Diversifying Software Architecture for Sustainability: A Value-based Perspective

1.2 MB·

by  Dalia Sobhy

Diversifying Software Architecture for Sustainability:
A Value-based Perspective
Dalia Sobhy Rami Bahsoon
SchoolofComputerScience SchoolofComputerScience
UniversityofBirmingham UniversityofBirmingham
BirminghamB152TT,UnitedKingdom BirminghamB152TT,UnitedKingdom
[email protected] [email protected]
ABSTRACT thenaturalformsofdiversityinspiredJ.Kellytointroduce
6 design diversity; “the approach in which the hardware and
Although the concept of software diversity has been thor-
1 software elements that are to be used for multiple computa-
oughly adopted by software architects for many years, yet
0 tions are not copies, but are independently designed to meet
theadventofusingdiversitytoachievesustainabilityisover-
2 asystem’srequirements”[6]. Inotherwords,itisthegenera-
looked. We argue that option thinking is an effective deci-
n sion making tool to evaluate the trade-offs between archi- tionoffunctionallyequivalentversionsofasoftwaresystem,
a tectural strategies and their long-term values under uncer- but implemented differently [5]. Further, diversity could be
J interpreted as a means to defend a common system from
tainty. Our method extends cost-benefit analysis method
1 CBAM. Unlike CBAM, our focus is on valuing the options uncertainty, which rises linearly with it. In this context,
2 whichdiversificationcanembedinthearchitectureandtheir software diversity raised the potential awareness to apply
corresponding value using real options pricing theory. The diversificationinthedecision-makingprocess,whichinturn
] may cause a noticeable improvement in the way we design
intuitive assumption is that the value of these options can
E dependable, evolvable, and sustainable software.
provide the architect with insights on the long-term per-
S Sustainabilityisoneofthemajorconcernsforthelongevity
formance of these decisions in relation to some scenarios of
. of any system. To clarify, ‘longevity’ as a term means how
s interest and use them as the basis for reasoning about sus-
c tainability. The method aims to answer the following: (1) long a system will continue to adapt with the advancement
[ oftechnologiesandchangesinuserrequirementsandtheen-
Is diversification of architectural decisions beneficial in sus-
1 taining the software, (2) When, where and to what extent. vironment. It is classically defined as“meeting the needs of
the present without compromising the ability of future gen-
v Theproposedmodelisillustratedandevaluatedusingacase
erations to satisfy their own needs” [13]. Due to the im-
8 study from the literature referred to as GridStix.
portance of sustainability attribute for the evolution and
3
longevityofsoftwaresystems,theIEEESoftwareforexam-
7 1. INTRODUCTION
ple published a special issue on architecture sustainability,
5
0 Diversity,inallofitsmanifestations,isanessentialcondi- which thoroughly discussed the long-term need for sustain-
. tioningfactorforthesuccessfulevolutionofvarioussystems, ability [4], possible metrics for sustainability[22], and the
1 summarized in the ancient dictum, ‘variety is the spice of necessary milestones to achieve it [27]. Our main focus will
0 life’. Providing a wide range of species forming disparate be on Architecture sustainability, which generally refers to
6
populationsisgenerallyrelatedtothetermdiversity,which long-termcost-effectiveadaptationandimmenseemergence
1
includesbiological,ecological,chemical,cultural,workplace ofasystemtowardsdiversekindsofchange,suchasrequire-
:
v diversity etc. These types of diversity aim at maximizing ments, environment, business strategies and goals, technol-
i the benefits from varieties. For example, as in workplace ogy, accidental complexity, and false decisions[4].
X
diversity, having diverse groups of employees from different Thereisageneralbeliefthatthereexistacorrelationbe-
r backgroundswouldleadtogreatercreativityandinnovation. tween diversity and sustainability. In light of this, natural
a
In its simplest form, biological diversity positively impacts formsofdiversityareprominentproofofemployingmoredi-
the quality of human existence, hence protecting the envi- verse system is likely to sustain more in the future. On the
ronment from extinctions [17]. opposite extreme, the link between diversity and sustain-
In the past years, seemingly endless streams of academic ability is still unexplored in software engineering. So the
literature,whichtoutthebenefitsofdiversityindesign,have question now is how that link can help in engineering more
filled bookshelves and the airwaves. Particularly, in 1984, sustainablesoftware? Wearguethatthislinkcanbejudged
from a value-based perspective. More specifically, the fo-
cus is on how we can value diversity in architecture design
decisionsandevaluatetheircontributiontoachievesustain-
Permissiontomakedigitalorhardcopiesofallorpartofthisworkfor abilityinsoftwaresystems. Asthevaluationshalltakeinto
personalorclassroomuseisgrantedwithoutfeeprovidedthatcopiesare consideration uncertainty, we appeal to options thinking to
notmadeordistributedforprofitorcommercialadvantageandthatcopies answer the above question.
bearthisnoticeandthefullcitationonthefirstpage.Tocopyotherwise,to In a nutshell, the novel contribution is an architecture-
republish,topostonserversortoredistributetolists,requirespriorspecific
centricmethod,whichbuildsoncost-benefitanalysismethod
permissionand/orafee.
