BUSINESS RULE ENGINE-BASED FRAMEWORK FOR SaaS

APPLICATION DEVELOPMENT

Zhang Xiuwei

1,2,3

, He Keqing

, Wang Jian

, Wang Chong

and Li Zheng

State Key Lab of Software Engineering, Wuhan University, Wuhan, China

Computer School, Wuhan University, Wuhan, China

94005 Troops of PLA, Jiuquan, China

Keywords: Business Rule Engine, SaaS, Multi-tenancy, Personalized Customization.

Abstract: Software as a Service (SaaS) is becoming a new direction of software industry in the new cloud computing

era. In order to satisfy business policy changes and personalized requirements from different tenants in SaaS

applications, business rule management must support multi-tenancy and online customization. This paper

proposed a framework based on business rule engine, decoupling of business logic rule from SaaS

application, which makes SaaS application more robust and maintainable. It takes business rule as an

independent and online maintainable part of SaaS application, which could allow tenants to safely upgrade,

delete or create rules during runtime. Finally, a practical case study of absence approval-process in

attendance management system evaluates the effectiveness of the framework.

1 INTRODUCTION

With the emergence of Cloud Computing and

maturity of Service Oriented Architecture (SOA),

the SaaS delivery model has gained popularity, due

to advantages such as lower start-up cost and

reduced time to market. A SaaS vendor owns and

takes the responsibility of maintaining a single

application for multiple tenants who may have

similar but also varying requirements (Kapuruge, et

al., 2011). The service vendor delivers software

functionalities with one single instance software

application running for all of its tenants. The most

ideal case for SaaS vendors is that every tenant feel

comfortable using a completely standardize offering.

However this ideal case usually does not happen in

enterprise software application area. Normally, this

one instance is used by different tenants having

different personalized requirements in terms of data,

process rules, and business rules (Kwok, et al.,

2008). Typically, business data and logic integrate

with other functionalities. In SaaS application,

configurability, multi-tenancy and scalability are the

three key attributes to evaluate the maturity of SaaS

application.

In today’s business environment of relentless

change, software configurability is inevitable since

changes generated by business policies and

operations need to be propagated onto the support

software application. A software system is directly

related to the business system within which it

operates and is thus a manifestation of some

business requirements for operational control and

support of decision making (Wan-Kadir and

Loucopoulos, 2003). Typically, business rules have

been bundled in program code or in database

structures, so it is very hard to upgrade. No matter in

large enterprises or small and medium enterprises

(SME), the business rules change very fast and need

to be adjusted timely. Business Rule Group (BRG)

believes that rules are a first-class citizen of the

requirements world. Traditional information

management systems for business process

configuration are not easy to maintain and are

difficult to expand. This problem becomes

increasingly prominent. There may even be a

situation where business rules changes can cause the

entire system to change (Liu, et al., 2010).

In SaaS application, many tenants are running on

one instance with the availability of 24*7. It is

unimaginable to modify or upgrade the business rule

for one tenant by suspending the whole application.

Meanwhile, it is a horrible disaster for one tenant to

modify its own business rules and affect other

tenants’ rules. In order to dealing with this kind of

345

Xiuwei Z., Keqing H., Jian W., Chong W. and Zheng L..

BUSINESS RULE ENGINE-BASED FRAMEWORK FOR SaaS APPLICATION DEVELOPMENT.

DOI: 10.5220/0003919603450354

In Proceedings of the 2nd International Conference on Cloud Computing and Services Science (CLOSER-2012), pages 345-354

ISBN: 978-989-8565-05-1

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

situation, the SaaS application’s business rules need

to be customized with a flexible method, which

enables organizations of any size to build, execute,

manage, and evolve its own rule-oriented

applications. A rule engine can be viewed as a

sophisticated interpreter of if-then statements. It can

reach a conclusion from a set of facts feed into it and

trigger an appropriate action. So we can use the

characteristic of rule engine to separate the business

logic out of the SaaS application to support online

customization and multi-tenancy with the isolated

rule file with specific tenant who has personal

customization of business rules. Therefore rule

independency and isolation is an essential part in the

development of SaaS application. In this paper, a

business rule engine-based framework was proposed

to help the development of SaaS application with the

personalized customization of business rules, which

is convenient for tenants to change the business rules

on-the-fly and minimize the downtime of the

application during the business rule upgrading or

modification.

