Network Selection Algorithm for Heterogeneous Wireless Environment

Bakmaz, Bojan; Bojković, Zoran; Bakmaz, Miodrag

doi:10.1109/pimrc.2007.4394315

Cited by 39 publications

(26 citation statements)

References 7 publications

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“…The entropy method (Bakmaz et al, 2007) is used to generate the subjective weights for multiple attributes. The weights are determined based on attribute entropy.…”

Section: Subjective Weights Estimation By Entropy Methodsmentioning

confidence: 99%

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Context aware spectrum handoff scheme in cognitive radio vehicular networks

Kumar¹,

Prakash²,

Tripathi³

2017

IJAHUC

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In future cognitive radio (CR) vehicular networks deployment, multiple radio access networks may coexist in overlapping areas. These networks may have with largely different characteristics in terms of multiple attributes. Hence, it becomes difficult for CR vehicular node to select preferred network for spectrum handoff decision. This can be done by a context aware spectrum handoff that takes multiple attributes into account for spectrum handoff decision for preferred network selection. This paper proposes a context aware spectrum handoff scheme with multiple attributes decision-making (MADM) methods for preferred network selection in CR vehicular networks. The MADM methods used are simple additive weighting and grey relational analysis. The paper also proposes a cost-based spectrum handoff scheme with MADM which outperforms other MADM methods. The spectrum handoff with MADM provides wider and optimum choice with quality of service. Numerical results show that the proposed scheme is effective for spectrum handoff decision for preferred network selection.

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“…The entropy method (Bakmaz et al, 2007) is used to generate the subjective weights for multiple attributes. The weights are determined based on attribute entropy.…”

Section: Subjective Weights Estimation By Entropy Methodsmentioning

confidence: 99%

“…Martinez-Morales et al (2010) has presented different MADM methods for vertical handoff in fourth generation networks for voice and data connections. Bakmaz et al (2007) uses TOPSIS method for network selection and entropy method for weights estimation with multiple attributes.…”

Section: Related Workmentioning

confidence: 99%

Context aware spectrum handoff scheme in cognitive radio vehicular networks

Kumar¹,

Prakash²,

Tripathi³

2017

IJAHUC

View full text Add to dashboard Cite

show abstract

“…As well as the emulator of the available networks and their characteristics (e.g. throughput, bit error rate, delay) and user preferences that can prohibit the selection of some access networks and express their perceived QoS by assigning a suitable set of weights obtained by means of some procedures as the Analytic Hierarchy Process (AHP) [7] or the entropy method [19] (see figure 3). …”

Section: Performance Evaluationmentioning

confidence: 99%

Seamless Mobility in Heterogeneous Wireless Networks

Zarai¹,

Smaoui²,

Bonnin³

et al. 2010

IJNGN

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“…This fact make TOPSIS suitable for limited computation devices like smartphones. Recent examples span a implementation range of this algorithm in mobile environment from wireless network selection [5].…”

Section: Introductionmentioning

confidence: 99%

The Development of Mobile Culinary Recommendation System Based on Group Decision Support System

Dewi

Ananta

Fanani

et al. 2018

Int. J. Interact. Mob. Technol.

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Abstract-Mobile based culinary recommendation system has received significant attention in recent mobile application research . Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) has regained popularity in supporting multi-criteria decision making due to this method allowing inclusion of many factors and criteria into the decision making process. Previous works on mobile based scenario culinary recommendation system reveal that TOPSIS stand out from other recommendation approaches like AHP and Fuzzy by providing a lightweight computation algorithm that have promising performance in time complexity. However, computing a culinary recommendation using TOPSIS has own limitations especially in the menu judgment processes due to the alternatives priority only include personal preferences for recommendation. In such a culinary recommendation system scenario, users more likely search culinary menus in group instead of alone. This research aims to develop a culinary recommendation system based on group decision support system (GDSS) using TOPSIS that possible to calculate a recommendation by using group preferences instead of personal preferences. The experimental results show that the overall functional of proposed GDSS gives better recommendation result. GDSS using TOPSIS have 100% rank consistency for 6 group of users with 5 combination of menus. The accuracy testing shows that 83,33 % recommendation of GDSS TOPSIS are match with real user preferences. Furthermore, it can be run well in various type of Android smartphone.

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Network Selection Algorithm for Heterogeneous Wireless Environment

Cited by 39 publications

References 7 publications

Context aware spectrum handoff scheme in cognitive radio vehicular networks

Context aware spectrum handoff scheme in cognitive radio vehicular networks

Seamless Mobility in Heterogeneous Wireless Networks

The Development of Mobile Culinary Recommendation System Based on Group Decision Support System

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