WOODSTOCK’97ElPaso,TexasUSA (CBAM)[3] to evaluate and reason about how architectural
Copyright20XXACMX-XXXXX-XX-X/XX/XX...$15.00.
diversificationdecisionscanbeemployedandtheiraugmen-
tation to value creation. The approach uses real options
analysis[32]toquantifythelong-termcontributionofthese
decisions to value and determine how that value can assist
decisionmakersandsoftwarearchitectstovisualizingabout
sustainability in software. Scenarios from case study are
necessary to demonstrate the validity and applicability of
approach. Our exploratory case analysis is based on provi-
sional data gathered from GridStix prototype, deployed at
River Ribble in the North West England[1][15].
Theremainderofthispaperisstructuredasfollows: Sec-
tion 2 elaborates on the motivation for proposing the ap-
proach,section3explainsbrieflythetechniquesusedtosup-
port our method. Section 4 presents the method. Section
5 applies the approach to a case study and provides a con-
structive evaluation for the method. Section 6 presents the Figure 1: Steps of Classical CBAM [3]
related work. Section 7 concludes the work.
2. MOTIVATION
Adhering to principles of diversity, it is a key enabler for
giesAS),whichhavetwomajorramifications: technicaland
sustainability. Beyond this, however, the link between di-
economical. TheformerimplicationsgeneratetheQAs,such
versity and sustainability was overlooked in the context of
as performance, usability, security, etc., portraying the sys-
software engineering. In particular, this link has not been
tem. While the latter are the costs of implementation and
studiedfromvalue-basedperspective. Thisneedcanbetrue
benefitsobtainedfromthesystem. Finally,theASsgenerate
formanyartefactsthatstemfromengineering. Wecontend
costsandQAresponses,whichinfluencethebenefits[3][19].
thatasustainablesoftwareshallcreateandaddvalue,while
in operation and as it evolves. Moreover, the cost-benefit
trade-offsandlong-termvaluehavesignificantimpactonthe
extenttowhichanarchitecturecanevolveandsustaindur-
3.2 RealOptionsAnalysis
ing its lifetime. A prominent demonstration of the issue is
theConcorde,aprestigioussupersonicjetthatflieswithup We view architecting for sustainability through diversifi-
to double the speed of sound at an expensive cost. During cation as an option problem. Real options theory provides
the operation of Concorde, only two major incidents hap- an analysis paradigm that emphasizes the value-generating
pened. A popular accident named“Paris Crash”occurred powerofflexibilityunderuncertainty. Anoptionistheright,
afteralmost35yearsofoperationwheretheenginesflamed, but not the obligation, to make an investment decision in
resulting in more than hundred deaths. Despite its high accordancetogivencircumstancesforaparticularduration
safety record over the operation lifetime, the operation ex- intothefuture,endingwithanexpirationdate[32]. Realop-
penseanditsinabilitytosustainvaluewereamongthemajor tions are typically used for real assets (non-financial), such
reasons for phasing out Concorde. as a property or a new product design. Furthermore, it
can be categorized into call and put options. The former
gives the right to buy an uncertain future valued asset for
3. BACKGROUND
thestrikepricebyaspecifieddate,whereasthelatteroffers
This section sets the concepts needed by the method to the option to sell that asset. There are several types of op-
quantifytheimpactofapplyingdiversifieddecisionsonsys- tions: switch, growth, abandon, defer, build, and alter. As
tem’s quality attributes (QA). an example of switching to improve the system QA, if we
are designing for sustaining value at runtime, the architect
3.1 CBAM
may think about how switching between various diversified
CBAMextendsATAM[21]withexplicitfocusonthecosts decisions can support value creation (i.e. the option can be
and benefits of the architecture decisions in meeting sce- offeringasuitableswitchingtype). Asafurtherillustration,
narios related to QA. Furthermore, it intends to“develop a adiversifiedoptionaimingtoscalethesystemcanbetreated
process that helps a designer choose amongst architectural as a growth option.
