SASSY: A Framework for Self-Architecting Service-Oriented

Systems

the main parts of the paper

Over view

The Challenge of Self-Architecting

The SASSY Approach

Service Activity Schemas

Generating the Base Architecture

Self-Architecting

Self Adaptation

The SASSY Development Environment

Overview

• The idea is to provide a way in the distributed system to monitor the computing environment and change it is behavior and requirement in order to make the system friendly with computing environment and to get the best of quality of service.

• This quality can be determined by the services that provide to customer and how such services are helpful for their business.

• Make change to the system with the change in the computing environment by dynamically monitoring the computing environment.

• SASSY (Self-architecting Software Systems) is framework in which the system requirement may change.

• We can imagine SASSY as many service providers are available to provide services at different quality of service level and different cost.

Chapter 1

The Challenge of Self-Architecting

• Changing the software system architecture to obtain the best QoS is complex; because some times to get the best quality it requires some change that may affect the quality and the performance of other services.

For example from paper:

• Replication to improve the system reliability create the system that is more reliable but also costly to deploy and operate.

So we have to take care about stakeholder priority in system architecture change.

Chapter 2

The Challenge of Self-Architecting

• The difficulty of determine and coordinate

1) The requirement can be define by using a visual activity-modeling language which is used by SASSY to determine which service are part of the system and which is are not and how to coordinate those service with system.

2) The difficulty of determines the original system architecture and how can the system automatically change it is architecture with the current system environment to obtain the best QoS.

3) It is NP-hard optimization problem.

• To overcome these challenges SASSY generate near optimal architecture and services to deal with these complexity

The SASSY ApproachChapter 3

Software engineering We have 3 type of software engineering:

1) Services developers : who responsible to develop services and register them in service registry by which the ASSYS can search and find such services

2) Architectures developers: whose responsible to develop QoS architecture pattern such as:

Replication for fault tolerance load balancing for increased throughput mediation for secure communication

software performance engineer use those pattern to define the QoS and determine how such pattern effect the performance.

3) Architectures developers: who develop software adaptations pattern, which is used to dynamically exchange the current execution architecture to another architecture according to the execution environment

• Domain experts

• Specify SAS (service activity schemas) and SSA which express system requirement those requirements are used by SASSY to automatically generate a base system service architectures, then select the optimal architecture by playing the QoS pattern that help to maximize system utility.

MAPE-K

(Monitor, analyze, plan, execute, knowledge) Loop

SASSY runtime self re architecting

(Monitor, analyze, plan, execute, knowledge) Loop

1) SASSY monitoring the current running system component and generate QoS values.

2) The metric QoS values are then pass to the analyzer in order to compute the system utility

3) If the utility is fall the system send a request to the architecture planer to determine the near-optimal architecture.

4) The self-adaptation component executes the changes to the running system through the adaptation patterns.

Service Activity Schemas

• SAS is a visual requirements specification language using (Business Process Modeling Notation BPMN)

Chapter 4

The modeling constructs in SAS

• service sequence scenarios (SSSs)

1) The first step in generating an SAS model is to select the required service and activities from the domain ontology. SAS deferent the local activates from service; that is activates perform from external entities.

2) The domain expert specifies the sequence of interactions among service and activities.

3) Step (2) done by the help of gateways that manage the flow of events.

4) The domain expert specifies the QoS requirement through service sequence scenarios (SSSs) is a well-formed sub graph of SAS it use to manage complexity and ensure autonomy

Gateway example

SAS for monitoring fire emergencies in public buildings

As we see the fire emergencies system contains: smoke detectors and fire sprinklers.This SAS contains three services and a composite activity: 1. Building locator 2. Occupancy awareness3. Building category finderThe start event (SomkeDet) starts two parallel threads of control:1. Emergency phone system tries to contact the building renter. If the system makes contact with the renter, it forwards the phone call to an operator otherwise it sends an investigate event to the police station.2. External building locator service finds the incident physical address. Produce tow external

services: renter awareness (determine the number of renter in the building) building category finder (determine the building type)The system then uses this information to request appropriate assistance.

Generating the Base Architecture

• The SSA provide structural and behavioral models for SASSY.

• The SSA is an up-to-date representation of the running software system.

• The SSA structural models are based on xADL(eXtensible Architectural Description Language)

Chapter 5

• To generate the base architecture from an SAS model, we used a model driven engineering (MDE)

1) We developed a model to model transformer to generate SSA models from SAS models.

2) Services in SAS are transformed to the components and connectors to form the SSA structural model in xADL.

3) The SAS sequence of activities and services are transformed to a coordinator component.

4) SAS has a formal semantics so SAS models can be checked for syntactic correctness and consistency.

5) SASSY can validate behavioral characteristics, such as deadlocks.

Self-Architecting

Software architectural patterns define templates that can be reused to solve the problem of automated generation of architectures.

This pattern contains one or more components that can be linked by connectors.

Each component can be associated with one or more service types, which are provided by one or more service providers.

Also includes one or more QoS metrics

Chapter 6

We have different attributes such as: Response time. Availability.Security.

Which affect the utility functions of QoS.

SASSY combines a utility function into a single global utility function.

SASSY monitors the utility values for the running system and make self-adaptation if one of the utility values is fall.

QoS metrics

Self Adaptation

A software adaptation descript the steps needed to dynamically adapt a system at runtime from one configuration to another without effect its functionality.

An adaptation pattern can be as a state machine that defines the sequence of states services that transmit from an active to a silent state.

A service is active: when it runs in its normal operation.

A service is silent: when the clients no longer communicate with it.

Chapter 7

The SASSY Development Environment

Chapter 8

The main result was developed the model transformation and optimization capabilities as GME plug-ins that can read and manipulate GME models. We use the XTEAM to execute the architecture model with actual service.We create automated generation architecture for SAS model to do it is functionality without any problem and correctly also we make sure about the QoS to obtain the best quality for SOA, and we show how to use the existed tools that help us to simulate and testing our models.