A taxonomic framework for autonomous service management in Service-Oriented Architecture

Du Wan CHEUN; Hyun Jung LA; Soo Dong KIM

doi:10.1631/jzus.C1100359

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A taxonomic framework for autonomous service management in Service-Oriented Architecture

Computer & Automation | Updated：2022-12-09

- A taxonomic framework for autonomous service management in Service-Oriented Architecture
- A taxonomic framework for autonomous service management in Service-Oriented Architecture
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 5, Pages: 339-354(2012)
- Affiliations：
  
  Department of Computer Science, Soongsil University, Seoul 156-743, Korea
- Author bio：
  
  [ "Du Wan CHEUN, E-mail: dwcheun@gmail.com" ]
  Hyun Jung LA, E-mail: hjla80@gmail.com
  [ "Soo Dong KIM, E-mail: sdkim777@gmail.com" ]
- Funds：
- DOI：10.1631/jzus.C1100359
  CLC： TP311
- Received：07 December 2011，
  
  Revised：2012-;3-;7，
  
  Published：2012-05
- Accepted：
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Du Wan CHEUN, Hyun Jung LA, Soo Dong KIM. A taxonomic framework for autonomous service management in Service-Oriented Architecture[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(5): 339-354.
DOI：

Du Wan CHEUN, Hyun Jung LA, Soo Dong KIM. A taxonomic framework for autonomous service management in Service-Oriented Architecture[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(5): 339-354. DOI： 10.1631/jzus.C1100359.

摘要

Abstract

Since Service-Oriented Architecture (SOA) reveals the black box nature of services

heterogeneity

service dynamism

and service evolvability

managing services is known to be a challenging problem. Autonomic computing (AC) is a way of designing systems that can manage themselves without direct human intervention. Hence

applying the key disciplines of AC to service management is appealing. A key task of service management is to identify probable causes for symptoms detected and to devise actuation methods that can remedy the causes. In SOA

there are a number of target elements for service remedies

and there can be a number of causes associated with each target element. However

there is not yet a comprehensive taxonomy of causes that is widely accepted. The lack of cause taxonomy results in the limited possibility of remedying the problems in an autonomic way. In this paper

we first present a meta-model

extract all target elements for service fault management

and present a computing model for autonomously managing service faults. Then we define fault taxonomy for each target element and inter-relationships among the elements. Finally

we show prototype implementation using cause taxonomy and conduct experiments with the prototype for validating its applicability and effectiveness.

关键词

Keywords

references

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