In this paper, we only focus on the business

rule’s online customization and multi-tenancy

support, other parts customization like process data,

UI elements, localization, performance monitor and

so on are out of the scope. The next section

identifies the related work and section 3 provides a

clear and concise description of the background.

Section 4 demonstrates our framework and provides

explanation for our framework. Section 5 presents

the implantation representing our case study and is

used to exemplify the potential of our approach.

Section 6 draws conclusions from our work and

identifies the possibilities for future work.

2 RELATED WORK

Business rule customization of software is not a new

issue. And many researchers have done a lot in

traditional applications. Initially, rule based software

tools originate from work carried out in the artificial

intelligence (AI) research community. Companies

were faced with the need to combine domain

expertise with the flexibility to write lots of “if x,

then y” statements over a wide range of variables

without resorting to spaghetti code (Gichahi, 2003).

Orriens (2003) and Vasilecas (2009) have two main

views in dynamic business rule driven software

system design. One of them is to design predefined

executable processes and execute them by using

rules in software system, where processes and

execution rules are derived from business rules using

transformations. And another one discussed in the

work (Vasilecas, 2009), where business rules and

facts describing current business system state are

loaded into inference engine of the software system

and transformed into software system executable

data analysis process according to the results of

logical derivations. Computer scientists and

programmers began developing rule languages and

the corresponding engines that could handle the

conditions and actions needed to satisfy the wide

range of rules. The most successful approach for

doing this has proven to be the Rete algorithm

(Forgy, 1982). Many rule-engine tools and

application development support environments was

applied like Blaze Advisor Builder, BRS RuleTrack,

Business Rule Studio, Haley Technologies, ILOG

Rules, Platinum Aion, etc (Karami and Iijima, 2010).

In SaaS applications, there are still lots of

differences in business rule customization with

traditional applications. These differences include:

z The business rule customization or

configuration for SaaS applications should

support multitenant architecture and each

tenant should have their own customization.

z Not to affect other tenants, SaaS providers

could not suspend the system when some

tenant wants to modify or upgrading the

business rules.

z The customization will be executed by

administrator of tenant, not by developers of

SaaS provider.

z The customization of the business rules should

be simplified and friendly.

Above mentioned differences between SaaS

applications and traditional software have raised

many researches in this new area. Guo (2007)

proposed a multi-tenant supported framework to

support better isolations among tenants in many

aspects such as security, performance, availability,

administration etc. Zhang (2007) proposed a SaaS-

oriented service customization approach, which

allows service vendors to publish customization

policies along with services. If tenant’s

customization requirement is in agreement with

policy after being verified, vendors will update

service accordingly. This approach will inevitably

burden service providers because of tenants’

reasonable customization requirement increments.

Gong (2009) developed ECA process orchestration

architecture to create flexible processes. This

architecture based on both knowledge rules

(separating knowledge from processes) and event-

condition-actions (ECA) mechanisms to provide the

highest level of flexibility. Configurability of SaaS

CLOSER2012-2ndInternationalConferenceonCloudComputingandServicesScience

346

issue was addressed in Ref (Nitu, 2009) who

researched the configurability like user interface,

workflow, data and access control from the different

aspect of SaaS. From the customization and

configuration perspective, Sun (2009) explored the

configuration and customization issues and

challenges to SaaS vendors, clarifies the difference

between configuration and customization. A

competency model and framework has been

developed to help SaaS vendors to plan and evaluate

their capabilities and strategies for service

configuration and customization. In the Ref (Shi, et

al., 2009), a flexible business process customization

framework for SaaS was proposed to solve problems

caused by orchestrating SaaS business process

through BPEL specifications. Kapuruge (2011)

discussed the challenges arising from single-instance

to multi-tenancy, and presented an approach of

Serendip4SaaS to define business processes in SaaS

applications.

