Call Routing and Data Model for Inter-Network Roaming in PCS

Shigefusa SUZUKI  Takao NAKANISHI  

IEICE TRANSACTIONS on Communications   Vol.E79-B    No.9    pp.1371-1379
Publication Date: 1996/09/25
Online ISSN: 
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on Personal Communications)
Category: Network architecture, signaling and protocols for PCS
personal communication systems,  call routing scheme,  data model,  directory information tree,  

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Personal communication systems (PCS) have more signalling traffic than conventional fixed networks and require large-scale databases to manage users' profiles, which are sets of data items, such as the location the user is currently visiting and the user's authentication key, necessary for a PCS user to be provided with PCS services. This paper focuses on inter-network roaming in PCS environments. In designing a PCS supporting roaming service, it is essential to avoid increased signalling traffic and data searching time in the database. We first identify the appropriate domains for three routing schemes-Direction Routing, Redirection Routing, and Look-ahead Routing-from the viewpoints of the number of signals for inter-network roaming and roaming probability. We do this for two kinds of PCS database network architecture, Home Location Register (HLR) and Visitor Location Register (VLR), and show that Look-ahead Routing is the best scheme for the HLR network architecture (considering the number of signals for intra-network and inter-network database access) and that in the VLR network architecture, the decreasing of the roaming probability expands domains for which Redirection Routing is appropriate. We also propose a generic PCS data model that inter-network roaming interfaces can use to search effectively for a user's profile. The data model clarifies the contents of a set of data items which share certain characteristics, data items that the contents compose, and the relationships (data structures) between sets of data items. The model is based on the X. 500 series recommendations, which are applied for an Intelligent Network. We also propose a data structure between sets of data items using the directory information tree and show the ASN. 1 notations of the data model.