A smart vertical handoff decision algorithm based on queuing theory

Sun, Yong; Liu, Chao; Yang, Peng; Wen, Xiangming

doi:10.1109/icact.2014.6779152

Cited by 6 publications

(2 citation statements)

References 14 publications

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“…The hysteresis-based and dwelling time-based are evaluated the vertical handover approach [2] but these method rely on sampling and averaging RSS points, which introduces increased handover delay. Analytic Hierarchy Process (AHP) was proposed by [3][4]; the network with the highest performance score is selected on target network but this method ignores the wireless environment. Finally, Multiple Attribute Decision Making (MADM) approach is the combination of methods and uses the many parameters at the same time (e.g.…”

Section: Introductionmentioning

confidence: 99%

Vertical Handover Decision Management on the Basis of Several Criteria for LVQNN With Ubiquitous Wireless Networks

Kunarak¹

2017

GEOMATE

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Vertical handover decision management is an essential to keep the seamless ubiquitous heterogeneous wireless networks since each access network has different operations in the next generation. In this paper, WCDMA, LTE and WLAN are cooperated in the architecture of mobile IP regional registration (MIP-RR). We propose the Learning Vector Quantization Neural Networks (LVQNNs) approach in order to maintain uninterrupted communication that depends on received signal strength indicator, data rate requirement, monetary cost of service and mobile terminal device speed metrics are considered as multi-criteria to initial handover. Furthermore, the multi-criteria are dynamic to influence for real-time and non-real time services in different networks and the users select the optimal target network which is the highest handover factor score in order to balance against the network condition and user preference. To ensure the Always Best Connected (ABC) demands, the simulation results illustrate that our proposed algorithm provided outperform the performance in term of unnecessary handover, the call dropping probability, data packet delay and network utilization compared with conventional method as fuzzy logic and neural network based machine learning.

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Section: Introductionmentioning

confidence: 99%

Vertical Handover Decision Management on the Basis of Several Criteria for LVQNN With Ubiquitous Wireless Networks

Kunarak¹

2017

GEOMATE

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“…Existing network selection algorithms main ly consist of game theory [5][6], genetic algorith m [7], mu lti-attribute decision making (MADM) [8], fuzzy logic [9], the utility function [10] and other methods and models [11], In [6], the author proposed a cost-effective network selection algorithm aimed at to maximize user's profit, explained the relationship between operators and users with non -cooperative game in the abstract, chose the best network by seeking a Nash equilibriu m. The authors in [9] adopted the received signal strength, available bandwidth, price and user's preference as network selection index, used fuzzy logic to calculate candidate network performance and execute the best network selection. The network selecting algorithm of the authors in [12] comb ined with AHP (analytic hierarchy process) and SAW (simple add weight) to perform network selection, namely used AHP computing network selection decision attribute weights, reused SAW sorting the candidate network, and then selected the best network, the authors in [13] through calculating the network performance parameters and traffic blocking probability, selected and assessed network with user's satisfaction dynamically. The authors in [14][15] based on AHP and TOPSIS (technique for order preference by similarity to an ideal solution), used AHP computing the relative importance of network selection decision attribute, reused TOPSIS executing the best network selection.…”

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confidence: 99%

Access Network Selection Algorithm in Heterogeneous Multi-cognitive Wireless Networks Coexistence Environment

Tang¹,

Deng²,

Wu³

et al. 2015

Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science

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Considering the three factors of user's preference, business requirement and network performance, this paper presented an integrated weighting network access selection algorithm under heterogeneous multi-cognitive wireless network coexistence environment. The algorithm based on AHP-TOPS IS algorithm which defined positive and negative ideal values, and used the distance value between the candidate networks to avoid the ranking abnormality problem when executing the TOPS IS algorithm. The algorithm introduced entropy as objective weight for decision attributes, to avoid the subjective and arbitrary problem when performing the AHP algorithm. And the algorithm used the relative relationship of the decision attributes, business types, and the network performance to define the subjective weight, and then combine the objective weight with the subjective weight to form an integrated weight. Adopting the algorithm to execute optimal access network selection can balance the network loads, and use network resources reasonably. Simulation results showed that the proposed integrated weighting network access selection algorithm can select candidate network correctly depending on the different business needs in the heterogeneous multi-cognitive wireless network coexistence environment, and can meet the service quality while achieving the entire network load balancing, and improving resource utilization.

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A Vertical Handoff Decision Algorithm Based on the Movement-Aware of Mobile Nodes

Xiaona

Liao

2014

2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

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A smart vertical handoff decision algorithm based on queuing theory

Cited by 6 publications

References 14 publications

Vertical Handover Decision Management on the Basis of Several Criteria for LVQNN With Ubiquitous Wireless Networks

Vertical Handover Decision Management on the Basis of Several Criteria for LVQNN With Ubiquitous Wireless Networks

Access Network Selection Algorithm in Heterogeneous Multi-cognitive Wireless Networks Coexistence Environment

A Vertical Handoff Decision Algorithm Based on the Movement-Aware of Mobile Nodes

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