• DocumentCode
    2364729
  • Title

    Neuron-a wide-area service discovery infrastructure

  • Author

    Hsiao, Hung-Chang ; King, Chung-Ta

  • Author_Institution
    Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    455
  • Lastpage
    462
  • Abstract
    A wide-area service discovery infrastructure provides a repository in which services over a wide area can register themselves and clients everywhere can inquire about them. We discuss how to build such an infrastructure based on the peer-to-peer model. The proposed system, called Neuron, can be executed on top of a set of federated nodes across the global network and aggregate their resources to provide the discovery service. Neuron is self-organizing, self-tuning, and capable of tolerating failures of nodes and communication links. In addition, it allows the services to be described with arbitrary forms and the system load to be distributed evenly to the nodes. Neuron also supports event notification. We evaluated Neuron via simulation. The preliminary results show that service registration, discovery and service state advertising take at most O(log N) hops to complete.
  • Keywords
    Internet; data structures; fault tolerance; performance evaluation; telecommunication network routing; wide area networks; Neuron; communication links failures; discovery service; event notification; federated nodes; global network; nodes failures; peer-to-peer model; repository; service registration; service state advertising; wide-area service discovery infrastructure; Advertising; Aggregates; Availability; Computer science; IP networks; Neurons; Peer to peer computing; Registers; Web and internet services; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel Processing, 2002. Proceedings. International Conference on
  • ISSN
    0190-3918
  • Print_ISBN
    0-7695-1677-7
  • Type

    conf

  • DOI
    10.1109/ICPP.2002.1040902
  • Filename
    1040902