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Autonomous Migration with Admission Control for Mobiles Affected by Access Network Failures

Published

Author(s)

David W. Griffith

Abstract

The loss of a set of wireless network access resources causes every mobile user that is connected through the failed resources to perform an unanticipated hard handover, resulting in disrupted connections. The users connected to the failed resources can be expected to migrate {\it en masse}to other access points (APs). Those other APs, if already heavily loaded, may restrict the number of incoming users using call admission control (CAC) algorithms. Rejected users will experience loss of connectivity for longer periods of time as they are forced to try to connect to other available APs. This paper quantifies the effect of limited capacity in target APs when multiple isplaced users attempt to connect to them. We first determine a performance bound by developing an optimal reassignment scheme using linear programming. We compare the ILP's performance to that of a distributed approach in which each user migrates to the AP to which it is closest. We next derive expressions for handover success probability and the mean number of displaced users that are successfully admitted on their first attempt, given that displaced users randomly choose an AP from a set of available ones. This leads to a simple probabilistic scheme that displaced users can use in a decentralized manner to minimize crowding effects at target APs.
Proceedings Title
Next Generation Public Safety Communication Networks and Technologies
Conference Dates
June 14-19, 2009
Conference Location
Dresden, DE
Conference Title
IEEE ICC (International Conference on Communications)

Keywords

call admission control (CAC), failure recovery, integer linear programs

Citation

Griffith, D. (2009), Autonomous Migration with Admission Control for Mobiles Affected by Access Network Failures, Next Generation Public Safety Communication Networks and Technologies, Dresden, DE, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=890038 (Accessed April 19, 2024)
Created June 18, 2009, Updated February 19, 2017