To the best of our knowledge, no related work

has combined the rule engine and decision table with

the SaaS application for multi-tenancy support and

online customization. Compared to them, our work

was focused on the perspective of business rule

customization and configuration. In our framework,

each tenant can update their personalized business

rule in SaaS application by online selecting and

modifying corresponding rules. Rule engine was

utilized as the essential part to improve the

flexibility and multi-tenancy for SaaS application,

which makes business rule as an independent and

maintainable part of application.

3 BACKGROUND

3.1 Business Rule Engine

In business, a lot of actions are triggered by rules:

“Order more ice-cream when the stock is below 100

units and temperature is above 25° C”, “Approve

credit card application when the credit background

check is OK, past relationship with the customer is

profitable, and identity is confirmed”, and so on.

Traditional computer programming languages make

it difficult to translate this “natural language” into a

software program. Business rule engine enables

anybody with basic IT skills and an understanding of

the business to turn statements as running computer

code (Browne, 2009). A business rules engine is a

software system that executes one or more business

rules in a runtime production environment. It will

test data objects quickly in the workspace, pick out

rules which meet requirement from loading rule sets,

and generate an instance of rule execution. Figure 1

shows the architecture of rules engine. Pattern

matcher decides which and when rules will be

implemented. The implementation sequence of rules

picked from pattern matcher is arranged in agenda

so that execution engine can execute the rules or

other actions in order. The underlying idea of a rule

engine is to externalize the business or application

logic. Business rules are expressions that describe

and control the processes, operations and behaviour

of how an enterprise, and the applications that

support it, performs. Rules assert influence over

business or system behaviour by recommending

actions to be undertaken. A rule provides its invoker

a directive on how to proceed. Further, rule policies

provide a generalized mechanism for specifying

frequently changing practices, freeing system

components from the burden of maintaining and

evaluating evolving business and system

environments (Jeng, et al. 2004).

Agenda



Pattern

Matcher

(RETE)

Facts

Working

Memor

Knowledge

Base

Action

Facts

Rules

Rule Engine

Figure 1: Basic architecture of rule engine.

3.2 Decision Table

A decision table is a tabular representation used to

describe and analyze decision situations, where the

state of a number of conditions determines the

execution of a set of actions. Many variations of the

decision table concept exist which look similar at

first sight (Vanthienen, 2009). Decision tables are

best suited for representing business rules that have

multiple conditions. Adding one condition is done

by simply adding one row or column. Like the

if/then rule set, the decision table is driven by the

interaction of conditions and actions. The main

difference is that in a decision table, the action is

decided by more than one condition, and more than

one action can be associated with each set of

conditions. If the conditions are met, then the

corresponding action or actions are performed

(Vasilecas, 2006). A column in the entry portion of

BUSINESSRULEENGINE-BASEDFRAMEWORKFORSaaSAPPLICATIONDEVELOPMENT

347

the table is known as a rule. Values which are in the

condition entry columns are known as inputs and

values inside the action entry portions are known as

outputs. Outputs are calculated depending on the

inputs and specification of the program. Figure 2

depicts the basic principle of the decision table.



Decisionrules

forthecase

(DecisionLogic)

Somecase

requiringa

decision

(

)



MakingDecision

Outcome

forthecase

Potential

outputs

Figure 2: The basic principle diagram of decision table.

4 FRAMEWORK

The SaaS application operating on the proposed

SaaS platform is one packaged business application

with web-based user interface to multiple tenants.

Based on the features of business rule engine, we

design and implement a framework for development

of SaaS application with an online business rule

customization. The architecture of framework is

shown as Figure 3. The essence of this framework is

to separate business logics and business rule, and

make the business rule as an independent and

maintainable part, support multi-tenancy. The

objective of this framework is to reach a flexible and

competitive scenario in which it would be easier and

faster to react when changes in demand or business

appear.



