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Jill Gabrielle Klein - One of the best experts on this subject based on the ideXlab platform.
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Ethical decision making and research deception in the behavioral sciences: An application of social Contract Theory
Ethics and Behavior, 2011Co-Authors: Allan J. Kimmel, N. Craig Smith, Jill Gabrielle KleinAbstract:Despite significant ethical advances in recent years, including professional developments in ethical review and codification, research deception continues to be a pervasive practice and contentious focus of debate in the behavioral sciences. Given the disciplines’ generally-stated ethical standards regarding the use of deceptive procedures, researchers have little practical guidance as to their ethical acceptability in specific research contexts. We use social Contract Theory to identify the conditions under which deception may or may not be morally permissible, and formulate practical recommendations to guide researchers on the ethical employment of deception in behavioral science research.
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social Contract Theory and the ethics of deception in consumer research
Journal of Consumer Psychology, 2009Co-Authors: Craig N Smith, Allan J. Kimmel, Jill Gabrielle KleinAbstract:Abstract Deception of research participants is a pervasive ethical issue in experimental consumer research. Content analyses find as many as three-fourths of published human participant studies in our field involved some form of deception, almost all of which employed experimental methodologies. However, researchers have little guidance on the acceptability of the use of deception, notwithstanding the codes of root disciplines. We turn to theories of moral philosophy and use social Contract Theory specifically to identify conditions under which deception may be justified as morally permissible. Seven guiding principles for research practice are formulated and their implications for consumer researchers are identified, together with practical recommendations for decision making on studies involving deception.
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Social Contract Theory and the Ethics of Deception in Consumer Research
Journal of Consumer Psychology, 2009Co-Authors: N. Craig Smith, Allan J. Kimmel, Jill Gabrielle KleinAbstract:Deception of research participants is a pervasive ethical issue in experimental consumer research. Content analyses find as many as three-quarters of published human participant studies in our field involved some form of deception and almost all of these deceptive studies employed experimental methodologies. However, researchers have little guidance on the acceptability of this use of deception, notwithstanding the codes of root disciplines. We turn to the theories of moral philosophy and use social Contract Theory to identify conditions under which deception may be justified as morally permissible. Seven principles to guide research practice are formulated and their implications for consumer researchers and others are identified, together with practical recommendations for decision making on deception studies.
Zhu Han - One of the best experts on this subject based on the ideXlab platform.
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incentive mechanism design for two layer wireless edge caching networks using Contract Theory
IEEE Transactions on Services Computing, 2021Co-Authors: Tingting Liu, Feng Shu, Haibing Guan, Zhu HanAbstract:Wireless caching technologies have been proposed to relieve the transmission pressures, especially, the transmission redundancy on back-haul channels. In this paper, we consider a two-layer caching network, consisting of traditional macro-cell base station (MBS) aided back-haul channels and small-cell base stations (SBSs) aided local links. The network service provider (NSP), who is in charge of the two layers, leases its resources of the secondary layer, i.e., coverage of the SBSs, to content providers (CPs) for making extra profits and releasing pressures on the back-haul channels. At the same time, CPs will evaluate whether they are provided with proper incentives to pre-cache their files in the SBSs. Considering different quality of services (QoS) provided by the two layers as well as the economical impact of the traditional layer on the secondary layer, the NSP designs the optimal incentive mechanisms within the framework of Contract Theory for maximizing its own profits. First, we formulate the utility of the NSP and CPs. Then, the minimum transmission requirement, reserve price and limited resources are considered as constraints in designing the optimal Contract. Also, some important properties of these constraints are analyzed to facilitate the optimal Contract determination process. At last, an optimal Contract determination scheme is proposed, based on which the optimal coverage set is determined first, and then the corresponding optimal prices are derived with the aid of equal cost line. Numerical results are provided to demonstrate the effectiveness of the proposed optimal Contract in increasing the NSP's profits and incentivizing CPs to transmit on the secondary layer.