options,duringbothinitialdesignanditssubsequentperiods Realoptionsanalysisiswell-knowntypeofoptionforthe
of upgrade, while being constrained to finite resources”[3]. use in strategic decision-making scenes [11]. As a recall,
The classical CBAM is illustrated in figure 1, which starts we contend that diversification is likely to create decisions
with the determination of business goals, the fundamental in the form of real options that can be exercised for value
for constructing a software architecture. Commonly, it has creation. In fact, the value of these options is long-term
beentroublesomeforstakeholderstoelicitmissiongoals,due and can cross-cut many dimensions, including economical
totheirpresenceinvariouslevelsofabstraction. Adeepre- and technical ones. Particularly, the valuation of the op-
viewforthecategorizationofbusinessgoalsisfoundin[20]. tions can be performed in accordance to the sustainability
Forexample,atypicalgoalcouldbecuttingdownthemain- dimensions,whichrelatetotechnical,individual,economics,
tenanceanddevelopmentcostsorprovidingahighlyreliable environment, and social [9]. For this work, we focus on the
andsecuresystem. Inthiscontext,thesegoalsdrivethear- technical issues that allied to QA responses and their value
chitecture decisions (sometimes called architectural strate- contribution to sustainability.
option,withanexercisepriceanduncertainvalue. Acollec-
tionofalternateASsaregatheredtogetherformingaDAD,
wherevariousDADscouldbeimplementedinthesystemat
the same time.
4.1.2 Step 2: Assessing the relative importance of
QAs(ElicitQAScore)
j
Thequestionthatsteersthisstep: whichQAsareofcrit-
ical importance for sustaining the system and what is the
relative importance? The evaluation has explicit focus on
long-term scenarios of exploratory and expansion nature.
The assumption is to further“tune”the architecture so it
can continue to deliver value if these materialize. Specifi-
cally, this is translated in terms of a ranking score to each
QAinaccordancetothesystem’sbusinessgoals,giventhat
wehave j QAs, thetotalscoresshouldsatisfyequation(1).
Figure 2: Diversified CBAM
(cid:88)
QAScore =100,∀j :QAScore (cid:62)0 (1)
j j
j
4. DIVERSIFIEDCBAMFOREVALUATING
4.1.3 Step 3: Quantifying the benefits of the DADs
ARCHITECTURESUSTAINABILITYWITH (ElicitContribScore)
j
REALOPTIONS Classically, any DAD has an intuitive effect on multitude
TheproposedapproachextendsCBAMwithanemphasis of QAs. This typical influence results in favouring certain
on diversification architectural decisions (DAD), their cost QAsandhurtingothers. Anapparentconstraintarisefrom
andthevaluetheyaddtothesoftware,asillustratedinfig- selectingaDADistheuncertaintyaboutitsrationalimpact
ure 2. More specifically, we use this information as a way on the system. In this context, the elicitation of DAD’s
to reason and reflect about sustainability. CBAM tends to effect on each QA is a critical exercise, which is denoted by
quantifytheextenttowhichanASmeetsthescenariosand ContribScore. This score is theoretically rated using -1 to 1
its response level, whereas our method operates on the im- scale, where ‘1’ resembles the best impact on QA and ‘-1’
provement (if any) on the QA responses once we consider means the opposite.
diversification. This improvement’s response can carry an The values of QAScore and ContribScore are given as
added value, but with a price. The use of real option can input to the method. Although outside the scope of the
adequately help to quantify and visualize that response un- method, one possibility to derive the value ContribScore is
der uncertainty. The essence is in the future opportunities toemploytheKendall’sConcordanceCoefficient[3]. Itisa
flexibility creates and its contribution to long-term value notable aid in addressing the variability of scores by valu-
creation.Therefore, the key issue is how to select the best- ing the consistency between raters of elicited contribution
fit diversified strategy according to the current goal. Our scores. Lowcoefficientsignifieshighvariabilityquota,which
holistic view is reaching a set of decisions that can have a denotesthatsomestakeholdersarelackingparticularknowl-
globalimpactonvalueandhencesustainingthesystem. In edge.
this section, the steps of the method are introduced. The subsequent step is quantifying the benefit of each
DAD (Benefit ) using equation (2).
