A Novel Genetic Algorithm Approach to Mobility Prediction in Wireless Networks

Mala, C.; Loganathan, M.P.; Gopalan, N. P.; Sivaselvan, B.

doi:10.1007/978-3-642-03547-0_6

Cited by 6 publications

(5 citation statements)

References 5 publications

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“…Finally, to compare the proposed CRP model with some existing works , Figure shows that the proposed model can improve P d‐isho (the dropping probability of inter‐sector handoff calls) by 17% for low‐traffic distribution and 20% for high‐traffic distribution as the speed of MTs equals 20 km/h. The improvement in P d‐isho is gradually reduced as the speed of MTs is increased.…”

Section: Numerical Simulation and Discussionmentioning

confidence: 99%

“…In the aspect of channel reservation, to more effectively utilize reserved channels, Mala et al . proposed a novel genetic algorithm for a sectored network, where a sector is split into high‐handoff and low‐handoff regions. In a three‐sector mobile network, Park and Chung proposed a dynamic resource reservation scheme based on a differentiated handoff estimation model.…”

Section: Introductionmentioning

confidence: 99%

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A channel reservation and preemption model using overlapping regions in sector‐based cellular networks

Sheu

Lin

Hwang

2013

Wireless Communications

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This paper presents a channel reservation and preemption (CRP) model using overlapping regions in a cellular network with multiple sectors. To fully exploit and reuse the frequencies, directional antennas are installed on base stations (BSs) to divide the coverage into a number of equal-sized sectors. When traffic is unevenly distributed across the sectors in a BS, channel utilization in every sector may become very different; low-traffic sectors may be underutilized while high-traffic sectors may be overutilized. A CRP scheme is thus proposed to more efficiently utilize free channels among sectors. CRP aims at reducing the dropping probabilities of handoff calls. Specifically, when free channels in a sector are not available, a handoff call, instead of being dropped, is allowed to preempt an ongoing call residing in the overlapping region of two adjacent sectors or two neighbor cells. Under CRP, the preempted ongoing call will not be disconnected, because it can switch over its service to the BS of a neighbor cell or to another directional antenna of an adjacent sector. For the purpose of evaluation, we build an analytical model for the proposed CRP using six-tuple Markov chains. Analytical results show that the proposed CRP can significantly reduce the dropping probabilities of inter-sector handoff calls, particularly when traffic between two sectors is not evenly distributed.

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Section: Numerical Simulation and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A channel reservation and preemption model using overlapping regions in sector‐based cellular networks

Sheu

Lin

Hwang

2013

Wireless Communications

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“…Routing, resources and services may be provided ahead of time by predicting the future location of a mobile user. Some of the research which deals with the topic at hand can be found in [1,3,[9][10][11][12][13][14][15]. The existing approaches for solving the problem of mobility prediction are discussed below.…”

Section: Link Expiration Time [1]mentioning

confidence: 99%

Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm

et al. 2015

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A mobile ad hoc network is a collection of wireless mobile nodes creating a network without using any existing infrastructure. Much research has been carried out to find out an optimal routing protocol for the successful transmission of data in this network. The main hindrance is the mobility of the network. If the mobility pattern of the network can be predicted, it will help in improving the QoS of the network. This paper discusses a novel approach to mobility prediction using movement history and existing concepts of genetic algorithms, to improve the MANET routing algorithms. The proposed lightweight genetic algorithm performs outlier removal on the basis of heuristics and parent selection using the weighted roulette wheel algorithm. After performing the genetic operations a node to node adjacency matrix is obtained from which the predicted direction of each node is calculated using force directed graphs and vector calculations. The technique proposes a new approach to mobility prediction which does not depend on probabilistic methods and which is completely based on genetic algorithms.

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“…When the user enters high handover regions, the target sector will be determined according to moving direction, so that target cell is also be determined. To solve the problem of poor accuracy when users move towards the corner of hexagonal cells in the sectorized method of [21], the authors of [81] propose an improved scheme based on genetic algorithm. A 2-tier cell structure is applied and each sector is divided into two regions: high handover region and low handover region.…”

Section: Hybrid Approachesmentioning

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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A Novel Genetic Algorithm Approach to Mobility Prediction in Wireless Networks

Cited by 6 publications

References 5 publications

A channel reservation and preemption model using overlapping regions in sector‐based cellular networks

A channel reservation and preemption model using overlapping regions in sector‐based cellular networks

Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm

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

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