作者机构：
[Huang, Xiaoyun; Huo, Ban; He, Tingting; Jiang, Xingpeng; Sun, Han; Fu, Lingling] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Peoples R China.;[Huang, Xiaoyun; Huo, Ban; He, Tingting; Jiang, Xingpeng; Sun, Han; Fu, Lingling] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;[Sun, Han; Fu, Lingling] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Peoples R China.;[Huang, Xiaoyun] Cent China Normal Univ, Collaborat & Innovat Ctr Educ Technol, Wuhan 430079, Peoples R China.;[He, Tingting; Jiang, Xingpeng] Cent China Normal Univ, Natl Language Resources Monitoring & Res Ctr Netw, Wuhan 430079, Peoples R China.
通讯机构：
[Jiang, Xingpeng] C;Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Natl Language Resources Monitoring & Res Ctr Netw, Wuhan 430079, Peoples R China.
摘要：
The dysbiosis of microbiome may have negative effects on a host phenotype. The microbes related to the host phenotype are regarded as microbial association signals. Recently, statistical methods based on microbiome-phenotype association tests have been extensively developed to detect these association signals. However, the currently available methods do not perform well to detect microbial association signals when dealing with diverse sparsity levels (i.e., sparse, low sparse, non-sparse). Actually, the real association patterns related to different host phenotypes are not unique. Here, we propose a powerful and adaptive microbiome-based association test to detect microbial association signals with diverse sparsity levels, designated as MiATDS. In particular, we define probability degree to measure the associations between microbes and the host phenotype and introduce the adaptive weighted sum of powered score tests by considering both probability degree and phylogenetic information. We design numerous simulation experiments for the task of detecting association signals with diverse sparsity levels to prove the performance of the method. We find that type I error rates can be well-controlled and MiATDS shows superior efficiency on the power. By applying to real data analysis, MiATDS displays reliable practicability too. Copyright (C) 2021, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights reserved.
摘要：
DTN（Delay Tolerant Network）具有间歇性连接、资源有限以及拓扑结构随机动态变化等特点,因此会受到网络资源有限和网络拓扑不确定性的限制,极易产生网络拥塞。针对这一问题,提出了一种基于消息质量度和节点可信度的拥塞控制策略CCMQ（Congestion Control Based on Message Quality and Node Reliability in DTN）。该策略主要根据消息的质量度划分消息的优先级,在转发消息时,将优先级高的消息优先转发;在选择下一跳节点时,选择节点可信度高的节点进行消息的转发,并充分考虑中继节点自身的属性;在发生拥塞时,消息质量度小的消息被率先丢弃,同时增加了S-ACK消息确认删除机制,以释放节点的缓存空间,从而有效缓解节点拥塞。仿真结果表明,相比传统的拥塞控制算法,CCMQ在消息递交率、网络负载率和平均时延性能方面都有较大的提升。
作者机构：
[He, Yan; Chen, Jiageng] Cent China Normal Univ, Wollongong Joint Inst, Wuhan 430079, Peoples R China.;[Chen, Jiageng] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.
通讯机构：
[Jiageng Chen] S;School of Computer, Central China Normal University, Wuhan, 430079, China<&wdkj&>Central China Normal University Wollongong Joint Institute, Wuhan, 430079, China
关键词：
Internet of things;Location-based services;Location privacy;Privacy protection mechanism;Confidentiality
摘要：
With the rapid development of the Internet of Things (IoT), Location-Based Services (LBS) are becoming more and more popular. However, for the users being served, how to protect their location privacy has become a growing concern. This has led to great difficulty in establishing trust between the users and the service providers, hindering the development of LBS for more comprehensive functions. In this paper, we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem. This mechanism not only guarantees the confidentiality of the user’s information during the subsequent information interaction and dynamic data transmission, but also meets the service provider’s requirements for related data.
摘要：
机会网络中的通信设备大多是随着时间的流逝而进行移动的,然而节点之间的移动路径又具有一定的重复性.因此,可以记录节点移动时与之相遇的节点之间的信息,利用该信息对路由算法做出更合理的决策.本文根据节点之间的相遇历史信息,提出了一种基于节点相似率的概率路由算法（Probabilistic routing algorithm based on node similarity rate,S-Prophet）,对传统的Prophet算法的预估节点传输概率阶段进行改进.首先统计网络中节点与其他节点的相遇集合,定义节点相似率,设计一个新的节点投递概率公式,并根据节点相遇持续时间对Prophet路由算法的概率衰减公式进行改变,最后,通过仿真实验验证SProphet的有效性.
