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Network and Service Management Taxonomy

IFIP WG6.6, together with IEEE-CNOM, the IRTF-NMRG and the Emanics Network of Excellence, have developed a taxonomy for network and service management. The goal of this taxonomy is to structure the research area in terms of a two-level, well-defined set of keywords. These keywords can be used by authors to annotate their papers and, more generally, by researchers to indicate their area of expertise and interest. By matching paper keywords to reviewers expertise, organizers of journals and conferences can use this taxonomy to improve quality of reviews.

The taxonomy has two levels: the first level indicates a broad area, whereas the second level refines that area. Keywords from both levels can be used to annotate papers and express areas of expertise. Since keywords are not orthogonal, multiple keywords may be selected. The taxonomy has already been implemented in JEMS, and will also be used for journals such as IJNM. Note that, if desired, authors and conference organizers can extend the taxonomy for their specific purpose. The keywords defined in this taxonomy should not be modified, however.

Note that the Association for Computing Machinery (ACM) has also created a two level classification system, which structures the general area of computer-science. This system has been taken over by others, including IEEE. The network and service management taxonomy can be seen as an extension of that system.

Network and Service Management Taxonomy:

  1. Network Management
    • Ad-hoc networks
    • Wireless & mobile networks
    • IP networks
    • LANs
    • Optical Networks
    • Sensor Networks
    • Overlay Networks
  2. Service Management
    • Multimedia service management (e.g., voice, video)
    • Data service management (e.g., email, web)
    • Hosting (virtual machines)
    • Grids
  3. Business Management
    • Legal & ethical issues
    • Process management
  4. Functional Areas
    • Fault management
    • Configuration management
    • Accounting management
    • Performance management
    • Security management
    • SLA management
    • Event management
  5. Management Approaches
    • Centralized management
    • Distributed management
    • Autonomic and self management
    • Policy-based management
  6. Technologies
    • Protocols
    • Middleware
    • Mobile agents
    • P2P
    • Grid
    • Data, information, and semantic modeling
  7. Methods
    • Control theories
    • Optimization theories
    • Economic theories
    • Machine learning and genetic algorithms
    • Logics
    • Probabilistic, stochastic processes, queuing theory
    • Simulation
    • Experimental approach
    • Design