Peter Fulop

Enhanced Mobility Management Modelling Framework

This paper investigates mobility management strategies from the point of view of their need of signalling and processing resources on the backbone network and load on the air interface. A method is proposed to model the serving network and mobile node mobility in order to be able to model the different types of mobility management algorithms. To obtain a good description of the network we calculate parameters from given topologies that we think are the most important ones. Mobility approaches derived from existing protocols and other, possible mobility scenarios are analyzed and their performance is numerically compared in various network and mobility scenarios. The aim is to give general designing guidelines for the next generation mobility managements on given network and mobility properties.

Mobility management algorithms for the Client-driven Mobility Frame System - mobility from a brand new point of view

In this paper a new mobility management is introduced. The main idea in this approach is that the mobil node should manage the mobility for itself not the network. The network nodes provide only basic services for mobile entities: connectivity and administration. We construct a framework called the Client-based Mobility Frame System (CMFS) for this mobility environment. We developed the CMFS protocol as a solution over IPv4 and we show how to use Mobile IPv6 to realize our concept. We propose some basic mobility management solutions that can be implemented into the mobile clients and give details about a working simulation of a complete Mobility Management System. Example mobility management approaches such as the centralized- and hierarchical- or cellular-like ones are also defined and hints are given what kind of algorithms might be implemented upon the Client-based Mobility Frame System over IPv4 and IPv6 as well. We introduce some example algorithms that can work with the CMFS making mobility management efficient by minimizing signalling load on the network. In the present work modeling and detailed discussion on the parameters of the algorithms is given and comparison to existing mobility approaches and protocols is done. We prepared a simulation to test our protocol and to back up the proposals we provide the reader with simulation results. We stress that still one the most important benefit of our findings is that all the MNs can run different management strategies and can optimize mobility for themselves.

The Accuracy of Location Prediction Algorithms Based on Markovian Mobility Models

The efficient dimensioning of cellular wireless access networks depends highly on the accuracy of the underlying mathematical models of user distribution and traffic estimations. The optimal placement/deployment of e.g. UMTS, IEEE 802.16 WiMAX base stations or IEEE 802.11 WLAN access points is based on user distribution and traffic characteristics in the service area. In this paper we focus on the tradeoff between the accuracy and the complexity of the mathematical models used to describe user movements in the network. We propose a novel Markov chain based model capable of utilizing user’s movement history thus providing more accurate results than other models in the literature. The new model is applicable in real-life scenarios, because it relies on information effectively available in cellular networks (e.g. handover history). The complexity of the proposed model is analyzed, and the accuracy is justified by means of simulation. [Article copies are available for purchase from InfoSci-on-Demand.com]

A Client-driven Mobility Frame System - Mobility Management From a New Point of View

In this paper a new mobility management approach is introduced. The main idea in this approach that not the network but the mobil node should manage the mobility for itself (similarly to the IP concept). The network nodes provides just basic services for mobile entities: connectivity and administration. We construct a protocol called the Client-based Mobility Frame System (CMFS) for this mobility environment. We propose some basic mobility management solutions that should be implemented into the mobile clients and give detail about a working simulation of a complete Mobility Management System. Example mobility management approaches such as the centralized- and hierarchical-or cellular-like ones are also defined and hints are given what kind of algorithms might be implemented upon the Client-based Mobility Frame System. After the theoretical analysis a simulation shows us the applicability of the newly introduced protocol framework.

Precise Location Prediction Algorithms Using Improved Random Walk-based and Generalized Markovian Mobility Models

As in recent 3G UMTS networks the number of users is increasing dynamically and the packet-switched data transfer become dominant, the network providers and operators face the increasing complexity of the network management and operation tasks.

Accurate mobility modeling and location prediction based on pattern analysis of handover series in mobile networks

The efficient dimensioning of cellular wireless access networks depends highly on the accuracy of the underlying mathematical models of user distribution and traffic estimations. The optimal placement/deployment of e.g. UMTS, IEEE 802.16 WiMAX base stations or IEEE 802.11 WLAN access points is based on user distribution and traffic characteristics in the service area. In this paper we focus on the tradeoff between the accuracy and the complexity of the mathematical models used to describe user movements in the network. We propose a novel Markov chain based model capable of utilizing users movement history thus providing more accurate results than other models in the literature. The new model is applicable in real-life scenarios, because it relies on information effectively available in cellular networks (e.g. handover history). The complexity of the proposed model is analyzed, and the accuracy is justified by means of simulation.

Mobility management algorithms for the client-driven mobility frame system: mobility from a brand new point of view

In this paper we introduce some example algorithms that can work with the Client-based Mobility Frame System presented recently by us. In this solution all the logic and structure is transferred from the network to the Mobile Node and thus each individuum can use the resources in a personalized and efficient way. In the present work modeling and detailed discussion on the parameters of the algorithms is given and comparison to existing mobility approaches and protocols is done. We prepared a simulation to test our protocol and to back up the proposals we provide the reader with simulation results. We stress that one the most important benefit of our findings is that all the MNs can run different management strategies and can optimize mobility for themselves.