社会感知多副本车载自组织网络机会路由协议

为提高车载自组织网络(vehicular Ad hoc networks, VANETs)中消息投递的效率, 提出了一种社会感知多副本车载自组织网络机会路由协议(SAMOR)。协议结合了车载自组织网络中节点的社会性特点和多副本路由方案的优势, 采用携带—存储—转发的机会路由方式进行消息投递。利用节点间的相遇历史区分社区节点和全局节点, 并使用所提出的节点社区中心性和网络中心性的度量方法, 得到了节点的效用。在路由过程的扩散阶段, 节点间按效用分配副本, 在转发阶段, 副本继续向效用高的节点转发。仿真结果表明, SAMOR实现了较高的消息投递成功率和较低的延迟。     

一种基于历史相遇信息的容迟网络地理路由算法

为使消息在容迟网络中更有效地传输,将节点的地理位置、移动方向等地理信息与节点间的历史相遇频繁程度相结合,提出一种新的容迟网络地理路由算法。该算法将移动节点间的历史相遇信息作为分配消息副本的依据,从而减少复制策略路由算法中的副本数量。利用邻居节点移动方向所构成的夹角对中继节点的选择进一步优化,得到较高的投递率以及较低的端到端平均时延。仿真结果表明,当节点移动相对缓慢并且消息生存周期较短时,该算法的消息投递率优于Spray&Wait,Epidemic,Prophet等路由算法,在消息生存周期较短的情况下,当节点的缓存资源为限制路由算法性能的瓶颈因素时,与Epidemic算法相比,网络负载率降低40%,与Prophet算法相比负载降低了25%,有效减少了平均跳数和平均时延。     

基于节点运动预测的社会性DTN高效路由

延迟容忍网络是一种缺乏持续连接的新型网络体系结构,采用存储-携带-转发的路由方式进行消息的转发.考虑到节点的特性及运动模式,基于分簇、社会网络的路由协议已成为近年来的一个研究热点.该文分析现有基于分簇、社会网络的路由算法的缺陷及社会网络的特点,提出了一种新型的混合路由算法CS-DTN(Clustering&Social Delay Tolerant Network):预测节点间的相遇概率并据此对节点进行分簇,簇内根据节点间相遇概率限定消息的副本数量,将消息以二分喷射的方式转发到更可能到达目的节点的中继节点;簇间对节点进行运动预测并结合节点的特性将消息不断地转发到更接近目的节点的中继节点.不同于已有的基于分簇、社会网络的路由算法,CS-DTN从多个角度结合了节点自身及节点间的特性,更考虑了对节点的运动预测,降低了由不必要的消息转发带来的资源浪费,同时也能更高效地将消息投递到目的节点.仿真结果表明CS-DTN较为明显地提升了消息的成功投递率并降低了消息的平均端到端延迟,在缓存足够的前提下,CS-DTN可以实现高达95%的投递率,而在资源有限的情况下也能获得80%以上的投递率.     

基于位图传递的机会网络免疫机制

在机会网络中,大多数路由机制采用多副本传输,当消息已经投递成功后,消息副本仍然保留在节点缓存中。通过免疫机制,节点自动删除缓存中已经成功投递的消息副本,并拒绝接收已投递的消息。分析几种免疫机制,提出一种基于位图传递的机会网络免疫机制:(1)以确认位图来表示消息的投递情况;(2)节点相遇时首先交换彼此的确认位图,根据确认位图删除本地冗余消息;(3)每个节点保留一个既往消息信息,通过既往消息减少确认信息的传递。仿真结果表明,该免疫机制能简单高效地转发确认信息,及时删除冗余消息,降低负载率、平均时延,提高消息投递率。     

基于历史相遇间隔的机会网络路由协议

针对大多数机会网络路由协议在寻找端到端通信链路时不能很好地抓住节点社会性质的问题,提出一种基于历史相遇间隔(HICR) 协议的路由算法。HICR协议利用社会关系的特点,根据节点之间的历史相遇间隔判断它们的亲密程度,转发消息给离目的节点更亲近的节点,使得消息朝更靠近目的节点方向发送。仿真结果表明,该HICR协议在网络资源有限的的情况下,与Epidemic协议和Prophet协议相比,能获得更高的消息交付率。     

