Multi-class Bandwidth Reservation Scheme Based on Mobility Prediction for Handoff in Multimedia Wireless/Mobile Cellular Networks

Al-Sanabani, Maher; Subramaniam, Shamala; Othman, Мohamed; Zukarnain, Zuriati Ahmad

doi:10.1007/s11277-007-9414-9

Cited by 7 publications

(6 citation statements)

References 23 publications

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“…Through next-cell prediction, the target cell can be determined, and an adaptive reservation can be derived. It reserves the required bandwidth only in those cells where the users are expected to visit in the near future [99], [100]. Also, BSs compute the amount of bandwidth need to be reserved based on cell estimation to reduce unnecessary bandwidth reservation [29].…”

Section: ) Resource Allocationmentioning

confidence: 99%

A Survey on Next-Cell Prediction in Cellular Networks: Schemes and Applications

2020

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Mobility prediction is a powerful tool for network operators to optimize network performance. From cell level, if network operators know the cells to which the users will be connected in advance, wireless resources can be pre-allocated to improve network performance and better user experience can be provided in location-based services. Many next-cell prediction models and methods have been suggested and implemented. This paper is devoted to next-cell prediction (cell level mobility prediction) in cellular networks, and provides a thorough survey of the prediction schemes and applications. Particularly, a two-level classification methodology was proposed and applied. We first divided the prediction schemes into three categories based on the mobility data used for prediction, i.e. Current Movement State based Approaches (CMSA), Historical Movement Pattern based Approaches (HMPA), and HybriD Approaches (HDA). Prediction schemes in each category were further classified based on the used prediction methods. The typical application scenarios were introduced as well, including handover management, resource allocation, etc. Finally, current challenges and potential trends in the near future were further discussed.

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Section: ) Resource Allocationmentioning

confidence: 99%

A Survey on Next-Cell Prediction in Cellular Networks: Schemes and Applications

2020

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“…All the traffic are queued and served by the single server with rate (l QS ) based on the priority level of each class. Generally, C B packets are given the highest priority, then C N and C R are served [18][19][20]. A problem of priority scheduling (of different traffic classes) of single band is that one type of packet may be served continuously while others may suffer starvation.…”

Section: Scheduling In Single Band Systemsmentioning

confidence: 99%

Management and Analysis of Multi Class Traffic in Single and Multi-band Systems

Narman

Hossain

Atiquzzaman

2015

Wireless Pers Commun

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A recent trend in Internet usage has seen large amounts of multimedia data due to increasingly large numbers of mobile users. To facilitate higher bandwidth, modern mobile routers are capable of supporting simultaneous multi-band, leading to less interference, higher capacity and better reliability. However, there exists neither previous work that attempts to maximize utilization of available bandwidth in order to increase performance of multi-band mobile routers through the sharing of traffic classes among different frequency bands of the multi-band mobile router by scheduling, nor that shows multi-band routers are better than single band routers in realistic scenarios. In this paper, we have proposed a novel scheduling algorithm for multi-band mobile routers which transmits different classes of traffic through different frequency bands to achieve improved performance. We have developed an analytical model to perform queuing analysis of the proposed scheduling algorithm for multi-band mobile routers and derived various performance metrics, validated by extensive simulations. Our results show that the proposed scheduling model can improve performance by ensuring maximum possible utilization through sharing of capacities among the bands in multi-band systems. We show our results by comparing proposed multi-band scheduling model with single and current multi-band scheduling models. In addition, we compare single and multi-band mobile routers. It is evident from our results that multi-band systems are not always better than single band systems although multi-band systems are expected to have better performance. Based on the results, we have listed recommendations for selecting single or multi-band systems and allocation policies according to traffic conditions, and their priorities. Our proposed scheduling algorithms and related analysis will help network engineers build next generation mobile routers with higher throughput and utilization, ensuring less packet loss of different classes of traffic.

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“…(3) Dropping probability of HCs from sectors to the SG Summing up the stationary probabilities of Markovian states where s D .C sgb / 0 , we have the dropping probability of HCs from sectors to the SG (i.e., DP sesg /, as shown in Equation (14).…”

Section: Blocking and Dropping Probabilitiesmentioning

confidence: 99%

Analytical models for call blocking and dropping in sectorized cellular networks with fractional frequency reuse

Sheu

Lin

Chou

2014

Wireless Communications

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In this paper, we construct mathematical models to analyze the probabilities of new call blocking and handoff call (HC) dropping for a sectorized cellular network with fractional frequency reuse (FFR). Because a sectorized FFR network (SFN) consists of two areas, the super group (SG) and the regular group (or sectors), three different types of HCs may happen when a mobile station (MS) moves from the SG to a sector, from a sector to the SG, or from one sector to another sector. To characterize three types of HCs, we first derive the area transition probability, which is defined as the reciprocal of MS's average residence time in an area (i.e., sector or SG). Moreover, we construct the model of Markov chains and derive the state transition rates. Then on the basis of the stationary probabilities of Markovian states, we derive the three types of blocking probabilities of new calls and two types of dropping probabilities of HCs. Finally, we conduct extensive numerical simulations. From the results of numerical simulations, we reveal two important rules for choosing the optimal radius of the SG, with which the system blocking and dropping probability can be effectively minimized. Copyright © 2014 John Wiley & Sons, Ltd.

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Multi-class Bandwidth Reservation Scheme Based on Mobility Prediction for Handoff in Multimedia Wireless/Mobile Cellular Networks

Cited by 7 publications

References 23 publications

A Survey on Next-Cell Prediction in Cellular Networks: Schemes and Applications

A Survey on Next-Cell Prediction in Cellular Networks: Schemes and Applications

Management and Analysis of Multi Class Traffic in Single and Multi-band Systems

Analytical models for call blocking and dropping in sectorized cellular networks with fractional frequency reuse

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