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312007

A new strategy for mobility prediction in the PCS network

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Last updated: 05 Jan 2025

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Abstract

 Mobility prediction is one of the main challenges that faced Personal Communication Service (PCS) network. It is probable for many users to move among cells (coverage areas) during their calls. Therefore, the network needs to predict their next location in order to reserve another resource in that next cell to keep their calls going on. In this paper, a new strategy is proposed for mobility prediction named Mixed Mobility Prediction (MMP). It is composed of two predictors. The first one is named Association Rules Predictor (ARP), and the second one is called Weighted Ant Colony Predictor 
(WACP). In ARP the prediction is based on Association rules in data mining and detecting the time of calls. In WACP the prediction is based on Ant Colony (AC) in swarm intelligence. In addition to that, roads lead to their predicted next locations, and priority of famous places found in those locations. Finally, MMP merges the decisions of both predictors to get the final accurate decision in the absence of sufficient history for a MT. The proposed approach outperformed the compared the state-of-arts methods in terms of; Prediction Accuracy (PA), and Quality of Measure (QM)  

DOI

10.21608/mjcis.2018.312007

Keywords

PCS network, Mobility prediction, Ant-based system, Association Rules

Authors

First Name

Abeer

Last Name

M. Hekal

MiddleName

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Affiliation

Misr Academy, a HighInstitute of computers Mansoura, Egypt

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Orcid

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First Name

Ahmed

Last Name

I. Saleh

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-

Affiliation

Computer Engineering and Systems Dept., Mansoura University, Mansoura, Egypt

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Orcid

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First Name

Magdi

Last Name

Zakria

MiddleName

-

Affiliation

Computer Science Dept. Mansoura University, Mansoura

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Volume

14

Article Issue

2

Related Issue

42820

Issue Date

2018-12-01

Receive Date

2023-08-10

Publish Date

2018-12-01

Page Start

27

Page End

37

Print ISSN

2090-1666

Online ISSN

2090-1674

Article File

MJCIS_Volume 14_Issue 2_Pages 27-37.pdf

PDF . 1.3MB

Link

https://mjcis.journals.ekb.eg/article_312007.html

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https://mjcis.journals.ekb.eg/service?article_code=312007

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312,007

Type

Original Research Articles.

Type Code

1,784

Publication Type

Journal

Publication Title

Mansoura Journal for Computer and Information Sciences

Publication Link

https://mjcis.journals.ekb.eg/

MainTitle

A new strategy for mobility prediction in the PCS network

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Article

Created At

28 Dec 2024