Security-Aware Resource Allocation for Mobile Social Big Data: A Matching-Coalitional Game Solution
Security-Aware Resource Allocation for Mobile Social Big Data: A Matching-Coalitional Game Solution
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DOI：
10.1109/tbdata.2017.2700318
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发表时间：
2021-09-01
影响因子：
7.2
通讯作者：
Xu, Qichao
中科院分区：
文献类型：
--
作者：
Su, Zhou;Xu, Qichao
随着移动网络规模和移动用户数量的不断增长，移动社交大数据应用应运而生，移动社交用户可以利用移动设备相互交换和分享内容。移动社交大数据在传输过程中需要安全资源来保护。然而，由于安全资源有限，如何分配安全资源成为新的挑战。因此，在本文中，我们提出了一种基于联合匹配联盟博弈的安全感知资源分配方案来提供移动社交大数据。在所提出的方案中，首先引入了基站（BS）的联盟博弈模型，以形成群体来提供无线和安全资源，从而可以提高资源效率和利润。其次，采用基于匹配理论的模型来确定社区和基站联盟之间的选择过程，以便移动社交用户可以形成社区来选择最佳联盟以获得安全资源。第三，提出了一种联合匹配联盟算法来获得稳定的安全感知资源分配。最后，仿真实验证明该方案优于其他现有方案。
As both the scale of mobile networks and the population of mobile users keep increasing, the applications of mobile social big data have emerged where mobile social users can use their mobile devices to exchange and share contents with each other. The security resource is needed to protect mobile social big data during the delivery. However, due to the limited security resource, how to allocate the security resource becomes a new challenge. Therefore, in this paper we propose a joint match-coalitional game based security-aware resource allocation scheme to deliver mobile social big data. In the proposed scheme, first a coalition game model is introduced for base stations (BSs) to form groups to provide both wireless and security resource, where the resource efficiency and profits can be improved. Second, a matching theory based model is employed to determine the selecting process between communities and the coalitions of BSs so that mobile social users can form communities to select the optimal coalition to obtain security resource. Third, a joint matching-coalition algorithm is presented to obtain the stable security-aware resource allocation. At last, the simulation experiments prove that the proposal scheme outperforms other existing schemes.