Game-based data offloading scheme for IoT system traffic congestion problems

Park and Kim EURASIP Journal on Wireless Communications and Networking (2015) 2015:192 DOI 10.1186/s13638-015-0418-y RESEARCH Open Access Game-based data offloading scheme for IoT system traffic congestion problems Youngjae Park and Sungwook Kim* 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. Keywords: Internet of things; Data offloading; Game theory; VCG mechanism; Rubinstein bargaining model 1 Introduction 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. The basic idea of IoT is to connect things to enhance several aspects of everyday life and behavior of potential users. Especially, with cellular network systems, ubiquitous public services would be of enormous benefit. However, due to the unprecedented worldwide growth of data traffic, which is expected to reach 10.8 exabytes per month by 2016, an 18-fold increase over 2011, effective traffic congestion mechanisms are needed [1–4]. To cope with explosive traffic demands, traditional network expansion methods have been developed while acquiring more spectrum licenses, deploying new micro-cells of small size, and upgrading technologies. But, these approaches are costly and time-consuming. Therefore, network operators must find a new novel method to resolve the mismatch between network capacity and traffic growth [2, 5, 6]. * Correspondence: Department of Computer Science, Sogang University, 35 Baekbeom-ro (Sinsu-dong), Mapo-gu, Seoul 121-742, South Korea For IoT/cellular network systems, mobile data offloading appears as one of the most attractive data delivering solutions. Data offloading mechanism has been developed to offload traffic from cellular networks to high capacity and free device-to-device networks. Recently, a growing number of studies have been devoted to the potential performance benefits of mobile data offloading and the technologies to support it. However, the existing researches only focused on the technical aspect of data offloading without considering the economic incentive for access point owners (APOs) to admit cellular network traffic. This incentive issue is particularly important for the scenario where APOs are privately owned by third-party entities who are expected to be reluctant to admit non-registered users’ traffic without proper incentives [2]. In this paper, we consider a new user-initiated data offloading scheme. In the proposed scheme, Internet of things modules (IoTMs) initiate the offloading process and the mobile network operators (MNOs) are responsible of incentivizing APOs. As users, IoTMs are assumed either (1) compliant or properly incentivized, such that they will offload their traffic exactly as the networks intended or (2) unaware of the offloading process at all; it means that data offloading is totally transparent to IoTMs. In this work, data offloading actions are only triggered by either an IoTM or a MNO. To reduce © 2015 Park and Kim. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Park and Kim EURASIP Journal on Wireless Communications and Networking (2015) 2015:192 communication costs, IoTMs offload data while the MNO tries to ease traffic congestion of cellular networks. Basically, we can assume that IoTMs, MNO, and APOs can make strategic decisions independently and rationally to maximize their payoffs. Due to this reason, game theory can be a suitable approach for data offloading scenarios. Game theory is a field of applied mathematics that provides an effective tool in modeling the interactions among independent decision-makers. It can describe the possibility to react to the actions of the other decisionmakers and analyze the situations of conflict and cooperation [7]. In this paper, we adopt Vickrey-Clarke-Groves (VCG) mechanism and Rubinstein bargaining game model to design the data offloading algorithm. The VCG mechanism implements efficient social choice functions in environments in which participants have private information about their preferences. In this mechanism, the game participants’ payoffs equal their respective marginal contributions to the social surplus [8]. A Rubinstein bargaining model refers to a class of bargaining games that feature alternating offers through an infinite time horizon. Rubinstein’s solution is one of the most influential findings in game theory [9]. 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. The main contributions of our work are as follows: 1. We propose a new pricing method by considering the characteristics of APOs and IoTMs. This method can induce the cooperation between APOs and IoTMs in data offloading operations. 2. Based on the Rubinstein bargaining model, we can fairly distribute the surplus profit. It can ensure the system effectiveness. 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. The rest of the paper is structured as follows. In Section 2, we survey previous work in resource allocations, auction-based game theory models, and data offloading algorithms. In Section 3, we explain in detail our proposed mobile data offloading algorithm. In Section 4, we discuss the experimental environment for performance evaluation and analyze simulation results. Finally, we conclude the paper in Section 5. 2 Related work In this chapter, we review the recently researched literatures that relate to our proposed scheme. Currently, Page 2 of 10 several (...truncated)