A Novel Prediction-Based Location Management Technique for Mobile Networks

A Novel Prediction-Based Location Management Technique for Mobile Networks

Sanjay Kumar Biswash (Department of Informatics Engineering, Faculty of Science & Technology, University of Coimbra Polo II, Coimbra, Portugal) and Chiranjeev Kumar (Department of Computer Science and Engineering, Indian School of Mines (ISM), Dhanbad, Jharkhand, India)
DOI: 10.4018/ijmcmc.2013100102
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In this paper, the authors have proposed a new prediction-based location management scheme for cellular networks. The current mobile switching centre predicts the previous mobile switching center of user, and then imports the data about the mobile terminal from that. For this purpose it uses a prediction table, which is based on the neighboring location areas. The analytical model and formulation presents the conceptual schema of proposed scheme. The performance comparisons and numerical analysis is helpful to find out the efficiency and effectiveness of the proposed system, with respect to existing location management techniques. It has been observed that, the registration cost, and the network overhead at mobile switching center have been reduced in the proposed prediction-based scheme.
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1. Introduction

The new generations of wireless network devices has the facility of communication over mobility and it is managed by mobility management in Personal Communication System (PCS) (Lai & Wu, 2006). The mechanism to deliver the calls during the movement of user is called mobility management and it is one of the key issues in PCS networks. There are many features of mobility management and it has two types: radio mobility and network mobility. The radio mobility consists of handover process and network mobility consists of location management (LM; Biswash and Kumar, 2010; Wu, et al., 2002; Huang, et al., 2008). In this paper, we focus on network mobility.

As the Mobile Terminal (MT) moves around the network, the information stored in location register (databases) may no longer be accurate. To ensure that, call can be deliver successfully a mechanism is required to update the information of the database. This mechanism called LM. For pervasive communication, the LM is mandatory which is use to keep track of the current location of MT (Biswash and Kumar, 2009, 2011, 2011; Chew et al., 2007; Zhang et al., 2009; Zhang et al., 2006; Zhang et al., 2002; Sen et al., 1995). For the efficient LM, whole coverage area of the service provider divided into the small region called location area (LA) and it consist of micro and macro cells (Nocetti et al., 2002). The LM generates the assurance, for successful communications during the movement of MT. It has two components: location update (LU) or location registration (LR) and paging (Zhang et al., 2006). The LU is a process of registering the MT in its new location and paging is a technique to search for the MT in the LA, for delivering the incoming call to MT (Chuon and Guha, 2008) . The cost associated to LR is, LR cost and for paging called paging cost. There are several research works is going on, for enhancing the performance of LM and its associated cost (Lai and Wu, 2006; Maita and Chatterjee, 2008; Feng et al., 2007; Wang et al., 2008; Zhu et al., 2008).

Towards narrowing the dilemma of the LM, two kind of LM scheme has been proposed; static and dynamic (Biswash and Kumar, 2009). The static LM scheme defines the frequency and occurrence of LR independently from any user characteristics and the various static LR schemes are: always update, never update. These static mechanisms allow efficient implementation and low computational requirements, due to the lack of independent user tracking and parameterization. The main drawback of the static scheme is, MT is bounded or refused for the LR. The mobile users are free to move in the LA without updating their location and needs to inform the network only when transitioning to a new LA. For a call to be forwarded to a user, the network must be page to every cell within the LA to determine their precise the location.

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