期刊文献+

物联网中基于信任的频谱资源分配机制 被引量:14

Trust-based Spectrum Resource Allocation Mechanism in Internet of Things
在线阅读 下载PDF
导出
摘要 随着无线网络的快速发展,物联网中频谱资源的高效分配问题亟需解决,为此,提出一种基于信任的频谱资源分配机制TSRA.借鉴拍卖理论建立频谱资源拍卖系统模型,根据信任理论确定用户间的信任关系以缩小客户网络范围,利用属性加密理论保护交易数据.在此基础上,采用改进的蚁群算法为用户合理规划资源分配路径,从而实现频谱资源的多目标分配.实验结果表明,该机制可以为用户的交易数据提供细粒度的保护,且具有较高的社会效益和较低的系统计算与通信开销. With the rapid development of wireless networks,the problem of efficient allocation of spectrum resources in the Internet of Things(IoT)needs to be solved.Therefore,this paper proposes TSRA,a trust based spectrum resources allocation mechanism.By referring to the auction theory,the suction system model of spectrum resources is established.According to the trust theory,the trust relationship between users is determined to narrow down the scope of customer network and the transaction data is protected by the attribute encryption theory.On this basis,the improved ant colony algorithm is used to make reasonable plan for the resources allocation path,so as to achieve multi-objective allocation of spectrum resources.Experimental results show that the proposed mechanism can provide fine-grained protection for users’transaction data.It has high social benefits and low system computing and communication costs.
作者 魏新艳 张琳 WEI Xinyan;ZHANG Lin(School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
出处 《计算机工程》 CAS CSCD 北大核心 2020年第4期26-32,39,共8页 Computer Engineering
基金 国家自然科学基金(61872194,61402241) 江苏省自然科学优秀青年基金(BK20160089) 江苏省高校自然科学研究面上项目(17KJB520026) 南京邮电大学校级科研基金(NY217050)。
关键词 频谱资源 信任 加密 拍卖理论 蚁群算法 spectrum resource trust encryption auction theory ant colony algorithm
  • 相关文献

参考文献8

二级参考文献50

  • 1徐精明,曹先彬,王煦法.多态蚁群算法[J].中国科学技术大学学报,2005,35(1):59-65. 被引量:66
  • 2HAYKIN S. Cognitive radio:brain-empowered wireless communications[J]. IEEE Journal on Selected Areas in Communications, 2005, 23(2):201-220.
  • 3NEEL J, REED J H, GILLS R P. The role of game theory in the analysis of software radio networks[A]. SDR Forum Technical Conference[C]. November, 2002.
  • 4ETKIN R, PAREKH A. Spectrum sharing for unlicensed bands[J]. IEEE. Journal on Selected Areas In Communications, 2007,25(3): 517-528.
  • 5SUN J, MODIANO E, ZHENG L. Wireless channel allocation using an auction algorithm[J].IEEE Journal on Selected Areas in Communications, 2006, 24(5): 1085-1096.
  • 6DRAMITINOS M, STAMOULIS G, COURCOUBETIS C. Auction-based resource reservation in 2.5/3G networks[J]. Mobile Networks and Applications, December 2004, 9(6): 557-566.
  • 7HUANG J, HAN Z, CHIANG M, et al. Auction-based resource allocation for cooperative communications[J]. IEEE Journal on Selected Areas in Communications, September 2008, 26(7): 1226-1247.
  • 8NIYATO D, HOSSAIN E. Optimal price competition for spectrum sharing in cognitive radio: a dynamic game-theoretic approach[A]. IEEE GLOBECOM'04[C]. 2007.4625-4629.
  • 9NIYATO D, HOSSAIN E. Competitive pricing for spectrum sharing in cognitive radio networks: dynamic game, inefficiency of Nash equilibrium, and collision[J]. IEEE Journal on Selected Areas in Communications, Jan.2008, 26(1):192-202.
  • 10WANG X B, LI Z, XU P C, et al. Spectrum sharing in cognitive radio networks-an auction based approach[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2010, 40(3): 587-596.

共引文献32

同被引文献133

引证文献14

二级引证文献29

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部