Visual Rule Definer

(like Guvnor)

Rule Converter

（DSL File）

SaaS Application



SaaS Operation Platform

PaaS

Business Logic Layer

aaS

Tenant A

Tenant B Tenant C

Platform Admin

Rule

EditorA EditorB

Rule File Set

Rule Engine

Rule Metadata

Rule Repository

Deploys

Spcifies

Figure 3: The business rule engine-based framework.

4.1 Basic Units of the Framework

The proposed framework includes the following

major interrelated parts: BR definer, BR engine, BR

repository, SaaS application and SaaS deployment

system.

BR definer acts as a web-based tool or sub-

system that helps visually manage and create new

business rules, where the business policy can be

changed online by manager, business analysts, and

software developers.

BR Converter is an essential auxiliary tool of

rule engine and responsible for convert the

visualized rule from definer to BR engine

understandable language. It also can translate the

decision table to a specific executable language.

BR engine is a central component which is

responsible for computation and evaluation of the

business rules according to the user's invocation and

request. It can automatically assert the business rules

for specific tenant according to the rule load

metadata from repository.

BR repository is a repository that stores the

rule-related information and supports the flexibility

of rule expression. This component contains two

major parts, rule files set is used to store the

information of business rules including decision

table, “When...Then” based rule file, and DSL file

(Domain Specific Language) and so on. The stored

business rules in the repository are determined based

on the target system's specifications. Rule Metadata

is another important part of repository which

includes the tenant customization and configuration

information for specific tenants. Metadata was

stored in repository as management information to

support multi-tenancy.

SaaS application includes basic functionalities

and business logic layer. And we have separated the

business policy out of code and as an independent

part for upgrading and modification.

SaaS deployment system includes SaaS

operation platform (Platform as a service) and IaaS

(Infrastructure as a Service). In SaaS platform,

administrator will be responsible for management

and deployment of SaaS application. IaaS as a basic

part for SaaS deployment including hardware and

storage part and so on. We will not explain more

details about the SaaS deployment system because

this article is focused on the connection between

Business Rule Management(BRM) and SaaS

application.

Rule editors can configure various business rules

in terms of workflow, activity type, and business

policy by using the Rule Definer tool. Tenant’s

CLOSER2012-2ndInternationalConferenceonCloudComputingandServicesScience

348

business rule configured information is stored

separately in tenant-specific metadata repository.

Rule engine-based framework generates

polymorphic service for individual tenant using

tenant-specific metadata at runtime. Through the

polymorphic service, tenant users feel as if they are

using their own business application while service

instance is shared by every tenant.

4.2 Capabilities of the Framework

SaaS application based on this framework will be

supported with the following capabilities, which also

was the basic requirement for SaaS application

development.

Support of Business Rules Management

Enterprises run their businesses with repeatable

business processes driven by general business rules

for specific situations and customers. These

capabilities allow enterprises to execute business

functionality using independent rule services made

up of executable, declarative rules, rather than being

forced to integrate the logic as code into a system.

Support of Online Maintenance

Current Enterprise applications require a new

application maintenance paradigm that can deliver

faster, easier application modification. Business rule

changes are first identified by the users of the system.

The fastest and safest way to empower these users is

to give them the tools they need to make the

application changes themselves. This can be

achieved by giving them access to easy-to-use rule

maintenance that allows them to maintain the

policies, procedures and rules for which they are

responsible.

Support of Multi-tenancy Customization

As the number of tenants with subscribed SaaS

application grows, specific personalized business

rules are needed for most tenants. In this framework,

we bind Tenant ID with rule files and store the

metadata in repository. In order to support multi-

tenancy, the most important part is the safety of

specific rules with specific tenants. In this

framework, the metadata of rules resolved this

problem.

4.3 Lifecycle of Business Rules in SaaS

In business world, some rule policies are changed

periodic and others are altered disorderly depending

market competition and development. Rule life-

Figure 4: Lifecycle of business rules.

cycle in SaaS is illustrated in figure 4 including rules

creation, edition, activation, deletion, et al. The

whole lifecycle of business rule should be

considered in SaaS development.

Rules Creation

The creation of rules is done by rule editors. A new

rule is available for editing but has to be approved

for deployment.