DADi
4.1 ProceduresofApproach
(cid:88)
Benefit = QAScore ∗ContribScore (2)
There are two fundamental questions to be answered in DADi j j i,j
our method: which diversity solution would provide more
4.1.4 Step4: QuantifyingthecostsofDADsandIn-
favorable option and when to exercise the offered option.
corporatingSchedulingimplications
Despite the prominent outcome from having variety of op-
tions,sometimesthevalueofanoptionintermsofcomplex- ClassicalCBAMusesthecommonmeasuresfordetermin-
ityexceedsitsbenefit. Inthiscontext,real-optionstheoryis ingthecosts,whichinvolvestheimplementationcostsonly.
employed along with CBAM, for example to provide design Unlike CBAM, our approach embraces the switching costs
support for run-time decisions that promote diversification, between decisions, which is equivalent to primary payment
which in turn sustain the software system. requiredforpurchasingastockoption. Thisisinadditionto
thecostsofdeployingDADs,configurationcosts,andmain-
4.1.1 Step 1: Choosing the business goals, Scenar-
tenance costs, similarly to the exercise price, denoted by
iosandDADs
Cost(DAD). Tothisextent,thecostmetricisaparamount
i
The preliminary analysis aims at providing the system indicatorforquantifyingtheoptionprice,inadditiontothe
with typical business drivers, a number of scenarios of in- benefit ramifications. For instance, decision A could pro-
terest, and varying architectural decisions, which uses the vide high utility and high cost, and hence high risk. While
formulationofCBAM.However,ourmethodfocusesonQA decision B supplies low utility and low cost, but low risk.
and their responses with respect to scenarios of interest, In this context, high costs are likely to generate a common
whicharekeytenetsforsustainingthesystem. Moreover,in threat towards achieving sustainability. Most importantly,
the diversified CBAM, DADs are envisaged as portfolio of thecostsofallDADsdeploymentshouldnotexceedtheto-
options. Exercising each decision can be formulated as call tal budget oftheprojectE asshowninequation(3). Asin
the system value is the summation of implemented
DADsandV . Asinequation5,letS (t)bethesys-
s DAD
tem value after implementing a particular DAD caus-
ing either incremental improvement or degradation at
timet,whichisequivalenttotheuncertainstockprice
when modelling an American call option.
(cid:88)
S =V + Benefit (4)
DAD s DADi
i
(cid:88)
S (t)=V + Benefit (t) (5)
Figure 3: Proposed Algorithm DAD s DADi
i
CBAM,wemeasuredthecostswithrespectto1-100range, 2. Calculate the likely rise and fall of payoff with
where ‘100’ denotes the most expensive cost and ‘1’ is the DADs
cheapest.
Let f be the likely rise of payoff i.e. rising option
u
pricefromimplementingDAD,whereasf isthelikely
d
(cid:88)
Cost(DAD )(cid:54)E (3) fallofpayoffi.e.. fallingoptionpricefromimplement-
i
i ingDAD.Thisistypicallyinterpretedusingequations
4.1.5 Step 5: Calculate the Return of each DAD for (6,7). Besides,Cost(DADi)isthegeneralcostsforim-
thescenarios plementing DADs as illustrated in equation 3, which
could constitute the implementation of one or more
As aforementioned, diversification decisions can be for-
DADs. Furthermore, the system value (corresponding
mulatedasoptionsthatcanbeevaluatedinthepresenceof
to stock) benefiting from DAD i.e. value rise, is de-
uncertainty. Ourcasetypicallyfocusesonoptionstoswitch,
notedbytheupfactoru,whereasd isthedownfactor
wait and/or abandon. DADs supporting diversification can
denoting the system value being hurt from DAD i.e.
bevaluedascalls. Thevalueofthesecallsprovidetheright
valuefall. Theuandd coefficientsareformulatedwith
withoutsymmetricobligationstoswitch amongDADsifthe
respect to the volatility of the anticipated outcome.
exerciseisfavourable. Moreover,theoptiontowaittoswitch
Certainly,theformulas f andf willnevergeneratea
is advantageous, the rational investigation of an option and u d
negative value and elicit the maximum possible value
waiting for provocative outcome has a positive impact on
from the net payoff, which makes them optimal.
switchingoptions. Last,butnotleast,ifaDADisnolonger
favouring the system, then preferably abandon(e.g. phase
out, rethink its design, etc) that DAD. (cid:88)
f =max(0,uS (t)− Cost(DAD )) (6)
We view DADs as portfolios with options, i.e. each DAD u DAD i i
is a portfolio with its varying exercise cost, risks, and ben-
(cid:88)
efits observed on QA responses. Each DAD comprises a fd =max(0,dSDAD(t)− Cost(DADi)) (7)
i
collection of ASs, so that similar or different ASs could be
implemented in multiple DADs, as previously shown in fig-
ure 2. Moreover, figure 3 illustrates the steps of applying 3. Calculate the option price of exercising DADs
diversification using portfolio of options where real options
A further critical step is determination of the option
analysis is employed for value quantifications.
