paper-1 service orchestration based on qos and transactional properties using mixed integer...

7/27/2019 Paper-1 Service Orchestration Based on QoS and Transactional Properties Using Mixed Integer Programming Model

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International Journal of Computational Intelligence and Information Security, September 2013 Vol. 4, No. 7ISSN: 1837-7823

4

Service Orchestration based on QoS and Transactional Properties using Mixed Integer

Programming Model

T.Alexander1

andE.Kirubakaran

2

1

Research Scholar, School of Computer Science, Engineering and Applications,Bharathidasan University, Tiruchirappalli, Tamilnadu, India.

2Additional General Manager, SSTP (Systems), Bharat Heavy Electricals Ltd,

Tiruchirappalli, India.

Abstract

Efficient and appropriate selection of web services has become mandatory in the currentinformation age. This paper presents an efficient methodology for selection of web services andincorporation of a transaction processing system in the selection of web services. The initial

process performs the service ranking using pairwise comparison and user assigned values. Theseprovide weights for the web services. Mixed integer programming is used to obtain the bestavailable service with minimum cost. Transaction processing system is used to enabletransactional and QoS aware web services. CWS are often long-running, loosely coupled, andcross organizational applications. In this context, we are interested in transactional behavior ofthe resulting WS composition. The transactional properties of a CWS highly depend on thetransactional properties of its component WSs and on the structure of the workflow.

Keywords: Web service selection; composition of web services; QoS bases service selection;Transaction aware processing

1.

Introduction

Web service is a series of platform-independent operations for cooperative design over anetwork. As services proliferate on the Web, several services may provide similar functionalitieswhile hosted in different sites [1,2]. It is necessary to select the best Web service fromavailable candidates. On the other hand, Web services are overloaded, and it is increasinglydifficult for the users to locate the right Web service at the right time. Therefore, Web servicerecommendation system has emerged to help user select suitable Web services. Quality ofService (QoS) encompasses important functional and nonfunctional characteristics of Webservice [3]. By combining QoS attributes with preferences and needs of users, recommendersystems will more effectively provide the user with intelligent and proactive Web services.

The Web service composition can be viewed as a three step process:

1) composite Web service specification, 2) selection of the component Web services, and 3)execution of the composite Web services. At the first step, the user submits the goal he/she wantsthe composite service achieves, along with some constraints and preferences that need to besatisfied [4]. Workflows can be used to model the composite Web service specification. Duringthe second step, component Web services fulfilling the users goal are selected among a set of


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available services. This WS selection could be done by hand (in this case, steps specification andselection are integrated) or could be automatically decided by the system. When component WSsare selected at design time, the third step of the composition process consists in executing theselected component WS. At runtime, selection and execution of component WS are integratedand the selection is described as dynamic.

While many works have been done for Web service selection, designing a composite Webservice to ensure not only correct and reliable execution but also optimal QoS remains animportant challenge [5]. Indeed, WSs composition based on transactional properties ensures areliable execution, however, an optimal QoS composite Web service is not guaranteed.Moreover, composing optimal QoS Web services does not guarantee a reliable execution of theresulting composite Web service. Thus, QoS-aware and transactional-aware should be integrated.However, the problem is generally addressed from the QoS side or from the transactional sideseparately. The conventional QoS aware composition approaches [6], [7], [8], [9], [10] do notconsider the transactional constraints during the composition process, likewise transactional-aware ones [11], [12], [13], [14], [15] do not consider QoS. As far as we know, only Liu et al. [5]propose a composition model in design time, which captures both aspects in order to evaluate theQoS of a composite WS with various transactional requirements.

However, the authors do not consider the automatic selection step and only analyze the impact ofthe transactional requirements on the QoS of the composite WS. Our research objective is topropose a design-time selection algorithm for automatic WS composition, where transactionaland QoS requirements are both integrated in the selection process. It is evident that such anintegration could only be done by considering first the transactional requirements.

The analytic hierarchy process (AHP) is a structured technique for organizing and analyzingcomplex decisions. It has particular application in group decision making[20], and is used aroundthe world in a wide variety of decision situations, in fields such as government, business,

industry, healthcare, and education.