Rules Edition

Rule edition is the modification of the condition part

or the action part of a rule. To keep track of changes,

only new or deployed rules can be edited.

Deactivated rules must be reactivated before they

can be modified.

Rules Deactivation and Reactivation

A rule can be manually or automatically deactivated.

For example, a rule is automatically deactivated on 1

January 2011, if it is time constrained to function

between 01 January 2008 and 31 December 2010.

An editor may manually deactivate a rule especially

when the regulatory changes. Rule editor may

reactivate a manually deactivated rule.

Rules Deletion

Rules that are no longer in use in the system can be

removed from the system by deletion.

BUSINESSRULEENGINE-BASEDFRAMEWORKFORSaaSAPPLICATIONDEVELOPMENT

349

Rules Deployment

Rules are deployed into the repository will be

reacted immediately by making a snapshot of

isolation for the deployed rules in SaaS application.

5 CASE STUDY

5.1 Motivation

In order to evaluate the proposed framework, we

will illustrate a business rule online customization

process via an example. We take Attendance

Management System (AMS) as the domain we do

experiment. AMS is an easy way to keep track of

attendance for enterprises, school activities, church

groups, and community organizations. It has become

as the necessity application for workforce

performance monitoring and evaluation. The

objective of this case was developing a multi-

tenancy supported AMS application with the online

customization. In order to show variation of business

rule for specific tenant, we demonstrate a roadmap

of rule policy from elicitation, presentation to

implementation by the process of absence approval

for sickness in AMS.

In most enterprises, the approval process for

employee who applied for the absence of sickness,

personal reason or salary holiday has different rules.

Here we show a simplified absence of sickness

approval process in AMS as a case to show the

variation of rules for different tenants. The approval

process of absence policy for sickness depends on

the absence days and other conditions like total

absence days in month, total absence days in year,

duration time and so on.

A simplified approval process depending only on

condition of absence days is depicted on Figure 5.

The whole approval process divides into four

situations, if the absence days not exceed the Level-

1’s limit. Only Level-1 approval is needed. If the

absence days over Level-1 and located in the Level-

2’s scope. The approval process will need both

Level-1 and Level-2. Normally Level-2’s approval

will executed after Level-1 approval passed except

for emergency situation. Level-3 and Level-4’s

approval have the similar approval procedure.

The following italic description outline the three

tenants A, B, C who has different approval process

and rule policies.

Tenant A. Absence days for sickness less than or

equal one day will be approved by team leader

(Level-1). From one day to five days absence will be

needed

both team leader and Human Resource

AbsenceApproval

Application

Tea mLeader

Approval

HRDirector

Approval

Deputy‐CEO

Approval

CEO

Approval

Start absence approval

lication

To the end

To: higher level

approval

To: higher level

approval

To: highest level

approval

Decision making by rule policy

Level-1 Level-2 Level-3

Level-4

Figure 5: Absence approval process of tenant C.

Department approval (Level-2). And more than five

days will be permitted by Manager (Level-3).

Tenant B. Absence days for sickness less than or

equal two days will be approved by team leader

(Level-1). And more than two days will approve by

Human Resource Department (Level-2).

Tenant C. Absence for sick leave less than or equal

one day will be approved by team leader (Level-1).

From one day to five days absence will be needed

both team leader and Human Resource Department

approval (Level-2). From five days to ten days

absence will be approved by team leader, Human

Resource Department and deputy-CEO approval

(Level-3). And more than ten days need to be

permitted by team leader, HR director, deputy CEO

and CEO (Level-4).

5.2 Representation of Business Rule

Different enterprises have their own rule policies for

absence approval like above mentioned. Here we

take Tenant C’s rules as a case to demonstrate how

to fill these rules into decision table.

Step1, Definition of the Terms

Here we draw up a list of all condition statements

and actions that are mentioned in the text. It is clear

that this example only uses absence days as the

condition to determine which level of approval will

be executed. The following table lists all related

occurrences of these terms in the text.

Table 1: Rule condition statement and action statement.

