea o Fog compu ing [10] is ela ed o ou wo k
in he concep o in eg a ing edge de ices. To his end, Fog
compu ing aims o ex end da a cen e -based cloud compu ing
by in eg a ing hos s a he edges o he ne wo ks in o he cloud
p ocess. Edges a e seen as being p oac i e componen s o
se ices, da a usage and s o age.
In he Pe sonal clouds p oposal [11], he au ho s enhance
he capabili ies o mobile de ices, seen as low-powe ed de-
ices, by using ei he emo e o nea by cloud esou ces, ins ead
o ha ing o p ocess da a locally and hus educing consump-
ion wi hin he mobile de ices. Fu he mo e, his wo k explains
how ne wo k esou ces a e o be in eg a ed in a he e ogeneous
en i onmen , while enhancing he use expe ience. In his way,
each de ice can be seen as a single de ice cloud and ac i e
pa icipan s can un he se ices which a e o in e es o he
end use s.
The wo k in [12] shows how clouds ha ha e unde -u ilized
esou ces can be enhanced by sha ing hese esou ces wi h
o he communi ies, while s ill main aining he same aspec s
ha he cloud owne s ha e ag eed upon.
Wo k epo ed in [13] desc ibes echniques ha may sa is y
he o load compu a ion o mobile de ices. A compa ison
is p o ided o be e unde s and and succeed when doing
p ocessing on low-powe ed de ices. This sys em only accoun s
o se ice concu ency and no use independen , hus only
conside ing he i ualiza ion laye o se ice o un concu -
en ly in a low-powe ed de ice.
In he Pa ad op sys em [14] he au ho s ha e c ea ed a
pla o m in which low powe ed esou ces a e used, such as
home ga eways, in o de o deploy di e en se ices unning
and p ocessing concu en ly and wi h di e en da a. T ying
o ge he mos use ou o such de ices, while also aking
ad an age o he pa allelism ha de ices can c ea e be ween
compu a ions. This sys em only accoun s o se ice concu -
ency and no use independency, hus i only conside s he
i ualiza ion laye o se ices o un concu en ly in a low-
powe ed de ice.
The wo k in [15] demons a es ha con aine -based sys em
i ualiza ion is pe o med well o e hype iso s by gi ing he
oppo uni y o isola ion in e ms o secu i y and esou ces.
Thei esul s show ha con aine -based sys em i ualiza ion
p o ides up o 2x he sys em pe o mance o hype iso s o
se e - ype wo kloads and scale u he while main aining he
sys em pe o mance a a highe le el.
VII. CONCLUSION AND OUTLOOK
Communi y ne wo ks a e IP-based ne wo ks ha can ha e
many nodes ha a e connec ed by wi eless links h ough a
e i o y. These ne wo ks we e ini ially s a ed o gi e hei
membe s access o he In e ne . We a gue ha hese ne wo ks
a e unde u ilized i only In e ne access is a ge ed. The
esou ces in he ne wo k can ac ually suppo mo e se ices,
which can gi e communi y membe s ad an ages and bene i s
when pa icipa ing in sha ed se ices.
The con aine -based ligh weigh i ualiza ion app oach
p oposed in his pape o con ibu ed low-capaci y de ices,
main ains he bene i s o unning concu en se ices on hese
low-powe de ices and deli e s a mul i-pu pose sys em. Also
i ea u es isola ion o bo h esou ces and secu i y whe eby
gua an eeing a be e o e all sys em pe o mance e en on
esou ce-cons ained de ices. This pape also add essed he
cu en limi a ions o communi y cloud in as uc u es such as
he scalabili y o he exis ing in as uc u e, and he pe o -
mance o low-powe de ices.
We demons a ed ha h ough i ualiza ion we can deli e
a mul i-pu pose en i onmen . This leads us o un mul iple se -
ices in low-powe de ices (which a e simila o he esou ces
sha ed in communi y ne wo ks) o gua an ee he communi y
cloud en i onmen emains easible while gi ing he owne s
a space o hei own usage. We eplica ed he Communi y-
Lab in as uc u e o deploy di e en se ices in he de ices
a ailable in o de o unde s and he pe o mance issues ha
ou p oposed app oach can ha e.
F om he e alua ion pe o med, we showed ha he impac
on he pe o mance o unning concu en se ices, while in
di e en use con ex s is minimum compa ed o he cu en
s a e o he de ices, deployed h oughou he communi y
ne wo k. In ac , in he p oposed app oached he e alua ed
se ices pe o m much he same way as in he cu en
Communi y-Lab app oach, sugges ing ha he p oposed ap-
p oach is easible o deploy on such in as uc u es.
Mo eo e he p oposed app oach can augmen he es ab-
lished ne wo k in as uc u e o communi y ne wo ks and he
abili y o use s o ha e access o mo e compu ing powe ,
explo ing he communi y cloud en i onmen s and achie ing
a mul i-pu pose sys em. This way we can add alue o he
communi y ne wo ks, wi hou deploying mo e physical de-
ices, and lowe ing he impac on he se ices when unning
concu en ly wi hin he communi y ne wo k in as uc u e.
As a nex s ep, we conside o deploy and moni o esou ces
using he p oposed app oach in he Communi y-Lab es bed,
such ha we can iden i y con igu a ion o secu i y issues ha
may hinde he pe o mance o he se ices. Also, we will
conside di e en ypes o se ices unning concu en ly o
speci ically imp o e and op imize hei pe o mance applying
he p oposed app oach.
ACKNOWLEDGEMENT
This wo k was suppo ed by he Eu opean F amewo k P og amme 7
FIRE Ini ia i e p ojec s CONFINE (FP7- 288535), CLOMMUNITY (FP7-
317879), Uni e si a Poli cnica de Ca alunya-Ba celonaTECH and by he
Spanish go e nmen unde con ac TIN2013-47245-C2-1-R.
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