Mobility Management Algorithms for the Client-Driven Mobility Frame System–Mobility from a Brand New Point of View

Fülöp, Péter; Kovàcs, Bálint; Imre, Sándor

doi:10.1155/2009/937358

Cited by 3 publications

(4 citation statements)

References 18 publications

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“…Several fast handover schemes have been proposed. Mobility prediction proposed by Fülöp et al [13] and the Client-based Mobility Frame System also introduced by Fülöp et al [14] are two examples. Yang et al [25] considered self-similarity in data traffic, handover, and frequency reuse to estimate the spectrum requirements of mobile networks so as to speed up communication and shorten SDT.…”

Section: Level3 Tek Exchangementioning

confidence: 99%

A Handover Security Mechanism Employing the Diffie-Hellman Key Exchange Approach for the IEEE802.16e Wireless Networks

Ciou

Leu

Huang

et al. 2011

Mobile Information Systems

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A handover security mechanism employing the Diffie-Hellman key exchange approach for the IEEE802.16e wireless networks Abstract. In this paper, we propose a handover authentication mechanism, called the handover key management and authentication scheme (HaKMA for short), which as a three-layer authentication architecture is a new version of our previous work, the Diffie-Hellman-PKDS-based authentication method (DiHam for short) improving its key generation flow and adding a handover authentication scheme to respectively speed up the handover process and increase the security level for mobile stations (MSs). AAA server supported authentication is also enhanced by invoking an improved extensible authentication protocol (EAP). According to the analyses of this study the HaKMA can effectively and efficiently provide user authentication and balance data security and system performance during handover.

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Section: Level3 Tek Exchangementioning

confidence: 99%

A Handover Security Mechanism Employing the Diffie-Hellman Key Exchange Approach for the IEEE802.16e Wireless Networks

Ciou

Leu

Huang

et al. 2011

Mobile Information Systems

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“…the transmission of the data packet begins simultaneously and the time interval of each data packet is fixed. This allows mobile clients to continue receiving a service without disruption when moving across a cell boundary [5,20].…”

Section: Assumptionmentioning

confidence: 99%

“…In this case, D = {d 1 , d 2 , d 3 , d 4 , d 5 }. Starting from d 1, it is analyzed for its relationship with the subsequent data items, namely: d 2 , d 3 , d 4 , d 5 . This process continues sequentially until m-1 data item.…”

Section: Broadcast Ordering Schemementioning

confidence: 99%

Mobile broadcast services with MIMO antennae in 4G wireless networks

et al. 2011

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The deployment of wireless data broadcast to empower mobile information services as a resource-conserving means offers significant benefits due to the scalability feature offered by the technology. In this paper, we present a novel and holistic data broadcast management approach in 4 G wireless networks with multiple-input multipleoutput (MIMO) antennae. The proposed scheme consists of three elements, namely: (i) broadcast ordering; (ii) Global indexing; and (iii) merging data structure. With the integration of these elements, we expect to obtain substantial efficiency for mobile computing clients when retrieving data on-air. We have experimentally evaluated the performance of the proposed model including comparison with the relevant schemes. The results from the experiments affirm the effectiveness of our proposed approach in respect to minimizing query access time and conserving energy utilization of the clients.

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“…We define the basic notations that we use is the article. The basic model will resemble to the abstract one in our previous work [11,12].…”

Section: Basic Notations and Descriptionsmentioning

confidence: 99%

General mobility modeling and location prediction based on markovian approach constructor framework

Szálka¹,

Fülöp²,

Imre³

2011

Per. Pol. Elec. Eng.

Self Cite

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Nowadays, in the wireless networks the number of users and the transferred packet switched data are increasing dramatically. Due to the demands and the market competition the services are becoming more complex, therefore network providers and operators are facing even more difficult network management and operation tasks. The efficient network dimensioning and configuration highly depend on the underlying mathematical model of user distribution and expected data transfer level. In this paper we propose a Markov Movement-model Creator Framework (MMCF) for setting up a model based on the network parameters and requirements with optimal number of states. Firstly we describe a method that gives an abstract model of the mobile network and the node, and we introduce a simple classifying method that defines the necessary parameters of the exact Markov movement model. The mathematical solutions for determining these parameters are also presented in the paper. Finally we analyze the accuracy, complexity and usability of the proposed MMCF and an analytical comparison is made with other mobility models, the comparison is justified with simulations. The movement model created with the framework helps the network operators in setting up an effective authorization, fraud detection system or solving self-configurations issues.

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Mobility Management Algorithms for the Client-Driven Mobility Frame System–Mobility from a Brand New Point of View

Cited by 3 publications

References 18 publications

A Handover Security Mechanism Employing the Diffie-Hellman Key Exchange Approach for the IEEE802.16e Wireless Networks

A Handover Security Mechanism Employing the Diffie-Hellman Key Exchange Approach for the IEEE802.16e Wireless Networks

Mobile broadcast services with MIMO antennae in 4G wireless networks

General mobility modeling and location prediction based on markovian approach constructor framework

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