Utility function-based TOPSIS for network interface selection in Heterogeneous Wireless Networks

Senouci, Mohamed Abdelkrim; Hoceini, Saïd; Mellouk, Abdelhamid

doi:10.1109/icc.2016.7511563

Cited by 36 publications

(16 citation statements)

References 19 publications

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“…Grey relational analysis It can avoid wrong weight distribution caused by conflicting opinions of experts, but determining the identification coefficient is difficult. [11][12][13] Entropy weight method It can significantly decrease the influences of experts' subjectivity on quantification of weights, but reasonably explaining the quantification results of weights is difficult. [7,14] AHP AHP can be used in the quantitative analysis of qualitative indexes and achieves clear logics.…”

Section: Referencesmentioning

confidence: 99%

Network Access Selection Algorithm Based on Balanced Profits between Users and Network

Chen

Juanping

Yuan

et al. 2019

Wireless Communications and Mobile Computing

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A network access selection algorithm based on the intuitionistic fuzzy analytic hierarchy process (AHP) and bilateral profit drive is proposed in this study for addressing problems regarding user–network bilateral profits. User preference, business demands, and network parameter changes are comprehensively considered in the algorithm. First, the initial weights centered at users are gained by intuitionistic fuzzy AHP. Second, the network participates in network access selection as a subject with competitive consciousness, and the entire selection process is transformed into a multiobjective optimization problem by the construction of a competitive model, thereby obtaining dynamic competitive weights. Third, the initial weights centered at users and the dynamic competitive weights are combined to obtain comprehensive weights. In this way, the dynamic adjustment of comprehensive weights is realized. Finally, candidate networks are ordered according to a comprehensive performance evaluation, and the optimal one is selected. The proposed algorithm is validated by simulation results to be valid in reducing the blocking rate of networks and optimizing network resource allocation. Therefore, it not only protects user–network bilateral profits but also maximizes comprehensive profits.

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Section: Referencesmentioning

confidence: 99%

Network Access Selection Algorithm Based on Balanced Profits between Users and Network

Chen

Juanping

Yuan

et al. 2019

Wireless Communications and Mobile Computing

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“…In [25], Senouci et al propose a network selection strategy based on utility function and TOPSIS. The authors consider the problem of ranking abnormality generated by TOPSIS when a low-ranking network is disconnected and the order of higher ranking networks changes.…”

Section: Related Workmentioning

confidence: 99%

Network selection algorithm for heterogeneous wireless networks based on service characteristics and user preferences

Liang

Huang

2018

J Wireless Com Network

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Next generation heterogeneous wireless networks (HWNs) will integrate various wireless access technologies, such as cellular networks, wireless local area network (WLAN), and Worldwide Interoperability for Microwave Access (WiMAX), in order to support quality of service (QoS) requirements of various services. To connect mobile users to the best wireless network continuously, network selection has become a hotspot for research in HWNs. This paper designs a network selection algorithm based on service characteristics and user preferences. First, utility functions are used to calculate the utility value of each network attribute for different services. Next, the entropy method and the fuzzy-analytic hierarchy process (FAHP) are used to calculate the objective weight and subjective weight of network attributes respectively, with FAHP specifically being used to calculate the user preference values of services for candidate networks. Finally, simple additive weighting (SAW), multiplicative exponent weighting (MEW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used according to network attribute utility values and weights to calculate the score of each candidate network. These scores are converted into a comprehensive score for the candidate network based on such user preferences, thus obtaining the ranking of candidate networks. Simulation results show that the proposed algorithm can allow users to choose the most suitable network to access according to different service characteristics while reducing the number of network handovers.

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“…They affirm that both monotonic and non-monotonic utilities can be taken into consideration, and are therefore better suited for achieving this type of optimization objectives. In [42] researchers proposed a user-centric RAN selection strategy based on maximizing consumer surplus, subject to meeting user-defined constraints in terms of transfer completion time. An exploration of a number of possible utility functions based on different user's attitudes to risk is presented.…”

Section: Utility Functionsmentioning

confidence: 99%

Network Selection in Wireless Heterogeneous Networks: a Survey

Bendaoud¹,

Abdennebi²,

Didi³

2018

JTIT

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Heterogeneous wireless networks is a term referring to networks combining diﬀerent radio access technologies with the aim of establishing the best connection possible. In this case, users with multi-mode terminals can connect via diﬀerent wireless technologies, such as 802.16, 802.11, UMTS, HSPA and LTE, all at the same time. The problem consists in the selection of the most suitable from all radio access technologies available. The decision process is called network selection, and depends on several parameters, such as quality of service, mobility, cost, energy, battery life, etc. Several methods and approaches have been proposed in this context, with their objective being to oﬀer the best QoS to the users, and/or to maximize re-usability of the networks. This paper represents a survey of the network selection methods used. Multiple attribute-dependent decision-making methods are presented. Furthermore, the game theory concept is illustrated, the use of the fuzzy logic is presented, and the utility functions deﬁning the network selection process are discussed.

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Utility function-based TOPSIS for network interface selection in Heterogeneous Wireless Networks

Cited by 36 publications

References 19 publications

Network Access Selection Algorithm Based on Balanced Profits between Users and Network

Network Access Selection Algorithm Based on Balanced Profits between Users and Network

Network selection algorithm for heterogeneous wireless networks based on service characteristics and user preferences

Network Selection in Wireless Heterogeneous Networks: a Survey

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