Condition Statement Action Statement

Absence Days

Absence Days <=1

1<Absence Days<=5

5<Absence Days<=10

Absence Days >10

Permission level

Team leader (L-1)

HR Director(L-2)

Deputy CEO(L-3)

CEO(L-4)

CLOSER2012-2ndInternationalConferenceonCloudComputingandServicesScience

350

Step 2, Verification of the Decision Rules

Based on the text of the regulations and conditions,

the condition states and the actions, we now can

proceed by defining the rules, analyzing each line in

the regulation and translating it into a rule. Absence

approval rule of Tenant C was built here as example.

z Absence days for sickness less than or equal

one day will be approved by team leader.

Rule 1: Absence Days <=1

Action: Level-1 Approved (team leader)

z From one day to five days absence will need

both team leader and Human Resource

Department approval.

Rule 2: 1< Absence Days <=5

Action: Level-1(team leader) and Level-2

(Human Resource Director) approval.

z From three days to ten days absence will be

approved by team leader, Human Resource

Department and deputy-CEO approval.

Rule 3: 5< Absence Days <=10

Action: Level-1, Level-2 and Level-3(deputy-

CEO) approval.

z And more than 10 days will be permitted by

team leader, HR Director, deputy-CEO and

CEO.

Rule 4: Absence Days >=10

Action: Level-1, Level-2, Level-3 and Level-

4(CEO) approval.

Step 3, Filling the Decision Table

After specifying the decision rules, it is needed to

fill them into the appropriate combinations in the

decision table as depicted in Table 2. The key point

to keep in mind is that in a decision table, each row

is a rule, and each column in that row is either a

condition or action for that rule. “ ※ ” indicates

actions in the combination will be activated, and “○”

means action will not activated by rules.

Table 2: Decision table for absence approval rule.

Absence Days (ADs) <=1 1<Ads<=5 5<Ads<=10 >10

Team Leader Approval

※ ※ ※ ※

HR Director Approval

○

※ ※ ※

Deputy-CEO Approval

○ ○

※ ※

CEO Approval

○ ○ ○

※

Step4, Optimization of the Rule Condition

Once a complete validation of the decision table is

finished, the table could be reduced to its minimal

format. The order of the conditions might influence

the number of columns in the contracted table. For

this case, the above condition is already the optimal

one.

5.3 Implementation

In this case, we take Eclipse IDE as the development

environment and java-supported rule engine Drools

as BR engine. Drools introduce the business logic

integration platform that provides a unified and

integrated platform for rule, Workflow, and Event

Processing. Drools 5 is now split into four main

subprojects: (1) Guvnor (BRMS), a centralized

repository for Drools; (2) expert (rule engine); (3)

flow (process/workflow), providing workflow or

process capabilities to the Drools platform; and (4)

fusion (event processing/temporal reasoning),

providing event processing capabilities (Browne,

2009).

Drools expert was used as a rule engine and

Guvnor as a visual business rule definer which allow

browsing and editing the rule set. Generally,

decision table is a useful way to represent

conditional logic in a compact format. This format is

also readily readable and editable by non technical

users and will be suitable for most employees to

understand. Spreadsheets may not be perfect, but

popular and well-understood. So we can use them to

hold the data that we supply to the business rules.

Then use spreadsheets to hold the actual rules in a

decision table format. Drools decision tables can

utilize a spreadsheet (such as Excel, CSV) as the

means to capture decision logic in a user friendly

way. Because of the convenience of decision table

and supportability of Drools, the decision table was

adopted as business rule representation style in our

application. The following figure is the snapshot of

the executable Drools decision table for absence

approval process of Tenant C.

BUSINESSRULEENGINE-BASEDFRAMEWORKFORSaaSAPPLICATIONDEVELOPMENT

351

Figure 6: Snapshot of Drools based on decision table.

