Analysis of Behavioral Economics in Crowdsensing: A Loss Aversion Cooperation Model

Deng, Li; Qiu, Lugui; Liu, Jiaqi; Chen, Xiao

doi:10.1155/2018/4350183

Cited by 9 publications

(5 citation statements)

References 43 publications

(69 reference statements)

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“…Tey have initiated Specoins, a cryptocurrency intended to cover the costs associated with spectrum transfers. However, the aforementioned reports lack a practical selection mechanism and rarely take into account the possibility of MUs while the SU base station is choosing users [35][36][37]. An approach for assigning cooperative relays in CR networks that makes use of the maximum weight matching (MWM) method is discussed in depth by Cao et al in their paper [38].…”

Section: Related Workmentioning

confidence: 99%

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Balakumar,

Sendrayan

2023

Journal of Electrical and Computer Engineering

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Cognitive radio (CR) is the best way to improve the efficiency of spectrum consumption for wireless multimedia communications. Spectrum sensing, which allows legitimate secondary users (SU) to find vacant bands in the spectrum, plays a vital role in CR networks. When cooperative sensing is used in CR networks, spectrum availability must be taken into account. In many ways, the shared cooperative spectrum sensing (CSS) data among SU. The presence of a malicious user (MU) in the system and sending false sensing data can degrade the performance of cooperative CR. The sharp rise in mobile data traffic causes congestion in the licensed band for the transmission of signals. Handling this security issue in real time, on top of spectrum sharing, is a challenge in such networks. In order to manage the spectrum and identify MU, blockchain-based CSS is developed in this article. To gauge the efficiency of the proposed topology, performance metrics like sensitivity, node selection, throughput measurement, and energy efficiency are used. This work suggests a unique, easier-to-use CSS method with MU suppression that outperforms the current one. According to simulation studies, the suggested topology can increase the likelihood of MU detection by roughly 15% when 40% of system users are malicious.

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Section: Related Workmentioning

confidence: 99%

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Balakumar,

Sendrayan

2023

Journal of Electrical and Computer Engineering

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“…Loss aversion in behavioral economics [33] means that people are more averse to lose than gain. Behavioral economics has been widely used in the computer field [34][35][36]. In mobile crowdsourcing [34], loss aversion is used to redefine the utility function of nodes.…”

Section: Incentive Mechanism Of Vanetsmentioning

confidence: 99%

“…Behavioral economics has been widely used in the computer field [34][35][36]. In mobile crowdsourcing [34], loss aversion is used to redefine the utility function of nodes. Reference [35] used reciprocal altruism in behavioral economics to promote message delivery in the Internet of Vehicles.…”

Section: Incentive Mechanism Of Vanetsmentioning

confidence: 99%

Cooperation Promotion from the Perspective of Behavioral Economics: An Incentive Mechanism Based on Loss Aversion in Vehicular Ad-Hoc Networks

Liu

Huang

et al. 2021

Electronics

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As a special mobile ad-hoc network, Vehicular Ad-hoc Networks (VANETs) have the characteristics of high-speed movement, frequent topology changes, multi-hop routing, a lack of energy, storage space limitations, and the possible selfishness of the nodes. These characteristics bring challenges to the design of the incentive mechanism in VANETs. In the current research on the incentive mechanism of VANETs, the mainstream is the reward-based incentive mechanism. Most of these mechanisms are designed based on the expected utility theory of traditional economics and assume that the positive and negative effects produced by an equal amount of gain and loss are equal in absolute value. However, the theory of loss aversion points out that the above effects are not equal. Moreover, this will lead to a deviation between the final decision-making behavior of nodes and the actual optimal situation. Therefore, this paper proposed a Loss-Aversion-based Incentive Mechanism (LAIM) to promote the comprehensive perception and sharing of information in the VANETs. This paper designs the incentive threshold and the threshold factor to motivate vehicle nodes to cooperate. Furthermore, based on the number of messages that the nodes face, the utility function of nodes is redesigned to correct the assumption that a gain and a loss of an equal amount could offset each other in traditional economics. The simulation results show that compared with the traditional incentive mechanism, the LAIM can increase the average utility of nodes by more than 34.35%, which promotes the cooperation of nodes.

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“…Selecting the Operator. Selecting operators is a key factor in the reduction in population diversity, which reflects the evolutionary direction of the survival of the fittest and determines the search performance of the algorithm [33]. Roulette strategy determines the selection probability according to the fitness of an individual.…”

Section: Adaptive Genetic Algorithmmentioning

confidence: 99%

Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

Cheng

Zheng

Wang

et al. 2019

Wireless Communications and Mobile Computing

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Due to the problem of attribute redundancy in meteorological data from the Industrial Internet of Things (IIoT) and the slow efficiency of existing attribute reduction algorithms, attribute reduction based on a genetic algorithm for the coevolution of meteorological data was proposed. The evolutionary population was divided into two subpopulations: one subpopulation used elite individuals to assist crossover operations to increase the convergence speed of the algorithm, and the other subpopulation balanced the population diversity in the evolutionary process by introducing a random population; these two subpopulations completed the evolutionary operations together. With the TSDPSO-AR algorithm and ARAGA algorithm, the attribute reduction operation for precipitation in meteorological data was performed. The results showed that the proposed algorithm maintained the diversity of the population during evolution, improved the reduction performance, and simplified the information system.

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Analysis of Behavioral Economics in Crowdsensing: A Loss Aversion Cooperation Model

Cited by 9 publications

References 43 publications

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Enhance the Probability of Detection of Cooperative Spectrum Sensing in Cognitive Radio Networks Using Blockchain Technology

Cooperation Promotion from the Perspective of Behavioral Economics: An Incentive Mechanism Based on Loss Aversion in Vehicular Ad-Hoc Networks

Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

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