Intelligent Reduction in Signaling Load of Location Management in Mobile Data Networks

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Author(s)

Kashif Munir 1,* Ehtesham Zahoor 2 Waseem Shahzad 2 Syed Junaid Hussain 2

1. FCIT, King Abdulaziz University, Jeddah, 21589, KSA

2. National University of Computer and Emerging Sciences, Islamabad, 44000, Pakistan

* Corresponding author.

DOI: https://doi.org/10.5815/ijcnis.2016.11.03

Received: 8 Apr. 2016 / Revised: 16 Jul. 2016 / Accepted: 15 Sep. 2016 / Published: 8 Nov. 2016

Index Terms

Location management, distributed mobility management, mobile network, location signaling, machine learning

Abstract

Massive increase in the mobile data traffic volume has recently resulted in a big interest towards the distributed mobility management solutions that aim to address the limitations and drawbacks of centralized mobility management. Location management is an important requirement in a distributed mobility management environment. To provide seamless Internet data services to a mobile node, the location of a mobile node is stored and periodically updated on a location server through a location update message that is sent by the mobile node. In this paper, we propose an intelligent approach of setting the period of sending location update messages on the basis of a mobile node’s patterns of data sessions and IP handovers. We use a machine learning approach on the location server. The results show that our approach significantly reduces the signaling load of the location management and the overall reduction is more than 50%.

Cite This Paper

Kashif Munir, Ehtesham Zahoor, Waseem Shahzad, Syed Junaid Hussain, "Intelligent Reduction in Signaling Load of Location Management in Mobile Data Networks", International Journal of Computer Network and Information Security(IJCNIS), Vol.8, No.11, pp.23-31, 2016. DOI:10.5815/ijcnis.2016.11.03

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