In this decision table, the first three lines are the

head information includes RuleSet, Import and

Notes. RuleSet lets Drools know where the header

table begins. Import lets Drools know which

package these rules live in and other imported

additional JavaBeans. Notes line is the comment

information and ignored as it means nothing to

Drools. The following part is the main body of

decision table. The left part of the decision table is

the CONDITION cells, which makes up the “WHEN”

part of the rule. The right part of the decision table is

ACTION cells which give the “THEN” part of the

rules. In Drools, the “WHEN” part of the rules define

the preconditions. The “THEN” part defines

conclusions, decision, actions, or just a new fact

deduced from the knowledge base. The <

preconditions > is also referred to as the left-hand

side (LHS) of the rule, whereas the < conclusions >

is referred to as the right-hand side (RHS). So, we

also can express rules as follow:

LHS (< rule name >) = < preconditions >

and

RHS (< rule name >) = < conclusions >

The first row of decision table could be rendered like

the following DRL rules:

rule "absence approval"

when

em(absence_days>0&&absence_days<1);

then

Tenant.sentToApproval (Level 1);

update (em);

end;

The fragments code for execution of decision table

is demonstrated in Figure 7. It almost has the same

executable code compare with the execution of the

DRL rule files.

In order to support the online customization of

business rule, it is necessary to use visual rule

definer. Guvnor Editor is a user-friendly web editor

which

is powerful enough to modify rules. Tenants

Figure 7: Fragment of Java code for implementation.

can fill in the rule name and rule description, set the

priority of this rule and choose templates to define

business rule in line with their requirements. The

modification of decision table will need to download

the decision table and modified it, then uploads it

with Guvnor. Otherwise, in order to keep the

isolation of business rules for different tenant, we

build the tenant-based security policy on the login

page with different password for different tenant to

prevent the violation of the rules modification. The

visual rule definer of Gnuvor is shown as Figure 8.

Figure 8: Snapshot of decision table creation in Gnuvor.

5.4 Prototype Application

The SaaS application of AWS prototype was

developed followed the proposed framework which

has successfully integrated business rule engine into

CLOSER2012-2ndInternationalConferenceonCloudComputingandServicesScience

352

Figure 9: Snapshots of SaaS application of AMS.

SaaS application. Figure 9 shows a snapshot of the

AMS prototype system, which was successfully

deployed on the SaaS platform of RGPS Cloud

Service Supermarket (Zhang et al., 2011). The

testing work and performance evaluation is now

ongoing and will be completed in other paper.

6 CONCLUSIONS

In this paper, we have overviewed BR engine based

framework and separated three main components

used for such a SaaS application development.

Depending on the proposed framework, it may be

possible to ensure different level of agility by an

instant deployment of changes in the business policy

and immediate reaction to the changes on the market

or competition by changing existing business rules.

Such advances allow SaaS application to be more

transparent, flexible and cost reduction. Although

BR engine based application have more complex

development process in an initial phase, but such a

system is more efficient in further maintenance and

modifications for numbers of tenants with frequently

changing regulations and business policy. Although

the proposed approach is convenient and effective to

modify the rule file and manage the requirement

changes by Rule Engine, it also brings lots of extra

performance consumptions. The consumptions

mainly include the following parts: the time of

compiling rule files, the time of rule matching and

the time of rule conflict resolution and the time for

management of rule metadata.

The work presented here, still in its earlier stage,

on the one hand，business rule isolation for multi-

tenant was not completely resolved by the Guvnor.

So still need to do more work on visual definer for

specific SaaS application. On the other hand, the

performance evaluation work still need to be done in

the future to make sure that the multi-tenant request

response time to in a reasonable and tolerant time.

Moreover we also need to do more experiment to

verify the efficiency of the framework.

ACKNOWLEDGEMENTS

This research project was supported by the National

Natural Science Foundation of China under Grant

No. 60970017 and No.61100018, the Fundamental

Research Funds for the Central Universities under

Grant No.3101034 and No.201121102020004, the

Specialized Research Fund for the Doctoral Program

of Higher Education No.20090141120020.

REFERENCES

Browne P., 2009. JBoss Drools business rules. Packt

publishing. Birmingham-Mumbai.

Forgy C., 1982. Rete: A Fast Algorithm for the many

pattern/many object pattern match problem. Artificial

Intelligence,19 (1982), pp 17–37.

