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Sailaja M
Assistant Professor,PVP Sidhartha Instituite and Technology,Vijayawada,
Ramya K
PVP Sidhartha Instituite and Technology,Vijayawada,

ABSTRACT
The next-generation mobile network will support terminal mobility, personal mobility, and service provider portability, making global roaming seamless. A location-independent personal telecommunication number (PTN) scheme is conducive to implementing such a global mobile system.
In this paper, firstly we propose multi tree database architecture consists of a number of database subsystems, each of which is a three-level t also proposes indexing schemes for each type of location databases and analyzes their efficiency and cost in terms of database access time and storage requirement. Tree structure and is connected to the others only through its root. Results have revealed that the proposed database architecture for location management can effectively support the anticipated high user density in the future mobile networks.

1. INTRODUCTION

THE next-generation mobile network will be an integrated global system that provides heterogeneous services across network providers, network backbones, and geographical regions [1]. Global roaming is a basic service of the future mobile networks, where terminal mobility, personal mobility, and service provider portability must be supported. In a wireless network, a node (mobile-phone) will be present in a region and each region will have a MSS. Mss is mobile-switching-station or tower. Each mss will have up to date information of all the nodes under its control. nodes will be continuously roaming i.e. it will change its location randomly. When ever a node leaves a region and enters another region, two region's mss will be updated. Each mss contains two databases namely HLR and VLR.
HLR is home-location-register which contains information about the nodes which are registered to operate in that area. VLR is visitor-location-register which contains location information about the nodes which are current in its area. The main aim of proposed concept is to provide minimum number of updates or evaluations (queries) when various service providers are going to be combined. That is, there will be different nodes under different service provider under a same area. For example, in a region, there will be 1000 nodes for AIRTEL, 1000 nodes for AIRCEL and 1000 nodes for BSNL. AIRTEL, AIRCEL and BSNL are maintaining different towers to handle their calls. But in future, if all the service providers are going to be combined, then the number of users will be increasing tremendously. At that time, the paper tells that the HLR-VLR scheme is not sufficient. Proposed scheme contains three databases db0, db1 and db2. db0 contains service profiles of all nodes globally. db0 is the top-level and it contains pointers for each node to its db1, which in turn contains pointer to one of db2's where that node currently resides. db2 contains copies of service profiles of nodes under it. so, db0 and db2 contains both index file and data file. Db1 contains only index i.e. it contains only pointers to db2. The paper tells that using the proposed architecture, the number of queries (evaluations) will be decreased. This is because since db2 contains data file also, it need not to access db0 every time whenever a node changes its location or a call is established. But in HLR-VLR scheme if more number of nodes resides in a region, then entire process will slow down because of slow time of location update procedures.

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Fig. 1. Proposed multi tree database architecture

The proposed database architecture is motivated by the following.
1) A location-independent PTN provides a basis for global roaming in the next-generation mobile networks where terminal mobility, personal mobility, and service provider portability will be implemented. A mobile subscriber can retain its lifelong PTN regardless of its location and service provider.
2) The multi tree database architecture is much more robust than the one-root hierarchical architecture. In the proposed architecture, an MT’s profile is stored in one of the root databases according to its current location. Thus, each root database only maintains a small portion of the user profiles in the global mobile system. The crash of one root database will not disrupt the operation of other root databases, and the recovery of the failed root database is much easier than in the one-root database architecture where all user profiles need to be recovered once the root is crashed.
3) The multi tree database architecture is scalable, which is crucial to support continuously increasing number of mobile subscriber’s in future mobile networks. When the capacity of a root database is saturated, a new DS is readily added. More importantly, the end-to-end delay in location registration and call delivery will not increase due to such an expansion in the mobile network. On the other hand, with the one-root structure, when the capacity of the root or a high-level database is saturated, more levels of databases need to be added in order to reduce the burden on the root or high-level databases. This will increase the delays in location registration and call delivery.
4) The proposed multi tree database system is easy to expand and maintain in the multi operator environment of a global mobile system. With the multi tree architecture, each service provider can have its own DSs and it is straightforward for a service provider to expand its service coverage by adding new DSs. It is also easy to operate and manage a DS when the DS is wholly owned by a single service provider. The one-root architecture, however, may not have such advantages.
5) No GTT is required in the proposed database architecture, where a signaling message is only sent from a database to another database in an adjacent level within the same sub tree or from a DB0 to another DB0. Since a message sender always contains the address of the receiver in its database, no GTT is required. This greatly simplifies the implementation of the proposed architecture.
In addition to the multi tree location database architecture, this paper also proposes indexing schemes for each type of location databases and analyzes their efficiency and cost in terms of database access time and storage requirement. The location registration and call delivery procedures based on the proposed database structure are also given. Analysis models are developed to study the service response time of each type of databases in the proposed multi tree architecture as well as the end-to-end delays incurred by the proposed location registration and call delivery procedures. The proposed architecture is compared with the one-root architecture as well as the HLR-VLR architecture in terms of the signaling loads due to location registration and call delivery. Numerical results have demonstrated that the proposed database architecture outperforms the one-root architecture and the HLR-VLR architecture, and can effectively cope with the anticipated high access rates to various location databases in future mobile
The remainder of this paper is organized as follows. Section II describes the proposed distributed database architecture for location tracking as well as the indices of the location databases. Section III presents the database searching strategies associated with the location update and call delivery procedures. and conclusions are given in Section IV.

