0% Complete
فارسی
Home
/
چهاردهمین کنفرانس بین المللی فناوری اطلاعات و دانش
Combinatorial Auction Based on Social Choice in the Internet of Things
Authors :
Maede Esmaeili
1
Faria Nassiri-Mofakham
2
Fatemeh Hassanvand
3
1- University of Isfahan
2- University of Isfahan
3- دانشگاه اصفهان
Keywords :
Internet of Things،Combinatorial Auction،Winner Determination،Social Choice
Abstract :
The Internet of Things (IoT) enables smart Things to communicate via the Internet. Things are growing in number, and their need for multiple resources in a complementary manner engenders serious problems in resource allocation. Combinatorial Auctions (CA) are the optimal market mechanism for allocating such indivisible bundles. Since the abundance of bundles in the IoT market makes it impossible to bid on all bundles, Things express their preferences on some (and not all) bundles to make the winner determination amenable. We address the winner determination problem by proposing an allocation mechanism based on social choice methods, which operates on the number of requested resources, the number of bundles, the offered price, and the preferred weight of each bundle. These methods include Borda, Copeland, Average without Misery, Least Misery, and Hare. Finally, we demonstrate the evaluation of these methods in terms of execution time and envy-freeness among the Things.
Papers List
List of archived papers
تخلیهی باری وظایف اینترنت اشیاء بر روی مه محاسباتی با استفاده از الگوریتم حشره آبسوار
عفت تقی زاده بیلندی - آرش دلداری - علیرضا صالحان
بهبود معاملات الگوریتمی سهام مبتنی بر رویکرد یادگیری تقویتی
مها العطوان - جعفر پورامینی
Optimal control of robotic hand for rehabilitation using fractional order systems and EEG signal processing
Mehran Safari Dehnavi - Vahid Safari Dehnavi - Masoud Shafiee
An Efficient Link Prediction Method using Community Structures
Dr Hadi Shakibian - Setareh Mokhtari
Towards Provable Privacy Protection in IoT-Health Applications
Samane Sobuti - دکتر سیاوش خرسندی
Enhancing Mutation Testing through Grammar Fuzzing and Parse Tree-Driven Mutation Generation
Mohamad Khorsandi - Alireza Dastmalchi Saei - Mohammadreza Sharbaf
Mode Selection and Resource Allocation in D2D-Enabled MC-NOMA using Matching Theory
Alireza Gholamrezaee - Hamid Farrokhi - Javad Zeraatkar Moghaddam
Enhancing kNN-Based Intrusion Detection with Differential Evolution with Auto-Enhanced Population Diversity
Zohre Karimi - Zeinab Torabi
Emotion Recognition Using Effective Connectivity and Fully Complex-Valued Magnetic Graph Convolution Neural Network
Armin Pishehvar - Eghbal Mansoori - Abbas Mehrbaniyan - Reza Tahmasebi
An OWA-Powered Dynamic Customer Churn Modeling in the banking industry Based on Customer Behavioral Vectors
Masoud Alizadeh - Mohammad Soleymannejad - Behzad Moshiri
more
Samin Hamayesh - Version 44.5.0