Gichahi H.K.,2003. Rule-based process support for

enterprise information portal. [online]Available at<

http:// www.sts.tu-harburg.de/ pw-and-m-theses/ 2003/

gich03.pdf> [ accessed 29 Sep 2011].

Gong YW., Janssen M., Overbeek S., et al. 2009. Enabling

flexible processes by ECA orchestration architecture.

ICEGOV 09 Proceedings of the 3rd international

conference on Theory and practice of electronic

governance, pp.19-26.

Guo CJ., Sun W., Huang Y., et al., A framework for native

multi-tenancy application development and

Management. The 9th IEEE International Conference

on E-Commerce Technology and The 4th IEEE

International Conference on Enterprise Computing, E-

Commerce and E-Services(CEC-EEE 2007), pp.551-

558.

Jeng JJ., Flaxer D., Kapoor S., 2004 . RuleBAM: A rule-

based framework for business activity Management.

2004 IEEE International Conference on Services

Computing, pp.262-270.

Kang SJ., Kang SW., Hur SJ. A design of the conceptual

architecture for a multitenant SaaS Application

Platform. Computers, Networks, Systems and

Industrial Engineering (CNSI), 2011 First ACIS/JNU

International Conference, pp.462-467.

Kapuruge M., Colman A., Han J., 2011. Achieving multi-

tenanted business processes in SaaS applications. In

WISE 2011, LNCS 6997, pp. 143–157.

Karami N., Iijima J., 2010. A logical approach for

implementing dynamic business rules. Contemporary

Management Research Vol 6(1), pp. 29-52.

Kwok T., Nguyen T. N., Lam L., 2008. Software as a

Service with Multi-tenancy Support for an Electronic

Contract Management Application. 2008 IEEE

BUSINESSRULEENGINE-BASEDFRAMEWORKFORSaaSAPPLICATIONDEVELOPMENT

353

International Conference on Services Computing, pp

179-186.

Liu C., Dong XP., Yang ZQ.,2010. Research of modern

enterprise intelligent system based on rule engine and

workflow. 2010 Intelligent Computing and Intelligent

Systems (ICIS), pp. 594-597.

Nitu, 2009. Configurability in SaaS (software as a service)

applications. ISEC’09, Proceedings of the 2nd India

software engineering conference, pp.19-26.

Orriens B., Yang J., Papazoglou M.P., 2003. A framework

for business rule driven service compostion.

Technologies for E-Services, Vol(2819), pp.14-27.

Shi YL., Luan S., Li QZ, et al, 2009. A flexible business

process customization framework for SaaS. ICIE 09,

WASE International Conference on Information

Engineering, pp.350-353.

Sun W., Zhang X., Guo CJ.,et al. Software as a Service:

Configuration and Customization Perspectives. IEEE

Congress on Services, SERVICES 2008, pp.18-25

Vanthienen J., 2009. Ruling the business: about business

rules and decision tables. [online]Available at: <http://

www.econ.kuleuven.be/tew/

academic/infosys/members/

vthienen/download/papers/br_dt.pdf> [accessed 25

Sep 2011].

Vasilecas O.,2009. The framework for the implementation

of business rules in ERP. Informacijos mokslai,Vol

(49), pp.146-157.

Vasilecas O., Smaizys A., 2006. Business rule based data

analysis for decision support and automation.

International Conference on Computer Systems and

Technologies, CompSysTech’06. pp.191-196.

Wan-Kadir ,W.M.N., Pericles L. 2003. Relating evolving

business rules to software design. Journal of Systems

Architecture 50 (2004), pp.367–382.

Zhang K., Zhang X., Sun W., et al., 2007. A policy-driven

approach for software-as-services customization. The

9th IEEE International Conference on E-Commerce

Technology and The 4th IEEE International

Conference on Enterprise Computing, E-Commerce

and E-Services (CEC-EEE 2007), pp.123-130.

Zhang XW., He KQ., et al., 2011. SaaS service super-

market building model and service recommendation

approach. Journal on Communication (In Chinese),

2011, 32(9A), pp.158-165.

CLOSER2012-2ndInternationalConferenceonCloudComputingandServicesScience

354