Fuzzy decision-making for selection of mobile base station location

2013 ◽

Vol 427-429 ◽

pp. 2497-2501

Author(s):

Yong Fu Zhao ◽

Jian Bo Yao

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Location Privacy ◽

Base Station ◽

Wireless Sensor ◽

Random Data ◽

Base Station Location ◽

Mobile Base Station ◽

Station Location ◽

Mobile Base

As wide applications of wireless sensor networks, privacy concerns have emerged as the main obstacle to success. When wireless sensor networks are used to battlefield, the privacy about base-sation-locations become a crux issue. If base-sation location will be exposed to adversary, the consequence is inconceivable. Random data collection scheme has a problem that message latencies become larger higher for protecting mobile-base-station-location privacy .In this paper, BDGW (Bidirection Greedy Walk) is proposed to preserve mobile-base-station-location privacy. In BDGW, data are forwarded by greedy walk and stored at pass nodes in the network, the base-sation move in bidirection greedy walk to collect data from the local nodes occasionally, which prevents the attackers from predicting their locations and movements. Compared to random data collection scheme, BDGW has smaller message latencies, while providing satisfactory mobile-base-station-location privacy.

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Mobile-Base-Station Location Privacy Based on Greedy Random Walk in WSN

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.427-429.2502 ◽

2013 ◽

Vol 427-429 ◽

pp. 2502-2507

Author(s):

Nan Nan Zhao ◽

Jian Bo Yao

Keyword(s):

Wireless Sensor Networks ◽

Random Walk ◽

Location Privacy ◽

Base Station ◽

Wireless Sensor ◽

Random Data ◽

Base Station Location ◽

Mobile Base Station ◽

Station Location ◽

Mobile Base

As wide applications of wireless sensor networks, privacy concerns have emerged as the main obstacle to success. When wireless sensor networks are used to battlefield, the privacy about base-station-locations become a crux issue. If base-station location will be exposed to adversary, the consequence is inconceivable. Random data collection scheme has a problem that message latencies become larger higher for protecting mobile-base-station-location privacy. In this paper, GROW (Greedy Random Walk) is proposed to preserve mobile-base-station-location privacy. In GROW, data are forwarded and stored at pass nodes in the network, the base-station move in greedy random-walk to collect data from the local nodes occasionally, which prevents the attackers from predicting their locations and movements. Compared to random data collection scheme, GROW has smaller message latencies, while providing satisfactory mobile-base-station-location privacy.

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A Fuzzy Decision-Making Model for Supplier Selection of Logistics

2012 Third International Conference on Innovations in Bio-Inspired Computing and Applications ◽

10.1109/ibica.2012.12 ◽

2012 ◽

Author(s):

Yu-Jie Wang ◽

Tzeu-Chen Han ◽

Chao-Shun Kao

Keyword(s):

Decision Making ◽

Supplier Selection ◽

Fuzzy Decision Making ◽

Fuzzy Decision ◽

Decision Making Model ◽

Selection Of

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Selection of resilient suppliers in manufacturing industries post-COVID-19: implications for economic and social sustainability in emerging economies

International Journal of Emerging Markets ◽

10.1108/ijoem-09-2021-1393 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Abhijit Majumdar ◽

Jeevaraj S ◽

Mathiyazhagan Kaliyan ◽

Rohit Agrawal

Keyword(s):

Decision Making ◽

Incomplete Information ◽

Emerging Economies ◽

Supplier Selection ◽

Fuzzy Decision Making ◽

Ideal Solution ◽

Fuzzy Decision ◽

Content Type ◽

Intuitionistic Fuzzy ◽

Selection Of

PurposeSelection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.Design/methodology/approachA group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.FindingsA closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.Originality/valueThe presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

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