scispace - formally typeset
Search or ask a question
Proceedings ArticleDOI

Trajectory Prediction and Data Filtering for Mobile Networks

TL;DR: The project proposes a trajectory prediction which estimates the users futures movement based on the information of the past movements of the user, and recommends a filtering mechanism, which avoids the unwanted data to be sent to the user by the server.
Abstract: In today’s modern world people use to move from one place to another regularly. So there is a need for a mechanism which gives mobile user the necessary information about the new location. The proposed project implements two such mechanisms known as Pull technology and Push technology. The project proposes a trajectory prediction which estimates the users futures movement based on the information of the past movements of the user. Mobility prediction algorithm comprises of three modules. The system can allocate the resources to the most probable cell with the prediction module instead of allocating excessive resources blindly to the neighboring cells of the user. Also recommends a filtering mechanism, which avoids the unwanted data to be sent to the user by the server. We propose two mechanisms for the filtering of data.
References
More filters
Book
01 Jan 2000

1,441 citations

Book
02 Aug 2002
TL;DR: Focusing on qualitative descriptions and the realistic explanations of relationships between wireless systems and performance parameters, this user-friendly book helps you learn this exciting technology through relevant examples, such as understanding how a cell phone starts working as soon as they get out of an airplane.
Abstract: Learn how wireless systems work, how mobility is supported, what the underlying infrastructure is and what interactions are needed among different functional components with INTRODUCTION TO WIRELESS AND MOBILE SYSTEMS, 4e. Focusing on qualitative descriptions and the realistic explanations of relationships between wireless systems and performance parameters, this user-friendly book helps you learn this exciting technology through relevant examples, such as understanding how a cell phone starts working as soon as they get out of an airplane.

667 citations

Journal ArticleDOI
TL;DR: The overall conclusion is that a location-area based location management method designed around a profile or history-based direction information offers the absolute best performance, in terms of location management cost, compared to all other alternative approaches.
Abstract: This paper actualizes the classification of location management methods published up to now and presents results of a related extensive performance comparison of the most important paradigms for location management in cellular networks. First, a universal structure of a performance analysis framework for location management methods is defined and analyzed. Then, both a user mobility model and a specific simulation environment claiming to be as realistic as possible are suggested and implemented. Finally, the simulation framework obtained is used for a systematic comparative performance analysis of a representative sample of the most important location management schemes. The overall conclusion is that a location-area based location management method designed around a profile or history-based direction information offers the absolute best performance, in terms of location management cost, compared to all other alternative approaches. The key difference from previous works in literature is clearly underlined concerning both mobility modeling and novel location management schemes.

101 citations

Journal ArticleDOI
TL;DR: A new analytical model is established available for the analysis of the important dynamic movement-based location management method for PCS networks with real HLR/VLR architecture.
Abstract: Location management is a key issue in personal communication service (PCS) networks. Performance analysis plays important roles in the implementation of location management methods and system design in PCS networks. Existing PCS networks have the home location registers (HLRs) and visitor location registers (VLRs) architecture for location management. Some interesting dynamic location management methods are proposed to improve the system performance of PCS networks. However, the existing performance analysis of the dynamic location management methods are too simple and not available for PCS networks with real HLR/VLR architecture. One of the reasons is the complexity and difficulty of the problem. In this paper, we challenge the problem and successfully establish a new analytical model available for the analysis of the important dynamic movement-based location management method for PCS networks.

98 citations

Journal ArticleDOI
TL;DR: The use of cellular automata (CA) combined with genetic algorithms to create an evolving parallel reporting cells planning algorithm to solve a wide range of location management scenarios is investigated.
Abstract: Location management is a very important and complex problem in mobile computing. There is a need to develop algorithms that could capture this complexity yet can be easily implemented and used to solve a wide range of location management scenarios. The paper investigates the use of cellular automata (CA) combined with genetic algorithms to create an evolving parallel reporting cells planning algorithm. In the reporting cell location management scheme, some cells in the network are designated as reporting cells; mobile terminals update their positions (location update) upon entering one of these reporting cells. To create such an evolving CA system, cells in the network are mapped to cellular units of the CA and neighborhoods for the CA is selected. GA is then used to discover efficient CA transition rules. The effectiveness of the GA and of the discovered CA rules is shown for a number of test problems.

86 citations