Rather than prescribing a "correct" decision, the AHP [21] helps decision makers find one thatbest suits their goal and their understanding of the problem. It provides a comprehensive andrational framework for structuring a decision problem, for representing and quantifying itselements, for relating those elements to overall goals, and for evaluating alternative solutions.

Users of the AHP first decompose their decision problem into a hierarchy of more easilycomprehended sub-problems, each of which can be analyzed independently. The elements of thehierarchy can relate to any aspect of the decision problemtangible or intangible, carefullymeasured or roughly estimated, well- or poorly-understoodanything at all that applies to the

decision at hand.

Once the hierarchy is built, the decision makers systematically evaluate its various elements bycomparing them to one another two at a time, with respect to their impact on an element abovethem in the hierarchy. In making the comparisons, the decision makers can use concrete dataabout the elements, but they typically use their judgments about the elements' relative meaning


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and importance. It is the essence of the AHP that human judgments, and not just the underlyinginformation, can be used in performing the evaluations.

The AHP converts these evaluations to numerical values that can be processed and comparedover the entire range of the problem. A numerical weight or priority is derived for each elementof the hierarchy, allowing diverse and often incommensurable elements to be compared to oneanother in a rational and consistent way. This capability distinguishes the AHP from otherdecision making techniques.

In the final step of the process, numerical priorities are calculated for each of the decisionalternatives. These numbers represent the alternatives' relative ability to achieve the decisiongoal, so they allow a straightforward consideration of the various courses of action.

The remainder of this paper is structured as follows; section II provides a complete systemarchitecture, section III provides a complete description of the working system, section IVprovides the results and discussion and section V concludes the study.

2. System architectureThe current process is performed in two phases. The initial web service selection phase fetchesthe appropriate services from the repository, while the service ranking phase analyzes theproperties of the web service and accordingly ranks them for the user perusal.

UserAttributeRankingMixedIntegerProgrammingWebserviceSelectionTransactionAwarewebservicelistWebService1WebServicenWebService2ServiceRankingPairwiseComparisonUserAssignedWeights

Figure 1: Transaction aware QoS Web Service Orchestration and Ranking

Figure 1 provides a complete process of web service selection and ranking. During the serviceranking, user is allowed to provide weights, and if the user is indeterminate about the weights,then, pair wise comparison is performed. Hence each attribute is provided with its corresponding


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rank. Mixed Integer Programming is used to filter out the web services that provide theappropriate functionalities with minimum cost. Finally, transaction awareness is incorporated toprovide a reliable system.

3. Our approachThe current approach is performed in two phases. The initial service selection uses various QoSparameters [19] that define the selection of the system. The various QoS parameters that arebeing used are performance, scalability, reliability, robustness, capacity, exception handling,accuracy, integrity, accessibility, availability, interoperability, security, regulatory and networkrelated QoS. These properties functions as the base in selecting a service for usage in the currentworkflow.

3.1. Service OrchestrationThis process performs the short-listing of services from the main service repository. All theappropriate services are taken from the repository and are passed to the next phase for

performing the ranking process. It performs automated arrangement, coordination, andmanagement of complex services.


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Table 1: QoS Parameter Description

Except

ion

Handling

Exception handling is the process of responding to the occurrence, duringcomputation, of exceptions anomalous or exceptional events requiring specialprocessing often changing the normal flow of program execution. It is provided byspecialized programming language constructs or computer hardware mechanisms.

Performance

Performance is the quality aspect of Web service, which is measured in terms ofthroughput and latency. Higher throughput and lower latency values represent goodperformance of a Web service. Throughput represents the number of Web servicerequests served at a given time period. Latency is the round-trip time betweensending a request and receiving the response.

Integrity Integrity is the quality aspect of how the Web service maintains the correctness of theinteraction in respect to the source. Proper execution of Web service transactions will

provide the correctness of interaction. A transaction refers to a sequence of activitiesto be treated as a single unit of work. All the activities have to be completed to makethe transaction successful. When a transaction does not complete, all the changesmade are rolled back.

Security Security is the quality aspect of the Web service of providing confidentiality and non-

repudiation by authenticating the parties involved, encrypting messages, andproviding access control. Security has added importance because Web serviceinvocation occurs over the public Internet. The service provider can have different

approaches and levels of providing security depending on the service requestor.