一种面向机会网络路由的最优停止决策方法

投递延迟是机会网络的一个重要指标,给定节点缓存和消息副本数目限制,如何选择合适的节点复制消息成为一个关键问题.提出一种基于最优停止理论的路由决策方法（OSDR）.OSDR 将每个时隙上所遇节点和目标节点的平均相遇时间看做一个随机变量,根据该随机变量的统计特性得到一个停止观察、复制消息的规则,该规则呈现简单的阈值结构,即当某个时隙上所遇节点和目标节点的平均相遇时间小于给定阈值时即复制消息. OSDR 可以在较小的相遇间隔和等待成本之间进行折衷,实现数学期望意义上的最小消息投递延迟.介绍了OSDR 的网络模型、最优停止规则的存在性证明过程以及计算方法.模拟实验结果表明,OSDR 相对其他方法,在投递成功率、投递延迟等方面具有明显优势.     

机会网络中基于社区的高效消息传输算法

针对机会社会网络中现有基于社区的消息传输算法(OSNCMTS)在社区内存在节点积压消息分发任务、在社区间存在盲目选择活跃节点转发信息的问题,提出一种基于社区的高效机会网络路由算法(HECMTS)。在HECMTS算法中,首先,采用极值优先(EO)算法划分社区并将划分的社区矩阵分发给社区节点;其次,采用社区矩阵和消息到目的节点成功率相结合的方法分配社区内消息副本数;最后,利用活跃节点往返不同社区的机会收集活跃节点信息,然后查询这些活跃节点信息从中选取合适的活跃节点完成社区间消息传输。仿真结果表明,与OSNCMTS算法相比,HECMTS算法在路由开销性能和平均端到端时延性能上分别至少下降了19%和16%。     

试析基于机会网络的终端消息传播方法及其应用

简述了机会网络及其消息传播方法,提出了一种改进的基于机会网络的终端消息传播方法,并分析了机会网络的应用。改进的传播方法具体为:在传统BSW算法基础上,对于节点分配和携带消息副本数量上参考了节点活跃度数值,阶梯式的消息副本数量,使得消息副本在传递过程中始终尽可能由活跃度高的节点进行传递,提高了消息投递的成功率,减少了网络内的消息完余。     

节点密度感知的容迟网络路由协议*

为适应容迟网络的动态变化,提高路由性能,结合空间节点分布和节点度中心性,提出一种节点密度感知的容迟网络路由协议DAR。该协议引入移动模型的节点分布,通过感知节点当前所处位置的节点密度,动态选择在网络中传播的消息副本数量,并根据节点的度中心性选择中继和分配消息副本数量。仿真结果表明,DAR能够提高传输率、降低传输延迟,在一定程度上降低了资源消耗。     

基于马尔可夫决策过程的机会网络转发策略

在机会网络节点随机移动的场景中,提高路由算法性能评价中的投递率,控制开销率,降低平均迟延是持续的研究方向。由于目前机会网络结构稀疏和拓扑多变,单副本路由转发策略效率较低。通过结合花粉布朗运动与机会网络节点的随机运动的相似性,并分析节点随机运动的规律,定义了一种基于马尔可夫决策过程的节点转发策略。该策略在平均延时适当增加的情况下,可以有效控制网络开销率,提高消息投递率。最后通过仿真实验验证了理论模型的正确性。     

How to Archive an Event: Reflections on the Social Repository of Ireland

Reflecting on a feasibility study into archiving social media, this article traces how “events” are defined in various domains and contexts, and employs case studies to analyze key relationships between hashtags and events to provide a critical analysis of how archival events can be constructed out of social events. It provides an overview of the archival and curatorial considerations involved in defining and preserving a social media event, and outlines the technologies developed for the process of collecting, annotating, and preserving social media events. Overall, the article endeavors to reveal how pragmatic considerations, computational approaches and curatorial perspectives shape digital archives and historical narratives.     