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Contract Theory based incentive design mechanism for opportunistic iot networks
IEEE Internet of Things Journal, 2021Co-Authors: Nitin Gupta, Jagdeep Singh, Sanjay Kumar Dhurandher, Zhu HanAbstract:Industrial Internet of Things and Industry 4.0 enable interconnection among various devices. An opportunistic Internet of Things network is an ad-hoc network that is formed by the nodes (e.g. smart vehicles and mobile phones) by utilizing various short radio range techniques. In this kind of network, information forwarding and dissemination among other smart devices is based upon the opportunistic contact nature mainly due to network dynamics and user mobility. Routing plays an important part in these kinds of networks since there does not exist a pre-established route tyagi2013systematic. Nodes are often selected dynamically based upon many parameters such that messages can be delivered successfully to the destination devices or sinks. However, these intermediate nodes are often selfish because routing these packets costs energy. In case of incomplete cooperation and asymmetric information, message delivery can be severely degraded, which increases the network delay affecting the overall network performance. Therefore, this work proposes an incentive design mechanism based on Contract Theory to reward intermediate nodes appropriately to forward the messages. Contract Theory is used to model the forwarding-forwarder node interaction as a labor market with private information. First, the users are classified into a finite number of types according to their ability of forwarding the message, and the service trading between the forwarding and forwarder nodes is properly modeled. Further, the necessary and sufficient conditions are derived to provide the incentives to the nodes involved in the message forwarding. Extensive simulations show that the proposed mechanism is effective in providing incentives and outperforms other benchmark schemes in terms of delivery probability, average latency, and overhead ratio.
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resource trading for a small cell caching system a Contract Theory based approach
Wireless Communications and Networking Conference, 2017Co-Authors: Tingting Liu, Feng Shu, Zhu HanAbstract:Evidences indicate that wireless video traffic has played an important role in cellular networks. Caching mechanisms which store popular contents into local small-cell base stations (SBSs) in cellular networks are proposed to further reduce transmission delay and release the traffic pressure over backhaul channels. In this paper, we consider a commercialized small-cell caching system consisting of a network service provider (NSP), several video retailers (VRs) and multiple mobile users (MUs). The NSP as a network facility monopoly releases its resources to the VRs in order to maximize its own profits. The distribution of VR's type is known to the NSP, while the actual type of a given VR is not known. We research on such an information asymmetric market within the framework of Contract Theory, formulated as an adverse selection problem. The MUs and SBSs are modeled as two independent Poisson point processes, and the directly downloading probability from the adjacent SBS is derived via stohastic geometry Theory. Based on the probability, we formulate the utility functions of the NSP and the VRs. Then, the optimal Contract problem is constructed. Also, we provide the feasibility of the Contract, and the optimal Contract is proposed when VR's popularity parameter amp;#947; takes different values. Numerical results are provided to show the optimal quality and the optimal price designed for each VR.
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incentive design for collaborative jamming using Contract Theory in physical layer security
International Conference on Communications, 2016Co-Authors: Yanru Zhang, Li Wang, Mei Song, Zhu HanAbstract:Cooperative jamming is a promising technology for improving information secrecy at the physical layer. The increase of secrecy capacity heavily depends on the participation of the jammer and its geographical locations. However, the jammer's geographical location might not be known to others such as the source node due to privacy, and the asymmetric information will lead to inefficiency in jamming. Thus, incentive mechanisms for cooperative jamming are on demand. In this paper, a solution based on Contract Theory is proposed to solve the problem of motivating efficient friendly jamming. First, we classify the diverse potential locations of the jammer into a finite number of types under the framework of Contract Theory. Second, we analyze the feasible conditions which guarantee that a jammer will provide service and select the Contract bundle designed only for its corresponding type. Finally, an optimal Contract is proposed targeting to maximize the source node's utility. Numerical results verify the performances of our proposed scheme.