Scalabili

ty Scalability is the ability of a web service to handle a growing amount of work in acapable manner or its ability to be enlarged to accommodate that growth.

Regulatory

Regulatory is the quality aspect of the Web service in conformance with the rules, thelaw, compliance with standards, and the established service level agreement. Webservices use a lot of standards such as SOAP, UDDI, and WSDL. Strict adherence tocorrect versions of standards by service providers is necessary for proper invocationof Web services by service requestors.

Networkrelated

QoS

To achieve desired QoS for web services, the QoS mechanisms operating at the webservice application level must operate together with the QoS mechanisms operating inthe transport network (e.g., RSVP, DiffServ, MPLS, etc.) which are ratherindependent of the application. In particular, application level QoS parameters shouldbe mapped appropriately to corresponding network level QoS parameters. Basicnetwork level QoS parameters include network delay, delay variation, and packet loss


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Accessibility Accessibility is the quality aspect of a service that represents the degree it is capable

of serving a Web service request. It may be expressed as a probability measuredenoting the success rate or chance of a successful service instantiation at a point intime. There could be situations when a Web service is available but not accessible.

High accessibility of Web services can be achieved by building highly scalablesystems. Scalability refers to the ability to consistently serve the requests despitevariations in the volume of requests.

Availability Availability is the quality aspect of whether the Web service is present or ready for

immediate use. Availability represents the probability that a service is available.Larger values represent that the service is always ready to use while smaller valuesindicate unpredictability of whether the service will be available at a particular time.Also associated with availability is time-to-repair (TTR). TTR represents the time ittakes to repair a service that has failed. Ideally smaller values of TTR are desirable.

Reliability

Reliability is the quality aspect of a Web service that represents the degree of beingcapable of maintaining the service and service quality. The number of failures permonth or year represents a measure of reliability of a Web service. In another sense,reliability refers to the assured and ordered delivery for messages being sent andreceived by service requestors and service providers.

Accurac

yWeb services should be provided with high accuracy. Accuracy here is defined as theerror rate generated by the web service. The number of errors that the servicegenerates over a time interval should be minimized.

Robustness

Web services should be provided with high robustness. Robustness here represents

the degree to which a web service can function correctly even in the presence ofinvalid, incomplete or conflicting inputs. Web services should still work even ifincomplete parameters are provided to the service request invocation.

Capacity

Web services should be provided with the required capacity. Capacity is the limit ofthe number of simultaneous requests which should be provided with guaranteedperformance. Web services should support the required number of simultaneousconnections.

Interop

erabili

ty

Web services should be interoperable between the different development

environments used to implement services so that developers using those services donot have to think about which programming language or operating system theservices are hosted on.


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3.2. Service RankingService rankings are performed using the weighted sum model of relevant measures. By default,the weights of categories, attributes and measures are set to be equal. Consumers can alter thoseweights based on their preferences. The consumers can either use pairwise comparison methodproposed by Saaty [16,17] or direct arbitrary weight. Analytic Hierarchy Processing is used forperforming the comparison process.

3.2.1. Pairwise ComparisonThe pairwise comparisons are made depending on a 9 point scale. In the pairwise comparisonmatrix, the score of suv represents the relative importance of the component on row (u) over thecomponent on column (v), i.e., suv = wu=wv. The reciprocal value of the expression (1=suv) isused when the component v is more important than the component u. The comparison matrix S isdefined as

1 1 1 2 1 12 1

2 1 2 2 2 21 2

1 2 1 2

/ / / 1

/ / / 1

/ / / 1

n n

n n

n n n n n n

w w w w w w s s

w w w w w w s ss

w w w w w w S s

= =

(1)

Then, a local priority vector (eigenvector) w is computed as an estimate of the relativeimportance accompanied by the elements being compared by solving the following equation:

max ,sw w= (2)

where max is the largest eigen value of matrix S.

3.2.2. User Assigned WeightsThe consumer can assign weights in their own scale rather than using the pairwise comparison.For this case, the weights are normalized. Let uwc denote the user assigned weight for category c,then category weights wc is calculated as follows:

,cc

cc

www c

ww=

(3)


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Let uwca denote the user assigned weight for attribute a and uwam denote the user assignedweight for measures m. Let wa and wam, denote the normalized attribute and measure weightrespectively.