BBS中信息传播模式的特征分析

通过比较传染病传播机制与信息传播机制,提出BBS中的信息传播机制模型。通过对BBS中帖子数量变化规律的建模,分析了BBS中信息传播模式的特征,并使用实际数据说明BBS中的信息传播模式。实验表明：BBS可以吸引大批的用户参与,但用户只对部分话题感兴趣并参与讨论;绝大多数话题（占94.9%）帖子数的增长率先增加再减小直至为0,而少量话题（占5.1%）帖子数的增长率直接减小至0。这些结论有助于认识BBS的信息传播机制,对控制和管理BBS的信息传播有启发意义。     

Community building and knowledge sharing by individuals with disabilities using social media

The use of social media to share information, enhance learning, and connect with an online community has grown rapidly over the past 10 years. As social media becomes a more common tool in both formal and informal education, it is imperative to understand how it is used by individuals with disabilities. Through a systematic study of the literature, 215 articles on social media used by individuals with disabilities were selected and 29 selected for in-depth thematic analysis. Six major themes were identified: community, cyberbullying, self-esteem, self-determination, access to technology, and accessibility. To confirm these six categories, we expanded our search, yielding an additional 30 articles, for a total 59 articles reviewed in-depth. Interactions between individuals with disabilities within online communities often had the goal of acquiring knowledge or learning new information. A communities of practice theoretical framework is used to discuss interactions among the elements of social media design, learning, and the building of community by individuals with disabilities.     

基于社会认证的网络身份模型

网络实名制的提出,是为了解决网络匿名性所带来的问题,却又面临实名信息泄露的诟病。造成信息泄露的根源在于实名认证依赖于实名信息。基于社会认证的网络身份模型,依赖社会关系进行身份认证,其利用OSN节点的社会关系构建网络身份,在发挥网络监管作用的同时,避免实名信息的泄漏。模型首先在OSN中依据一定策略选择根节点;然后,采用担保方式进行社会认证;最后,在不依赖实名信息的基础上,构建节点的唯一网络身份SANI。SNAI身份含节点的社会认证信息,具有身份认证和行为溯源的功能。     

Cultivating Social Resources on Social Network Sites: Facebook Relationship Maintenance Behaviors and Their Role in Social Capital Processes

This study explores the relationship between perceived bridging social capital and specific Facebook‐enabled communication behaviors using survey data from a sample of U.S. adults (N=614). We explore the role of a specific set of Facebook behaviors that support relationship maintenance and assess the extent to which demographic variables, time on site, total and “actual” Facebook Friends, and this new measure (Facebook Relationship Maintenance Behaviors) predict bridging social capital. Drawing upon scholarship on social capital and relationship maintenance, we discuss the role of social grooming and attention‐signaling activities in shaping perceived access to resources in one's network as measured by bridging social capital.     

An Efficient Two-Phase Model for Computing Influential Nodes in Social Networks Using Social Actions

在社会网络的影响的测量在数据采矿社区收到了很多注意。影响最大化指发现尽量利用信息或产品采纳的有影响的用户的过程。在真实设置,在一个社会网络的一个用户的影响能被行动的集合建模(例如,份额,重新鸣叫,注释) 在其出版物以后由网络的另外的用户表现了。就我们的知识而言,在文学的所有建议模型同等地对待这些行动。然而,它是明显的一工具少些比一样的出版的份额影响的一份出版物相似。这建议每个行动有它影响的自己的水平(或重要性) 。在这份报纸,我们建议一个模型(叫的社会基于行动的影响最大化模型, SAIM ) 为在社会网络的影响最大化。在 SAIM,行动没在测量一个个人的影响力量同等地被考虑,并且它由二主要的步组成。在第一步,我们在社会网络计算每个个人的影响力量。这影响力量用 PageRank 从用户行动被计算。在这步的结束,我们得到每个节点被它的影响力量在标记的一个加权的社会网络。在 SAIM 的第二步,我们计算一个新概念说出 influence-BFS 树的使用的有影响的节点的一个最佳的集合。在大规模真实世界、合成的社会网络上进行的实验在计算揭示我们的模型 SAIM 的好表演,在可接受的时间规模,允许信息的最大的传播的有影响的节点的一个最小的集合。     