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On-device Computational Caching-Enabled Augmented Reality for 5G and Beyond: A Contract Theory-Based Incentive Mechanism
IEEE Internet of Things Journal, 2026Co-Authors: Tri Nguyen Dang, Zhu Han, Kitae Kim, Latif U. Khan, S. Ahsan M. Kazmi, Choong Seon HongAbstract:Recently, we have witnessed an increasing demand in augmented reality (AR) based Fifth-Generation (5G) and beyond applications, such as smart gaming, smart navigation, smart military wearable, and smart industries. These AR-based applications require on-demand computational and caching resources with low latency that can be provided via Multi-access Edge Computing (MEC) server. However, due to the massive growth of AR-enabled devices, the MEC server resources might be insufficient. To overcome this challenge, we can utilize the computational and caching resources of user equipment (UE) to serve the other UEs in its close vicinity. Successfully enabling such interaction among devices requires an attractive incentive mechanism. Therefore, we propose a Contract Theory-based incentive mechanism for enabling on-device caching for AR-based applications. In our approach, the MEC offers a reward to the UE for providing its resources (i.e., storage capacity, power, etc.). Furthermore, under the information asymmetry problem, we derive an optimal mechanism via the Contract Theory for enabling on-device caching subject to the individual rationality and incentive-compatible constraints. Finally, we perform numerical evaluations to validate the effectiveness of our proposed scheme.
Oliver Hart - One of the best experts on this subject based on the ideXlab platform.
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making the case for Contract Theory
Social Science Research Network, 2010Co-Authors: Oliver HartAbstract:Economics has changed a great deal in the last thirty years and there is every reason to think that the changes in the next twenty to thirty years will be at least as great. Although Theory may not be as prominent as it once was, it remains essential for understanding the (increasingly) complex world we live in. One cannot analyze the bewildering amount of data now available, or make sensible policy recommendations, without the organizing framework that Theory provides. Contract Theory is a good example of an area where great progress has been made in the last thirty years, and yet where much remains to be done. In this short essay I will discuss some of the major themes of Contract Theory and also issues that are still not well understood.
Dusit Niyato - One of the best experts on this subject based on the ideXlab platform.
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towards small aoi and low latency via operator content platform a Contract Theory based pricing
IEEE Transactions on Communications, 2021Co-Authors: Xuying Zhou, Wei Wang, Naveed Ul Hassan, Chau Yuen, Dusit NiyatoAbstract:Increasing demands of multimedia contents brings a great profit to the content providers, but also a challenge of how to efficiently delivery contents to make users have a good Quality of Experience (QoE). Take the advantage of owning wireless infrastructures, the telco operator is motivated to build a content platform for entering the market of content. In this paper, we consider a content platform belonging to the operator, which can provide periodically-updated contents with small Age of Information (AoI), namely, fresh contents. The content update consumes radio resource resulting in a trade-off between the AoI and the latency. We adopt the Contract Theory to monetize contents considering the above two factors in a realistic asymmetric information scenario. Necessary and sufficient conditions are derived to ensure the feasibility of the Contract. We further propose the optimal update schemes and the corresponding fees, which maximizes the utility of the operator. Simulation reveals that the proposed Contract enables the users, who attach importance to the freshness, to obtain frequently updating contents.