C Category

P Web serviceS Comparison matrix

max Largest eigun value of S

aip Attribute for webservice p

cip Cost of service

did No of services required to complete theworkflow

spc Score of category c for a webservice p

spa Sum of rank category scores

ta Atomicity variable

tc Comparsable variable

tr Retriable variablett Transactional behaviour definer

tsp Ranking total score

ua Minimum required ranking score for anattribute

uc Minimum required ranking sccore for awebservice

uts Minimum required total ranking score

wan Weight for m measure

wca Weight for attribute a

xip No of service provided

yip Binary decision variable

Table 2: List of Notations used

3.3.Service Ranking CalculationLet spa denote the ranking attribute score of an attribute a for a web service p and spam denotethe measure score of a measure m belong to attribute a. The attribute score spa for every attributetype is calculated as follows:

, ,pampa amm

w s ps a= (4)

Subject to


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,1amm

aw =

(5)

Let spac denote the score of the category c for the web service p. The category score Spac is

calculated using weighted sum approach of relevant ranking attributes score Spa and measures m.The ranking category Score Spc for every category type is defined as follows:

, ,papc caa

s p cw s = (6)

Subject to

1,caa

w c=

(7)

Let tsp denote the total ranking score for a service provider p. Total ranking score tsp iscalculated by using weighted sum approach of all rank category scores spac. The ranking totalscore for every web service p is defined as follows.

,c

pcp ct ps w s = (8)

Subject to

1cc

w =(9)

3.4.Mixed Integer ProgrammingIn this section, the mixed integer programming is presented as the core formulation.

Minimize:


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i

i

p

p ipz xc= (10)

Subject to

,ip i

px d i (11)

,ip ip

i

x a p (12)

{ }, , 0,1ppp

nx p x (13)

, ,jp jpy uy j p (14)

, ,pc cs u p c (15)

, ,pa as u p a (16)

,p tsts u p (17)

0 , ,ipx i p (18)

1

0

if provider phascompliancewith property jotherwisejpy {=

(19)

1 '0

{ if all component ws s complete sucessfullyotherwisea

t =(20)

01 { If all the webservices are comparsable

other ec wist =

(21)

10

{ If all the webservices are retriableotherwiser

t =(22)

ex10

{ If all the webservices aibit transactional behaviourotherwit se

t =(23)

The general form of MIP is formulated above. The goal of objective function (10) is to minimizethe total deployment cost. The decision variable xip denotes the number of services provisionedand cip denotes the cost of services. The constraint in (11) maintains that the consumers demandfor a service i is satisfied. In (12), the constraint states that the allocation for a web service must


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not exceed the maximum resources capacity offered. Constraint (13) indicates that the number ofweb services is to be limited for deployment according to the consumer specification andapplication requirements. Constraint in (14) ensures that the providers compliance withconstraints.

Constraints in (15) and (16) ensure that the web services having ranking category and attributescore greater than or equal to the consumer requirement. In (17), the constraint implies that theweb service having a total ranking score greater than or equal to the consumer specified score isconsidered for usage. Constraint (18) indicates that variables accept the values from a set ofnonnegative integers.

3.5. Transaction Aware Web ServicesAtomic CWS:A CWS is atomic if once all its component WSs complete successfully, theireffect remains forever and cannot be semantically undone. On the other hand, if one componentWS does not complete successfully, then all previously successful component WSs have to be

compensated. In the following, is used to indicate an atomic CWS while is used to indicate a

non atomic one.

Compensatable CWS: A CWS is compensatable (c) if all its component WSs arecompensatable.

Retriable CWS: An atomic or a compensatable CWS is retriable (r) if all its components areretriable.

Transactional CWS: A Transactional Composite Web Service (TCWS) is a CWS whose

transactional behavioral property is in { , r,c, cr}

A TCWS[18] takes advantage of component service behavioral properties to specify mechanismsfor failure handling and recovery. It can be composed of elementary WSs, whose properties are

in {p, pr, c, cr}, and/or can be composed of CWSs, whose properties are in { , r,c, cr}

This section shows the process of assigning a WS to each activity in a workflow, in order toobtain a TCWS. For simplicity, we suppose a workflow containing only two activities. We firstconsider the assignation of two WSs to the activities of a sequential pattern.