Perceived social support moderates the relationships between variables in the social cognition model

Posting behaviour on social networking sites (SNS) has become a method enabling unsatisfied users to vent emotions. Based on social cognition theory (SCT), personal outcome expectations and self-efficacy affect posting behaviour for venting emotions on SNS. However, perceived social support (PSS) may alter the relationships within the SCT model. Thus, this study aimed to explore the moderating effect of PSS on the relationships between variables in the SCT model for venting emotions on SNS. In total, 310 unsatisfied customers in Taiwan were investigated, and structural equation modelling was performed to test the hypotheses. The results indicated that personal outcome expectations and self-efficacy were positively associated with posting behaviour which, in turn, increased venting emotions on SNS. Moreover, PSS moderated the relationships between variables in the SCT model.     

Topology-Based Recommendation of Users in Micro-Blogging Communities

Nowadays,more and more users share real-time news and information in micro-blogging communities such as Twitter,Tumblr or Plurk.In these sites,information is shared via a followers/followees social network structure in which a follower will receive all the micro-blogs from the users he/she follows,named followees.With the increasing number of registered users in this kind of sites,finding relevant and reliable sources of information becomes essential.The reduced number of characters present in micro-posts along with the informal language commonly used in these sites make it difficult to apply standard content-based approaches to the problem of user recommendation.To address this problem,we propose an algorithm for recommending relevant users that explores the topology of the network considering different factors that allow us to identify users that can be considered good information sources.Experimental evaluation conducted with a group of users is reported,demonstrating the potential of the approach.     

Specifying the dynamics of social technologies as social microworlds

This paper explores the affordances of social technologies for supporting the construction of a shareable artefact by a group of learners. A qualitative study that captures the use of five different types of social technologies (Facebook, blogs, wikis, Google Documents and Dropbox) in three different classroom settings sheds light on the potentials and challenges of these tools for supporting material exploration, artefact construction and evaluation. Qualitative content analysis of instructors’ field notes, students’ and instructors’ reflections, interviews and focus groups sheds light on the potential of social technologies to transform the activity of learning across a new culture of computational tools. The affordances of social technologies are discussed as well as design principles that need to be followed in these new arenas.     

Behavior‐Based Propagation of Trust in Social Networks with Restricted and Anonymous Participation

Increasing interactions and engagements in social networks through monetary and material incentives is not always feasible. Some social networks, specifically those that are built on the basis of fairness, cannot incentivize members using tangible things and thus require an intangible way to do so. In such networks, a personalized recommender could provide an incentive for members to interact with other members in the community. Behavior‐based trust models that generally compute social trust values using the interactions of a member with other members in the community have proven to be good for this. These models, however, largely ignore the interactions of those members with whom a member has interacted, referred to as “friendship effects.” Results from social studies and behavioral science show that friends have a significant influence on the behavior of the members in the community. Following the famous Spanish proverb on friendship “Tell Me Your Friends and I Will Tell You Who You Are,” we extend our behavior‐based trust model by incorporating the “friendship effect” with the aim of improving the accuracy of the recommender system. In this article, we describe a trust propagation model based on associations that combines the behavior of both individual members and their friends. The propagation of trust in our model depends on three key factors: the density of interactions, the degree of separation, and the decay of friendship effect. We evaluate our model using a real data set and make observations on what happens in a social network with and without trust propagation to understand the expected impact of trust propagation on the ranking of the members in the recommended list. We present the model and the results of its evaluation. This work is in the context of moderated networks for which participation is by invitation only and in which members are anonymous and do not know each other outside the community. Copyright © 2014 John Wiley & Sons, Ltd.