A social group utility maximization framework with applications in database assisted spectrum access

Chen, Xu; Gong, Xiaowen; Yang, Lei; Zhang, Junshan

doi:10.1109/infocom.2014.6848136

Cited by 69 publications

(63 citation statements)

References 18 publications

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“…As discussed also in this paper, recent observations can be used in predicting future availability and additionally spectrum users located close to each other may experience similar spectrum availabilities. Joint use of physical and social characteristics can be used to assist spectrum access [21] and device-to-device (D2D) communications [22]- [24].…”

Section: Social-aware Spectrum Accessmentioning

confidence: 99%

Predictive channel selection: Practical implementation and a social-aware vision for spectrum use

Höyhtyä¹,

Korpi²,

Hiivala³

2017

EAI Endorsed Transactions on Cognitive Communications

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This paper demonstrates a predictive channel selection method by implementing it in software-defined radio (SDR) platforms and measuring the performance using over-the-air video transmissions. The method uses both long term and short term history information in selecting the best channel for data transmission. Controlled interference is generated in the used channels and the proposed method is compared to reference methods. The achieved results show that the predictive method is a practical one, able to increase the throughput and reduce number of collisions and channel switches by using history information intelligently. The method is developed further and a cellular assisted social-aware method that enables efficient use of D2D links is defined in the end of this paper.

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Section: Social-aware Spectrum Accessmentioning

confidence: 99%

Predictive channel selection: Practical implementation and a social-aware vision for spectrum use

Höyhtyä¹,

Korpi²,

Hiivala³

2017

EAI Endorsed Transactions on Cognitive Communications

View full text Add to dashboard Cite

show abstract

“…The Social Group Utility Maximization (SGUM) scheme [11] is developed for cooperative networking that takes into accounts both social relationships and physical coupling among network users. Instead of maximizing its individual utility or the overall network utility, each user aims to maximize its social group utility that hinges heavily on its social ties with other users in IoT systems.…”

Section: Related Workmentioning

confidence: 99%

“…Instead of maximizing its individual utility or the overall network utility, each user aims to maximize its social group utility that hinges heavily on its social ties with other users in IoT systems. The SGUM scheme provides rich modeling flexibility and spans the continuum space between noncooperative game and network utility maximization [11].…”

Section: Related Workmentioning

confidence: 99%

“…In Section 4, we explain in detail the developed IoT system management algorithm based on the behavioral learning game model. We present the experimental results in Section 5 and compare the performance to other existing schemes [5,11]. Finally, we give our conclusion and future work in Section 6.…”

Section: Introductionmentioning

confidence: 99%

“…The rapid IoT development makes it possible for connecting various smart objects together through device-to-device communications and providing more data interoperability methods for application purpose [10]. However, there is much room left to exploit diverse social interactive relationships among agents for networking optimization, and it is of great interest to explore the continuum space [11][12][13]. Motivated by the facts presented in the above discussion, in this paper, we design a new IoT communication control scheme based on the behavioral learning game model.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Behavioral learning game for socio-physical IoT connections

Kim

2016

J Wireless Com Network

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Game theory is an innovative idea to understanding human behaviors from economics to political science. However, due to the bounded rationality of game players, game theory alone cannot fully explain human behavior and should complement other key concepts championed by the behavioral disciplines. This paper provides a foundation for decision-making process from the viewpoint of game theory and behavioral science approach. First, we develop a new behavioral learning game model to examine how bounded rationality is exhibited in the game player's cognitive capabilities. Second, we apply the developed game model to operate the socio-physical Internet of Things (IoT) system. Finally, we study how to effectively negotiate between players who, though interested in their own welfare, are also willing to consider other players in the IoT system. The main contribution of our work lies in the fact that we shed some new light on the interplay between the game player's selfishness and the public interest. We believe that our approach will open a new door to exploring the impact of social behavior on networking.

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Socially‐Aware Cooperative D2D and D4D Communications toward Fog Networking

Zhang

Misra

2017

Fog for 5G and IoT

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A social group utility maximization framework with applications in database assisted spectrum access

Cited by 69 publications

References 18 publications

Predictive channel selection: Practical implementation and a social-aware vision for spectrum use

Predictive channel selection: Practical implementation and a social-aware vision for spectrum use

Behavioral learning game for socio-physical IoT connections

Socially‐Aware Cooperative D2D and D4D Communications toward Fog Networking

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