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Combining Contract Theory and Lyapunov Optimization for Content Sharing With Edge Caching and Device-to-Device Communications
IEEE ACM Transactions on Networking, 2020Co-Authors: Alia Asheralieva, Dusit NiyatoAbstract:The paper proposes a novel framework based on the Contract Theory and Lyapunov optimization for content sharing in a wireless content delivery network (CDN) with edge caching and device-to-device (D2D) communications. The network is partitioned into a set of clusters. In a cluster, users can share contents via D2D links in coordination with the cluster head. Upon receiving the content request from any user in its cluster, the cluster head either delivers the content itself or forwards the request to another node, i.e., a base station (BS) or another user in the cluster. The content access at the BS and in each cluster is modeled as a queuing system, where arrivals represent the content requests directed to respective nodes. The objective is to assign content delivery nodes to stabilize all queues while minimizing the time-averaged network cost given incomplete information about content sharing costs of the users and unknown distribution of the network state defined by users' locations and their cached/requested content. The proposed framework allows the users to truthfully reveal their content sharing expenditures, minimize the time-averaged network cost and stabilize the queuing system representing the CDN. Based on this framework, a distributed content access and delivery algorithm where the node assignments are made by every cluster head independently is developed. It is shown that the algorithm converges to the optimal policy with the trade-off in total queue backlog and achieves a superior performance compared with some other D2D content sharing policies.
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incentive mechanism for reliable federated learning a joint optimization approach to combining reputation and Contract Theory
IEEE Internet of Things Journal, 2019Co-Authors: Jiawen Kang, Zehui Xiong, Dusit Niyato, Shengli Xie, Junshan ZhangAbstract:Federated learning is an emerging machine learning technique that enables distributed model training using local datasets from large-scale nodes, e.g., mobile devices, but shares only model updates without uploading the raw training data. This technique provides a promising privacy preservation for mobile devices while simultaneously ensuring high learning performance. The majority of existing work has focused on designing advanced learning algorithms with an aim to achieve better learning performance. However, the challenges, such as incentive mechanisms for participating in training and worker (i.e., mobile devices) selection schemes for reliable federated learning, have not been explored yet. These challenges have hindered the widespread adoption of federated learning. To address the above challenges, in this article, we first introduce reputation as the metric to measure the reliability and trustworthiness of the mobile devices. We then design a reputation-based worker selection scheme for reliable federated learning by using a multiweight subjective logic model. We also leverage the blockchain to achieve secure reputation management for workers with nonrepudiation and tamper-resistance properties in a decentralized manner. Moreover, we propose an effective incentive mechanism combining reputation with Contract Theory to motivate high-reputation mobile devices with high-quality data to participate in model learning. Numerical results clearly indicate that the proposed schemes are efficient for reliable federated learning in terms of significantly improving the learning accuracy.
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incentive design for efficient federated learning in mobile networks a Contract Theory approach
Asia-Pacific Conference on Wearable Computing Systems, 2019Co-Authors: Jiawen Kang, Zehui Xiong, Dusit Niyato, Yingchang Liang, Dong In KimAbstract:To strengthen data privacy and security, federated learning as an emerging machine learning technique is proposed to enable large-scale nodes, e.g., mobile devices, to distributedly train and globally share models without revealing their local data. This technique can not only significantly improve privacy protection for mobile devices, but also ensure good performance of the trained results collectively. Currently, most the existing studies focus on optimizing federated learning algorithms to improve model training performance. However, incentive mechanisms to motivate the mobile devices to join model training have been largely overlooked. The mobile devices suffer from considerable overhead in terms of computation and communication during the federated model training process. Without well-designed incentive, self-interested mobile devices will be unwilling to join federated learning tasks, which hinders the adoption of federated learning. To bridge this gap, in this paper, we adopt the Contract Theory to design an effective incentive mechanism for simulating the mobile devices with high-quality (i.e., high-accuracy) data to participate in federated learning. Numerical results demonstrate that the proposed mechanism is efficient for federated learning with improved learning accuracy.