Proposition 1:

In a sequential pattern, if the WS assigned to the first activity of the pattern is pivot (p), pivot

retriable (pr), atomic ( ), or atomic retriable ( r), then, to obtain a TCWS, the WS assigned to the

second activity should be pivot retriable (pr), atomic retriable ( r), or compensatable retriable

(cr). The Transactional Property (TP) of the resulting TCWS is atomic ( ) and is moreover

atomic retriable ( r) if all its components are retriable.

Proof. If the WS assigned to the first activity of the pattern is p, pr, , or r, then, its effects

cannot be semantically undone, thus the execution of the second WS should guarantee a


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successfully termination. The only condition to guarantee a successfully termination is the

retriable property. Therefore, the WS assigned to the second activity should be pr, r, or cr.

Proposition 2:

In a sequential pattern, if the WS assigned to the first activity of the pattern is compensatable (c)or compensatable retriable (cr), then the resulting CWS is always transactional (TCWS)whatever the TP of the WS assigned to the second activity is. The TP of the resulting TCWS is

atomic ( ) if the WS assigned to the second activity is either pivot (p), pivot retriable (pr), atomic

( ), or atomic retriable ( r). The TCWS TP is compensatable (c) if the WS assigned to the

second activity is either compensatable (c) or compensatable retriable (cr). Moreover, when bothcomponent WSs are retriable, the resulting TCWS is retriable.

Proof. When service WS1 assigned to the first activity of the pattern is c or cr, the resulting

CWS is at least because if the WS assigned to the second activity fails, then WS1 can be

compensated. Moreover, the resulting CWS is c when the WS assigned to the second activity is c

or cr.

4. Results and discussionThe 14 QoS properties are considered for evaluation. 4 web services corresponding to a singleprocess are taken into account. Each webservice is imposed with various criterion and weightedaccording to the QoS parameters. The criteria vales assigned for the QoS parameters defines theimportance of the parameter. This is carried out as a pairwise comparison process.

Figure 2: Criterion weight ratio


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Figure 2 shows the criterion weight ratio in a 100% scale. According to our scenario, we can seethat accuracy has the maximum importance, while network related QoS has the minimumimportance.

Figure 3:Consolidated Ranking

Figure 3 shows the consolidated ranking of various QoS parameters with respect to the servicesproviding them.


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Figure 4: Service Comparison

Figure 4 shows the comparison of services with respect to the QoS parameters.

Figure 5(a): Evaluation in context of: Exception Handling


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Figure 5(b): Evaluation in context of: Performance

Figure 5(c): Evaluation in context of: Integerity


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Figure 5(d): Evaluation in context of: Security

Figure 5(e): Evaluation in context of: Scalability


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Figure 5(f): Evaluation in context of: Regulatory

Figure 5(g): Evaluation in context of: Network related QoS


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Figure 5(h): Evaluation in context of: Accessibility

Figure 5(i): Evaluation in context of: Availability


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Figure 5(j): Evaluation in context of: Reliability

Figure 5(k): Evaluation in context of: Accuracy


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Figure 5(n): Evaluation in context of: Interoperability

Figures 5 (a) to (n) shows the evaluation of services in the context of each QoS parameter. It alsoranks these services accordingly in the graphs.

5. ConclusionMany services exist in the service marts for performing a single process. Selection of theefficient and the most appropriate web service is one of the most important process that improvesthe efficiency of any system. The quality aware selection made by the current proposal takes intoconsideration various parameters defined by the W3C and IBM as the most important qualityattributes that should be provided by a web service. Every web service is evaluated with theseproperties in consideration, and are ranked accordingly. Finally the service with appropriate

properties and least cost is considered for usage. The current proposal also incorporates atransaction based service. Since web services only form a part of the workflow, maintenance ofACID properties becomes a necessity.

Further improvisation can be provided by providing provisions for web service reuse. Increase inservice selection can be performed by caching the top k dominating queries. Dynamic servicecomposition can be performed for efficient functioning.

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(RACSAM) 102 (2): 251318. Retrieved 2008-12-22.
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