2. MULTITREE DATABASE ARCHITECTURE FOR LOCATION TRACKING

A. Multi tree location Database Architecture
The proposed database architecture for location tracking is a multi tree structure, where each subsystem is a three-level architecture (Fig. 1), referred to as a database subsystem (DS) in this paper. Various DSs may represent networks operated possibly by different service providers. All these DSs are interconnected together via a fixed network, such as PSTN or ATM net- work, and communicate with each other only through their root databases. This architecture can support a multi operator environment which is expected in future mobile networks. In each DS, databases DB0 and DB2 may correspond to the HLR and the VLR in the two-level database system, respectively. Each DB2 may control an RA where a user can roam freely without triggering registrations. Each DB2 is co-located with an MSC, which performs call processing on origination or termination calls. A number of DB2s are grouped into one DB1 and severalDB1s are connected to a single DB0. Each DB1 and DB0 also needs a switch, called the STP, that provides routing functionality for message exchange between various location databases. The DB0 maintains the service profile for each user currently residing in its service area, and maintains an entry for each user in the global mobile system. The entry contains either a pointer to another DB0 where the user is residing or a pointer to the user record that contains a pointer to the DB1 with which the user is currently associated. Each DB1 has an entry for every currently residing user, storing a pointer to the DB2 the user is currently visiting. Every DB2 has a copy of the service profiles of the users currently roaming within its area. With this architecture, the frequency of queries to the higher level databases is greatly reduced due to the locality of calling and mobility patterns.
However, when a call or a location update is not local, more databases—including the large centralized database DB0—need to be visited. This increases the end-to-end delays in call setup and location registration. In addition, as the number of mobile subscriber’s increases, the access time of each database is increased, which also increases the end-to-end delays? To meet the delay demands in call setup and location registration, the number of database levels in a DS has to be limited. Moreover, to support a larger amount of mobile sub- scribers while keeping the end-to-end delays low, it is critical to reduce the access times to the databases. Thus, investigation into efficient database access indices for the location databases is as important as research into the overall location database architecture.

B. Two Efficient Database Indices
A database usually consists of two parts: an index file and a data file. The index file contains an access structure called index, which provides search paths for locating the records in the data file. The index determines the database access time, thereby being the critical component for improving database throughput. Efficient indices should be based on application characteristics such as the types of storage devices available, the affordable storage capacity, the types of queries required, the available keys, etc.
In this paper, we focus on the indices suitable for a variety f databases in mobile systems. There are two classes of indices: the disk-oriented index, such as the B -tree, and the memory-resident index, such as the AVL-tree and the T-tree. While the disk-oriented indices are designed primarily to minimize the number of disk block accesses and to minimize disk space, the memory-resident indices aim to reduce computation time while using as little memory as possible. For real-time applications, the memory-resident indices are preferred due to their much faster access times than the disk-resident indices. The indices can also be classified into the following two categories: the order-preserving indices and the randomizing indices. The primary order-preserving indices include arrays, B-trees, AVL-trees, T-trees, and direct files. The randomizing indices include various hashing indices. Essentially, the direct file is a special form of hashing indices.


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