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Stochastic control of inter-switch handoff and location update in wireless cellular networks Wong, Wai-Shuen Vincent
Abstract
One of the issues in mobility management is to support handoff. When the mobile user moves from one location to another, the network should ensure that all ongoing connections are rerouted to another access point in a seamless manner. Part of our work focuses on connection rerouting due to inter-switch handoff in wireless ATM networks. Although fast local connection rerouting minimizes handoff delay, the end-to-end path after rerouting may become "suboptimal", which implies an inefficient use of network resources. Path optimization may be necessary afterwards. Our research begins with the following question: "How often should path optimization be performed?" To this end, we propose three path optimization schemes (namely: exponential, periodic, and Bernoulli), which are simple to implement. Closed-form solutions of the optimal operating point are derived for each scheme. We further investigate this problem and propose a stochastic model to determine the optimal time to initiate path optimization. Link cost and signaling cost functions are introduced to capture the trade-off between the network resources utilized by a connection and the signaling and processing load incurred on the network. Results indicate that the optimal policy derived from our model has a better performance compared to other heuristics. Another issue in mobility management is to track the location of the users between call arrivals. Although it has been shown that the distance-based location update algorithm has a better performance than the movement and timer based schemes, the determination of the optimal distance threshold is often based on certain unrealistic assumptions. We propose a stochastic model to study the distance-based update algorithm. Our model is applicable to arbitrary cell topologies and the cell residence time can follow general distributions. We consider Markovian movement patterns in which the probability that the mobile user moves to a particular neighboring cell can depend on the location of the current cell or a list of cells recently visited. Results indicate that the distance thresholds determined from our model have a better performance than those derived from a hexagonal cell configuration with random walk movement pattern.
Item Metadata
Title |
Stochastic control of inter-switch handoff and location update in wireless cellular networks
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2000
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Description |
One of the issues in mobility management is to support handoff. When the mobile
user moves from one location to another, the network should ensure that all ongoing
connections are rerouted to another access point in a seamless manner. Part of our work
focuses on connection rerouting due to inter-switch handoff in wireless ATM networks.
Although fast local connection rerouting minimizes handoff delay, the end-to-end path
after rerouting may become "suboptimal", which implies an inefficient use of network
resources. Path optimization may be necessary afterwards. Our research begins with the
following question: "How often should path optimization be performed?" To this end, we
propose three path optimization schemes (namely: exponential, periodic, and Bernoulli),
which are simple to implement. Closed-form solutions of the optimal operating point are
derived for each scheme.
We further investigate this problem and propose a stochastic model to determine
the optimal time to initiate path optimization. Link cost and signaling cost functions are
introduced to capture the trade-off between the network resources utilized by a connection
and the signaling and processing load incurred on the network. Results indicate that the
optimal policy derived from our model has a better performance compared to other heuristics.
Another issue in mobility management is to track the location of the users between
call arrivals. Although it has been shown that the distance-based location update algorithm
has a better performance than the movement and timer based schemes, the determination
of the optimal distance threshold is often based on certain unrealistic assumptions. We
propose a stochastic model to study the distance-based update algorithm. Our model is
applicable to arbitrary cell topologies and the cell residence time can follow general distributions.
We consider Markovian movement patterns in which the probability that the
mobile user moves to a particular neighboring cell can depend on the location of the
current cell or a list of cells recently visited. Results indicate that the distance thresholds
determined from our model have a better performance than those derived from a hexagonal
cell configuration with random walk movement pattern.
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Extent |
5927921 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-07-20
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0065351
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2000-05
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.