Semantic-based Contxt-aware Dynamic Service Composition

http://portal.acm.org/citation.cfm?id=1516533.1516536

Contributions

1. Not only system designers but also end users to specify rules on how to compose context-aware applications
2. It supports both rule-based and learning-based context-aware service composition
3. It utilizes semantic similarities among components to improve its adaptability in a dynamic environment
4. supports seamless service migration which autonomously composes a new application and migrates onto it when user context changes
   

Componetn Service Model with Semantics (CoSMoS)

There is a UML meta model for CoSMoS wichi helps with Defining

• Functional Informaiton
• Semantic Information
  
• Contextual Information
• User specific rules

Component Runtime Environment

CoRE consists of the following pieces

• Dscovery Manager
• Execution Manager
• User Manager

Three methods for context acquisition

1. metadata of the components: context information is embedded in the components metadata
   
2. context-aware discovery or user submodule: acquiring context information through existing context aware technologies
   
3. inference: infer context based on a set of facts

Semantic Graph-based Service Composition (SeGSeC)

two approaches are used

1. Rule-based
2. Learning-based

Problem in creating the workflow is that, semantic correctness of the workflow gets checked at the end of its execution, wherease it can be included in the process of execution so that the semantically valid components get discovered first before actually having to deal with the composition and orchestration of components

The learning algorithm for selecting a component
Pi = max (SSi,j x (CMDj + const)) 1 <= j <= n SS i,j = semantic similarity between two components CMDj = context matching degree. (how well the component matches the context it is used in based on the previous experiments in using this component in this context). To decide about context matching conditioins a C4.5 DT algorithm is used collecting information about a composed workflow. context aware dynamic service composition systems have problems for the following reasons:

1. predefined rules usually cannot be modified once they are deployed
2. it is difficult to define a generic rule that is applicable to every user
   
3. some users preferences may be too complex to define as a set of rules

interesting evaluations for dynamic composition of context-aware services. I skipped the experiments but they might be worth reading.