priceofexercisingdiversifieddecisionsf,whichreveals
Wehaveexploitedthebinomialpricingmodel[12]forop-
atwhattimet itisfavourabletotakethedecisioni.e.
tions valuation, as well as Ozkaya et. al, approach [26] for
exercise an option. Moreover, it also illustrates the
guidance. Thebinomialmodelprovidesavisualrepresenta-
long-termperformanceofasystem,whichinturnaids
tionfor the options. Itis aconstructive aidaimingtoshow
in promoting sustainability. An important coefficient
thesuitabletimeslotforexercisinganoption. Foreachstep
p carries the risk-adjusted probability. It is essential
of binomial tree, the up and down nodes values are impor-
to note that u, d, and risk-free interest rate r values
tant in determining the system value rise and fall, which
areelicitedfromstakeholders,giventhefollowingcon-
are ultimately used to calculate the option price. In our
straint: d < 1+r < u.
method,theimpactofapplyingeachDADonthesystemis
computedateverytimeslott,wheret=k indicatesthatthe
time equals to k unit time of interest. The following steps pf +(1−p)f
f = u d (8)
arenecessaryforvaluationofoptionsusingbinomialoption 1−r
pricing model.
1+r−d
1. Calculate the system value without factoring di- p= (9)
versification into the decisions u−d
As a start, the system value S is evaluated with To move beyond the general approach, it is necessary to
DAD
respect to the initial system value denoted by V and perform an exploratory analysis to evaluate the proposed
s
resultant benefit of deploying DADs as in equation 4. method via a case study, which is illustrated in the next
Toexemplify,considerpossessingmultipleDADs,then section.
5. EVALUATION&DISCUSSION
Totesttheapplicabilityofapproach,thissectionpresents
anapplicationofthemethodonGridStixprototype[16]. The
evaluation is performed using hypothetical data, aiming to
measurethelong-termeffectivenessofimplementingvarious
diversifieddecisionsi.e. portfolioofoptions,onsystemQAs.
5.1 GridStix
A Grid-based technique to support flood prediction pro-
cess by implementing embedded sensors with diverse net-
working technologies [16]. Particularly, it measures the wa-
ter level for flood anticipation. We have chosen GridStix,
becauseofitsgreatvariabilityindesignspaceofferingasiz- Figure 4: Utility versus Reporting Latency in case
zling environment for the development of diversification. It of implementing additional nodes
is portrayed by numerous QAs and different architectural
components [15]. To this extent, the elements of design
space are adequate for having diversified design decisions, despite the system is highly reliable, it has poor energy ef-
which is necessary for our case evaluation. Typically, our ficiency of -0.2 and so on. In other words, the positive QA
method is aiming to envisage diversification by providing a response should not overlook the negative impact on other
portfolio of options, which are evaluated from value-based QAs i.e. tradeoffs between QAs.
perspectiveunderuncertainty,topromotesustainability. In
5.2.4 Step4: QuantifyingthecostsofDADsandIn-
other words, it is how to engineer the concept of diversity
corporatingSchedulingimplications
in software architecture. Furthermore, GridStix is one of
thewell-documentedcasestudiesthatwefoundinresearch, The general costs involved for each DAD are depicted in
illustrating the pros and cons, and hence a good aid for as- table 3, which is similar to the exercise price of an option.
sessing our approach. For better illustration, we multiplied all the costs and ben-
efits by a factor of 25.
5.2 Application
5.2.5 Step 5: Calculate the Return of each DAD for
5.2.1 Step 1: Choosing the business goals, Scenar- thescenarios
iosandDADs
Generally, our method is a scenario-based mechanism,
Amongthebusinessgoals,whichweconsidertoillustrate which utilizes scenarios as a way to determine the trade-
ourapproacharetheaccuracyoffloodanticipationandrea- offs between QAs. Drawing on case study, the scenario em-
sonablewarningtimepriortheflood. Wethenelicitdifferent ployedforevaluationis: (Sc)Messagestransmissionbetween
scenarios-seeTable1-withrespecttoQAsandthespecific any given sensor node and gateway should be ≤ 30ms (ad-
concerns. Moreover,thegeneralcapabilitiesofferedbyGrid- dressing the performance QA), hence improving the aver-
Stixalongwiththeprimitivesfordiversificationisshownin age network latency provided in [15] roughly by 60%. The
Table 2. stakeholderschosethetoprankedDADs,whicharesuitable
for implementation aiming to achieve the prior objective:
5.2.2 Step 2: Assessing the relative importance of
DAD ,DAD , DAD , and DAD .
