Abstract
Internet of things (IoT) is seen as another information and industrial wave after the invention of personal computers, the Internet, and mobile communication networks. Especially, IoT/cellular network integration becomes a new service platform for the different kinds of traffic manipulation. However, due to the excessive traffic demands, it is currently facing a severe traffic overload problem. In this paper, we propose a new traffic control scheme based on the data offloading technique. By using the Vickrey-Clarke-Groves (VCG) mechanism and Rubinstein bargaining game model, our data offloading approach can effectively alleviate the IoT traffic congestion while enhancing the quality-of-service (QoS) in cellular network systems. Finally, we show the effectiveness of our proposed scheme through extensive simulations.
Highlights
Internet of things (IoT) is a novel paradigm that integrates several technologies such as wired and wireless networks, enhanced communication protocols, distributed intelligence for smart objects, mobile phones, and undoubtedly the Internet
Based on the combination of VCG mechanism and Rubinstein bargaining model, mobile network operators (MNOs), access point owners (APOs), and Internet of things modules (IoTMs) participate in the data offloading process for the effectiveness of IoT/cellular system operation
Through the adaptive combination of VCG mechanism and Rubinstein bargaining model, MNO, APOs, and IoTMs actively participate in the data offloading process in the IoT/cellular system environment
Summary
Internet of things (IoT) is a novel paradigm that integrates several technologies such as wired and wireless networks, enhanced communication protocols, distributed intelligence for smart objects, mobile phones, and undoubtedly the Internet. Based on the combination of VCG mechanism and Rubinstein bargaining model, MNO, APOs, and IoTMs participate in the data offloading process for the effectiveness of IoT/cellular system operation. 3. Through the adaptive combination of VCG mechanism and Rubinstein bargaining model, MNO, APOs, and IoTMs actively participate in the data offloading process in the IoT/cellular system environment. In the paper [15], authors have proposed a novel framework to model mobile applications as a locationtime workflows of tasks and showed that an optimal mapping of location-time workflows to tiered mobile cloud resources is an NP-hard problem They proposed an efficient heuristic algorithm that can perform well and scale well to a large number of users while ensuring high application QoS.
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