Title
An knowledge model for self-regenerative service activations adaptation across standards
Abstract
One of the greatest challenges for dependable service-oriented software systems of next generation is coping with the complexity of required adaptation or reaction to the detected unforeseen vulnerability attacks. To this end, autonomic system[1] has been advocated as a way to design self-protective systems to defend against malicious attacks or cascading failures. However, other initiatives such as the self-regenerative system[2] adopt the biological-inspired [2, 3]notions such as natural diversity and self-immune as a main strategy to achieve the robust and adaptable self-protection. Based on an ongoing research into self-regenerative programming model, this paper presents a knowledge-centric approach for supporting the runtime automated generation of software adapters for cross-standard service activation; and argues the importance of application of a semantic knowledge to extract the notion of self-regenerative adaptation from the previous polyarchical middleware implementation. The benefit of this will be the production of a customizable self-regenerative adaptation service; and also, support for abstraction integration between domain of similar interests or others in a high-level management directed towards building autonomic systems in a large domain of interest.
Year
DOI
Venue
2005
10.1007/11596448_160
CIS (1)
Keywords
Field
DocType
self-regenerative programming model,self-regenerative service activations adaptation,large domain,knowledge model,dependable service-oriented software system,self-regenerative system,customizable self-regenerative adaptation service,self-regenerative adaptation,cross-standard service activation,required adaptation,next generation,autonomic system,programming model,middleware
Middleware,Knowledge representation and reasoning,Autonomic computing,Programming paradigm,Computer security,Computer science,Software system,Software factory,Software architecture,Personalization
Conference
Volume
ISSN
ISBN
3801
0302-9743
3-540-30818-0
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Mengjie Yu1552.88
David Llewellyn Jones200.34
A. Taleb-Bendiab338348.64