کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383588 660827 2013 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Wright–Fisher multi-strategy trust evolution model with white noise for Internetware
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Wright–Fisher multi-strategy trust evolution model with white noise for Internetware
چکیده انگلیسی


• A trust measurement model based on QoS is established.
• Considering timeliness of history behavior data and aggregation degree of entity, entity’s utility value is calculated based on fuzzy theory.
• A Wright–Fisher multi-strategy trust evolution model with white noise for Internetware is proposed to predict the evolutionary trend of an Internetware.
• An incentive mechanism based on evolutionary game theory is proposed to solve the free-riding problem.

A trust evolution model plays an important role in ensuring and predicting the behaviors of entities in Internetware system. Most of the current trust evolution models almost adopt expertise or average weight method to calculate entities’ trust incomes, and focus on two strategies (‘full trust’, ‘full distrust’) to analyze trust behaviors. In addition, the researches on dynamics evolution models fail to consider the factor of noise, and cannot effectively prevent free-riding phenomenon. In this paper, a trust measurement based on Quality of Service (QoS) and fuzzy theory by considering timeliness of history data is proposed to improve the accuracy of trust measurement results. Furthermore, a trust evolution model based on Wright–Fisher and the evolutionary game theory is proposed. This model considers multi-strategy and noise problems to improve the accuracy of prediction and adaptability of model in complex networks. Meanwhile, in order to solve the free-riding problem, and improve the trust degree of a system, an incentive mechanism is established based on evolutionary game theory to inspire entities to select trust strategies. The simulation results show that this model has good adaptability and accuracy. In addition, this model can effectively improve network efficiency, and make trust income reach an optimal value, so as to improve trust degree of a system.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 40, Issue 18, 15 December 2013, Pages 7367–7380
نویسندگان
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