Mobility-Prediction-Aware Bandwidth Reservation Scheme for Mobile Networks

Nadembéga, Apollinaire; Hafid, Abdelhakim; Taleb, Tarik

doi:10.1109/tvt.2014.2345255

Cited by 52 publications

(24 citation statements)

References 37 publications

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“…A distributed bandwidth reservation scheme called the mobilityprediction-aware bandwidth reservation scheme was proposed by Nadembega A. et al [13].…”

Section: R E T R a C T E D A R T I C L Ementioning

confidence: 99%

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RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

Zhou

Dong

2015

J Wireless Com Network

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According to the loss network problems caused by limited resources and environment interference factors, we presented a survivability mechanism based on mobility prediction and based on the topological evolution of cloud computing wireless multimedia sensor network (WMSN). First, based on cooperative neural network and opportunity Markov chain model, the multimedia mobile sensor node state and state transition probability could be predicted. Then, the opportunity computational scheme was given based on mobility prediction of dynamic topology evolution mechanism. Finally, using the network topology reconfiguration and opportunities for cloud computing, an enhanced WMSN survivability and end-to-end quality of service guarantee mechanism was proposed. Experimental results show that compared with the static scheme for WMSNs, the proposed survivability mechanism has the obvious advantage in the node protection, data communication, network life cycle, and decodable frame rate and other aspects, and can effectively improve the invulnerability of WMSNs.

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“…A distributed bandwidth reservation scheme called the mobilityprediction-aware bandwidth reservation scheme was proposed by Nadembega A. et al [13].…”

Section: R E T R a C T E D A R T I C L Ementioning

confidence: 99%

“…In the process of opportunity cloud computing, WMSN topology reconfiguration probability is shown in the formula (13).…”

Section: Ementioning

confidence: 99%

RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

Zhou

Dong

2015

J Wireless Com Network

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“…trains and planes, it is pivotal to consider both the movements of the vehicles and the satellites. The terminals with greater speed are ignored in this paper and for the interested readers, please refer to [10] [11] and [12] for more detailed information.…”

Section: Related Workmentioning

confidence: 99%

A simple real-time handover management in the mobile satellite communication networks

Seyedi

et al. 2015

2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS)

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Low earth orbit (LEO) satellite networks are capable of providing global or regional mobile services for a large number of users. Since the user's service duration may be greater than the coverage time of a LEO satellite, the user may be handed over to another visible satellite to prevent interruption of the ongoing communication. On the other hand, a mobile user may be covered by more than one satellite at the instant of connection handover. When the user is about to be handed over to another satellite, the serving satellite minimizing the number of handovers would in general be the one that provides the largest service time which is not necessarily equal to the coverage time of the very satellite. In this paper, we propose a new handover algorithm which exploits both the Global Positioning System (GPS) infrastructure and satellite diversity to provide a simple and real-time handover management in LEO satellite networks. The proposed algorithm not only minimizes the expected number of satellite handover, but is also efficient and easy to be implemented in hand-held devices, thus facilitating the mobile users' access to the satellite networks. Numerical simulations performed for two typical mobile satellite networks, viz. Iridium and Globalstar, corroborate the advantages gained by the proposed algorithm.

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“…The utility perceived by each player connected to the HSDPA system at time t is as follows:

U_{i}^{t} = U_{h} (n_{w}^{t}) = \frac{C_{h}}{n_{h}^{t}} G (n_{h}^{t})

We denote by

G ((), n_{h}^{t})

the ratio of what the user receives from the base station as compared with a plain fair access scheduling. For Rayleigh fading ,

G ((), n_{h}^{t}) = \sum_{i = 1}^{n_{h}^{t}} \frac{1}{i}

. In this paper, we consider that the two technologies are totally overlapping as shown in Figure (d).…”

Section: Game Theoretic Modelmentioning

confidence: 99%

“…We denote by G n t h the ratio of what the user receives from the base station as compared with a plain fair access scheduling. For Rayleigh fading [11], G n t h D P n t h iD1 1 i . In this paper, we consider that the two technologies are totally overlapping as shown in Figure 2…”

Section: The Utility Functionmentioning

confidence: 99%

Group vertical handoff management in heterogeneous networks

Walid

Kobbane

Mabrouk

et al. 2015

Wireless Communications

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Traditional vertical handover schemes postulate that vertical handovers (VHOs) of users come on an individual basis. This enables users to know previously the decision already made by other users, and then the choice will be accordingly made. However, in case of group mobility, almost all VHO decisions of all users, in a given group (e.g., passengers on board a bus or a train equipped with smart phones or laptops), will be made at the same time. This concept is called group vertical handover (GVHO). When all VHO decisions of a large number of users are made at the same time, the system performance may degrade and network congestion may occur. In this paper, we propose two fully decentralized algorithms for network access selection, and that is based on the concept of congestion game to resolve the problem of network congestion in group mobility scenarios. Two learning algorithms, dubbed Sastry Algorithm and Q-Learning Algorithm, are envisioned. Each one of these algorithms helps mobile users in a group to reach the nash equilibrium in a stochastic environment. The nash equilibrium represents a fair and efficient solution according to which each mobile user is connected to a single network and has no intention to change his decision to improve his throughput. This shall help resolve the problem of network congestion caused by GVHO. Simulation results validate the proposed algorithms and show their efficiency in achieving convergence, even at a slower pace. To achieve fast convergence, we also propose a heuristic method inspired from simulated annealing and incorporated in a hybrid learning algorithm to speed up convergence time and maintain efficient solutions. The simulation results also show the adaptability of our hybrid algorithm with decreasing step size-simulated annealing (DSS-SA) for high mobility group scenario.

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Mobility-Prediction-Aware Bandwidth Reservation Scheme for Mobile Networks

Cited by 52 publications

References 37 publications

RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks

A simple real-time handover management in the mobile satellite communication networks

Group vertical handoff management in heterogeneous networks

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