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toward secure blockchain enabled internet of vehicles optimizing consensus management using reputation and Contract Theory
IEEE Transactions on Vehicular Technology, 2019Co-Authors: Jiawen Kang, Zehui Xiong, Dusit Niyato, Dong In Kim, Jun ZhaoAbstract:In the Internet of Vehicles (IoV), data sharing among vehicles is critical for improving driving safety and enhancing vehicular services. To ensure security and traceability of data sharing, existing studies utilize efficient delegated proof-of-stake consensus scheme as hard security solutions to establish blockchain-enabled IoV (BIoV). However, as the miners are selected from miner candidates by stake-based voting, defending against voting collusion between the candidates and compromised high-stake vehicles becomes challenging. To address the challenge, in this paper, we propose a two-stage soft security enhancement solution: 1) miner selection and 2) block verification. In the first stage, we design a reputation-based voting scheme to ensure secure miner selection. This scheme evaluates candidates’ reputation using both past interactions and recommended opinions from other vehicles. The candidates with high reputation are selected to be active miners and standby miners. In the second stage, to prevent internal collusion among active miners, a newly generated block is further verified and audited by standby miners. To incentivize the participation of the standby miners in block verification, we adopt the Contract Theory to model the interactions between active miners and standby miners, where block verification security and delay are taken into consideration. Numerical results based on a real-world dataset confirm the security and efficiency of our schemes for data sharing in BIoV.
V K Bhargava - One of the best experts on this subject based on the ideXlab platform.
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relay selection for ofdm wireless systems under asymmetric information a Contract Theory based approach
IEEE Transactions on Wireless Communications, 2013Co-Authors: Ziaul Hasan, V K BhargavaAbstract:User cooperation although improves performance of wireless systems, it requires incentives for the potential cooperating nodes to spend their energy acting as relays. Moreover, these potential relays are better informed than the source about their transmission costs, which depend on the exact channel conditions on their relay-destination links. This results in asymmetry of available information between the source and the relays. In this paper, we use Contract Theory to tackle the problem of relay selection under asymmetric information in OFDM-based cooperative wireless system that employs decode-and-forward (DF) relaying. We first design incentive compatible offers/Contracts, consisting of a menu of payments and desired signal-to-noise-ratios (SNR)s at the destination. The source then broadcasts this menu to nearby mobile nodes. The nearby mobile nodes which are willing to relay, notify back the source with the Contracts they agree to accept in each subcarrier. We show that when the source is under a budget constraint, the problem of relay selection in each subcarrier with the goal of maximizing capacity is a nonlinear non-separable knapsack problem. We propose a heuristic relay selection scheme to solve this problem. We compare the performance of our overall mechanism and the heuristic solution with a simple relay selection scheme. Selected numerical results show that our solution performs better and is close to optimal. The benefits of the overall mechanism introduced in this thesis is that it is simple to implement, needs limited interaction with potential relays and hence it requires minimal signalling overhead.
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relay selection for ofdm wireless systems under asymmetric information a Contract Theory based approach
arXiv: Networking and Internet Architecture, 2012Co-Authors: Ziaul Hasan, V K BhargavaAbstract:User cooperation although improves performance of wireless systems, it requires incentives for the potential cooperating nodes to spend their energy acting as relays. Moreover, these potential relays are better informed than the source about their transmission costs, which depend on the exact channel conditions on their relay-destination links. This results in asymmetry of available information between the source and the relays. In this paper, we use Contract Theory to tackle the problem of relay selection under asymmetric information in OFDM-based cooperative wireless system that employs decode-and-forward (DF) relaying. We first design incentive compatible offers/Contracts, consisting of a menu of payments and desired signal-to-noise-ratios (SNR)s at the destination and then the source broadcasts this menu to nearby mobile nodes. The nearby mobile nodes who are willing to relay notify back the source with the Contracts they are willing to accept in each subcarrier. We show that when the source is under a budget constraint, the problem of relay selection in each subcarrier in order to maximize the capacity is a nonlinear non-separable knapsack problem. We propose a heuristic relay selection scheme to solve this problem. We compare the performance of our overall mechanism and the heuristic solution with a simple relay selection scheme and selected numerical results showed that our solution performs better and is close to optimal. The overall mechanism introduced in this paper is simple to implement, requires limited interaction with potential relays and hence requires minimal signalling overhead.