1 3 5 7
QAs(ElicitQAScore)
j Currently, the approximate number of deployed gridstix
The relative importance of QAs for GridStix are elicited nodes is 14 [15]. It is likely that adding extra nodes may
from stakeholders, with respect to equation 1 as shown be- improve the system’s safety due to the presence of backup
low: nodes and providing wider network coverage. This in turn
promotes the accuracy of flood prediction, satisfying our
• Performance: 20 mainbusinessdriver,thussustainingtheGridStixsoftware.
Figure 4 envisages the utility gained versus reporting la-
• Reliability: 30 tency in accordance to offering up to 20 nodes. This graph
is based on the maximum utility achieved from applying a
• Availability: 20
single decision from the set of prior DADs.
• Security: 10
FavourableDiversificationOutcome.
• Scalability: 5 Bymovingbacktocasestudy,DAD andDAD areused
5 7
for method evaluation. The predicted utility values for the
• Energy Efficiency: 15 sole implementation of DAD and DAD is revealed in fig-
5 7
ure 5. While the deployment of both DADs is shown in
5.2.3 Step 3: Quantifying the benefits of the DADs
figure 6. Decision makers can vary the base value at cell A
(ElicitContribScore)
j (guidedbythechartinfigure 4)toperformwhat-ifanalysis.
Table3isemployedtodeterminetheimpactofeachDAD A bound of possible values, which can constitute the base
on the QAs (ContribScore). As a recall, this score is rated value ranging from $300 to $2200, where the worst case is
using -1 to 1 scale, where ’1’ resembles the best impact on $300andbestcaseis$2200. SoeachDADwillhaveadiffer-
QA and ’-1’ means the opposite. For instance, for DAD entlikelihoodinitialvaluewithrespecttoitsgeneralutility.
1
deployment, a QA response of 1.0 reliability reveals that Moreover,thevaluationofoptionsforDAD overvarying
5
Table 1: QA Responses
QA Concern Scenarios
1 Performance GridStix Node Latency Messagestransmissionbetweenanygivensensornode
and gateway should be ≤ 30ms
2 Availability Hardware Failure Gateway failure detected and recovered in <1 minute
3 Reliability Flood Prediction Accuracy Thesystemshouldsendalertmessagesin<2seconds
for flood anticipation
Network Resilience Theaveragenumberofroutesfromagivensensornode
to gateway > 13
4 Scalability Data Management ifanodehasfullcapacity,itshouldforwardtheincom-
ingmessagetoaneighbornodein≤100ms(75msfor
choosing the best available neighbor node and 25ms
for transmission)
5 Energy Efficiency Minimize power consumption Average power consumption for 1KB data forwarding
from node to gateway ≤1400mW
6 Security Node Manipulation Gateway should be 99.99% secured against any data
manipulations
Table 2: General capabilities provided by the Grid-
Stix
General Capabilities Primitives for Diversification (ASs)
1 Connectivity Wifi, BT, and GPRS
2 Data Management Local Storage, Shared DB, Cloud,
Neighbour Node
3 Power Consumption Built-in Battery (Rechargeable),
Battery Replacement,
and Energy Conservation
via Solar Cell, Kinetic Energy
4 Routing Algorithm FH, SP
Figure6: AnticipatedValuesfortheutilityofimple-
menting both DAD and DAD due to uncertainty
5 7
of number of nodes
Figure 5: Anticipated Values for the utility DAD
5
and DAD due to uncertainty of number of nodes
7
time slots for uncertainty of implementing additional nodes
is clearly shown in figure (7,8). Note that the r is always
0.5% in our case and V is $1750. For detailed analysis,
s
considercellDfortheevaluationoftwo-dayaspresentedin
Figure 7: Valuation of Options for DAD in case of
figure 11, which is the upper cell value: 5
implementing additional nodes for 1-day and 2-day
S (2)=V +V (2)=1750+1200=2950
uu s DAD5
The lower cell value is computed as follows:
=934.08+832.06+776.25=$2542.39
f (2)=max(0,S −Cost(DAD )
uu uu 5 SameappliesforDAD ,thevaluationofoptionsovervary-
