Two-level forwarding pointers-based cache scheme for location management in PCS networks

Ramadan, Salah; Sherbini, A. El; Zaki, Mohamed H.; Marie, Mahmoud

doi:10.1109/mwscas.2003.1562316

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…Let a receiver antenna is separated from a base station by a distance, R. Then, the free space power received is given by (6).…”

Section: The Power Constraintmentioning

confidence: 99%

“…In [6], the relation between the cost of smallscale location management and the number of LAs is discussed. The study shows that the list size can be increased up to certain threshold point since after this point the cost of location management is not acceptable.…”

Section: The List Size Constraintmentioning

confidence: 99%

“…This constraint controls in the length of forwarding pointer chain from Mobile Agent/VLR to another agent and the length of forwarding pointer chain from VLR to VLR as discussed in [7]. For high mobility users, the longer the chain length is the more reduction in the total cost of large-scale roaming, but the more setup delay.…”

Section: The Setup Delay Constraintmentioning

confidence: 99%

See 2 more Smart Citations

An Integrated Model to Design PCS Networks

Ramadan

Sherbini

Marie

et al. 2006

Wireless Pers Commun

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An integrated model is proposed that comprises essentially, an Enhanced Profile-Based Strategy (EPBS) for small-scale roaming and a Caching Two-Level Forwarding Pointer (C2LFP) strategy for large-scale roaming. The idea behind the integrated model is how those two location management solutions are applied, and what is the suitable approach to specify the physical parameters of PCS networks from mobility management's point of view so that our solutions can be more cost effective for location management. An evolutionary method, using a constrained Genetic Algorithm (GA) has been used to achieve network parameters optimization. For convenience, we selected the underlying planning problem with an appropriate set of parameters so that it can be treated, in what follows, both genetically and analytically. Thus one can easily verify the accuracy and efficiency of the evolutionary solution that would be obtained from the genetic algorithm. For more realistic environments, GA could be used reliably to build up sophisticated models that integrate the small-scale and large-scale roaming parameters of PCS networks. The results that have been obtained from a case study are presented in order to provide a deep explanation for the proposed integration approach.

show abstract

“…Let a receiver antenna is separated from a base station by a distance, R. Then, the free space power received is given by (6).…”

Section: The Power Constraintmentioning

confidence: 99%

Section: The List Size Constraintmentioning

confidence: 99%

Section: The Setup Delay Constraintmentioning

confidence: 99%

See 1 more Smart Citation

An Integrated Model to Design PCS Networks

Ramadan

Sherbini

Marie

et al. 2006

Wireless Pers Commun

View full text Add to dashboard Cite

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Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

Zaki

Ramadan

2009

Handbook of Research on Telecommunications Planning and Management for Business

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The cellular principle is an effective way to guarantee efficient utilization of the offered radio band. Although PCS networks use the cellular principle, the next generation of PCS networks needs more improvements in location management to face the increased number of users. Both an Enhanced Profile- Based Strategy (EPBS) for small-scale roaming and a Caching Two-Level Forwarding Pointer (C2LFP) strategy for large-scale roaming have been proposed. This chapter introduces a model that unites the above two strategies. The idea behind this model is based on applying those two location management strategies and specifying the physical parameters of PCS networks from mobility management’s point of view so that the underlying solutions can be more cost effective for location management. An evolutionary method using a constraint Genetic Algorithm (GA) has been used to achieve network parameters optimization. For convenience, we selected the planning problem with an appropriate set of parameters to be treated both genetically and analytically. Thus one can easily verify accuracy and efficiency of the evolutionary solution that would be obtained from the genetic algorithm. For more realistic environments, GA could be used reliably to solve sophisticated problems that combine the small-scale and large-scale roaming parameters of PCS networks. A case study is presented to provide a deep explanation of the proposed integration approach.

show abstract

Two-level forwarding pointers-based cache scheme for location management in PCS networks

Cited by 2 publications

References 7 publications

An Integrated Model to Design PCS Networks

An Integrated Model to Design PCS Networks

Combining Small and Large Scale Roaming Parameters to Optimize the Design of PCS

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