7
ing time slots for uncertainty of implementing additional
=max(0,2950−1125)=1825
nodes is shown in figure (9,10). The option price formula f
Therefore, the option price formula f of DAD5 is: of DAD7 is:
f =f +f +f f =f +f +f
DAD5 DAD5.1 DAD5.2 DAD5.3 DAD7 DAD7.1 DAD7.2 DAD7.3
Table 3: The impact of a DAD on QAs and DADs costs
DAD Performance Reliability Availability Security Scalability Energy Efficiency Cost
i
1- Wifi 0.6 1.0 0.7 0.3 0.7 -0.2 30
2- BT 0.1 0.4 0.9 0.8 -0.4 0.8 20
3- FH 0.5 0.8 0.8 0.0 0.0 -0.4 15
4- SH 0.2 -0.1 0.5 0.0 0.0 0.7 10
5- Wifi+FH 1.0 1.0 0.9 -0.1 0.7 -0.6 45
6- Wifi+SP 0.7 0.5 0.5 -0.1 0.7 0.2 40
7- BT+FH 0.5 0.2 0.6 0.8 -0.4 0.7 35
8- BT+SP 0.2 0.1 -0.2 0.8 -0.4 1.0 30
Figure 8: Valuation of Options for DAD in case of Figure10: ValuationofOptionsforDAD incaseof
5 7
implementing additional nodes for 3-day implementing additional nodes for 3-day
Figure 9: Valuation of Options for DAD in case of
7
implementing additional nodes for 1-day and 2-day Figure 11: Valuation of Options for the deployment
of both DAD and DAD for 1-day and 2-day
5 7
=1002.49+906.06+852.89=$2761.44
By applying diversification, we implemented DAD5 and beenimprovedbyimplementingbothDADssimultaneously,
DAD7 together, and then the pay-off is computed to deter- which eventually sustains the system. As a result, it is
mine whether diversification has yielded favourable or un- favourable to exercise that option and hence invest in such
favourable outcome. The valuation of options for both is anarchitecture. Moreover,thecontinualmonitoringofpay-
depicted in figure (11,12). The option price value is: off by waiting was a prominent aid for deciding the most
suitabletimetoswitch,aswellasanadvocateindicatorfor
the system sustainability. However, this is not the case for
f =1156.72+970.15+790.04=$2916.90
DAD5,7 all diversification, in the following section, an unfavourable
In this context, this clearly shows that the utility has case arose due to diversification.
Figure 12: Valuation of Options for the deployment Figure14: ValuationofOptionsforDAD incaseof
1
of both DAD and DAD for 3-day implementing additional nodes for 1-day and 2-day
5 7
Figure 13: Anticipated Values for the utility of im- Figure15: ValuationofOptionsforDAD incaseof
1
plementing DAD1 vs implementing DAD1, DAD5 implementing additional nodes for 3-day
and DAD due to uncertainty of number of nodes
7
UnfavourableDiversificationOutcome.
Typically,wehaveimplementedthreeDADstoachieveour
scenario: DAD , DAD , and DAD . The anticipated util-
1 5 7
ity values for the implementation of DAD versus the three
1
DADs are depicted in figure 13, as well as the valuation
of options for DAD is shown in figure (14,15) and for all
1
DADsinfigure(16,17). Byapplyingthesamelogicusedto
calculate the prior option values, f is $3111.58 and the
DAD1
option price for 3 DADs equals:
f =11.19+1.20+2.36=$14.75
DAD1,5,7
An unfavourable outcome occurred in subsequent to ap-
plyingfurtherdiversificationbyimplementingadditionalar-
chitectural decisions, as shown by the major drop in option
priceto$14.75andalsothroughoutthetimeslotsazeropay-
off appeared repeatedly. Therefore, it is highly desirable to Figure 16: Valuation of Options for the deployment
abandonthatoption. Inthisregard,thisadverseyieldmay of DAD1, DAD5 and DAD7 for 1-day and 2-day
beduetoseveralissues. First,thehighcostsresultingfrom
the deployment of the three architectural decisions, which
outweigh the benefits. Equally importantly, there is inter- itytheywillbedeployedonlyonce. Consequently,weargue
dependence between DADs, for instance both Wifi and FH that the correlation between the DADs should be studied,
capabilitiesareimplementedseveraltimes,althoughinreal- in order to provide better results.
addressed it from sustainability point of view.
Real options approach has been discussed thoroughly in
literatureinvariousdomains,includingsoftwaredesign[30],
software architecture [26], systems design and engineering
[8], software refactoring [30][7], and COTS-centric develop-
ment[14]. Baldwinet. al,[8]enactedtheuseofrealoptions
insystemsdesignandengineering. Theyempathizedonthe
contributionofmodularityonsystemdesignsintheformof
realoptions. Similarly,Sullivanetal.[31],establishedtheuse
of real options in software engineering. They proposed an
options-basedanalysisapproachtoevaluatetheuseofspiral
model in software development [30][29]. A common goal of
modelisminimisingtheuncertainty,providingalternatives,
and hence making decision based on prior knowledge from
phases. This is analogous to option to defer a decision of
investment until a specific optimal time. Ozkaya et. al[26],
introduced a model that establish the use of real options in
Figure 17: Valuation of Options for the deployment
software architecture. In their approach, a variety of differ-
of DAD , DAD and DAD for 3-day
1 5 7 ent architectural patterns are valued by real options with
respect to their relative impact on system quality goals. In
other words, the main aim is to determine the most suit-
Reflectionoftheresultsonsustainability.
able architecture for deployment, given uncertainty future
This begs to the question: How decision makers and ar-
values. Furthermore, Erdogmus et al. [14] investigated the
chitects can reason about sustainability benefiting from the
meansofvaluingthestrategicflexibilityinsoftwaredevelop-
above results? In our case, we have three possible options.
mentusingrealoptions. Themainobjectiveistostudythe
First, the option to switch similar to switching between
economic incentive of choosing a favourable COTS centric
DADs,whenthereisapayoff. Second,theoptiontowait,so
strategyinaproject. Accordingtotheirresults,realoptions
thatthedecisionmakeranalyticallymonitorstheoptiontree
theory is preferred over Net Present Value (NPV) analysis,
todeterminewhetheritisbeneficialtocontinueorwaituntil
aslatterignoresthevalueoftheflexibilityinCOTS-centric
reaching a more profitable outcome. Ultimately, the option
projects. Real options theory was also employed in CBAM
to abandon, if the option price kept on falling or having a
aimingtourgeaboutthevalueofpostponinganinvestment
zero value throughout the time periods, hence it is wiser
decision in an AS, which in turn enhances CBAM [19].
to stop using that DAD and switch to another favourable
one. Though we have followed a value-based reasoning to
7. CONCLUSIONS
sustainability. Theapplicationhasfocusedontheeconomic
performance diversification over time and its contribution We have described an approach, which makes novel ex-
tosustainability. Ontheotherhand,theapplicationisver- tensionofCBAM.Themethodreasonsaboutdiversification
satile as business goal can be still linked to other dimen- in software architecture design decisions using real options.
sions of sustainability as described in the manifesto [9] and Thefundamentalpremiseisthatdiversificationembedsflex-
value-basedreasoningcanbeemployedasthemechanismto ibilityinanarchitecture. Thisflexibilitycanhavevalueun-
monitor for sustainability. der uncertainty and can be reasoned using Real Options.
Realoptionstheoryprovidesananalysisparadigmthatem-
phasizes the value-generating power of flexibility under un-
6. RELATEDWORK
certainty. Themethodcanbeusedbythearchitectandthe
Over the past decades, in literature, design diversity was decision maker to apprise the value of architecting for sus-
mainly envisaged from the context of the design and code tainabilityviadiversification. Forinstance,themethodcan
levels. Thesewereintroducedtoachievesomequalitygoals, beusedtoinformwhetheranarchitecturedecisionneedsto
such as dependability [10], fault-tolerance [6], and security bediversifiedandtowhatextentitcanbenefitfromdiversi-
[25]. There are two popular methods, N-Version Program- fication. It also discusses how and when diversification can
ming[24]andRecoveryBlockStructure[2],proposedtoob- contributetolong-termvalue(andwhenitmayceasetoadd
tain fault-tolerance. Ipek et. al,[18] introduced core fusion value). Consequently, this value can be used to reflect on
which applies the software diversity by efficiently providing sustainability. The application shows that the method can
fine-grainandcoarse-grainparallelism,sequentialcode,and providesystematicassessmentfortheinterlinkbetweensus-
diversemultiprogrammingphases. Theyaimtosupportdy- tainability and diversity using value-based reasoning. In a
namic adaptation to requirements via workloads. Laperdix nutshell,architectsanddecisionmakerscanbenefitfromthe
et. al, proposed reconfiguration diversified approaches to visualisation of the value to assess the extent to which di-
constructadefenceagainstbrowserfingerprinttracking[23]. versificationofthearchitecturedesigndecisionscansustain
Obviously,theonlycloselyrelatedworkisofSonget. al[28], the software system.
who recently proposed a diversification architecture“Diver-
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