Pub Date : 2014-10-01DOI: 10.1109/ComComAp.2014.7017184
Chenfei Zhang, L. Lei, Ting Zhang
Performance evaluation of IEEE 802.11 multi-hop wireless networks has been drawing significant attention in recent years whereas most studies ignore the interfering noise far away. However, since the packets may overlap in time in multi-hop wireless networks, the cumulative energy of the noise coming from far away can be high enough to affect the performance of the network. In this paper, we investigate the interfering noise in the IEEE 802.11 wireless multi-hop networks. Then, we perform simulations to evaluate the effect of cumulative interfering noise on the performance of IEEE 802.11 DCF protocol. The results show that the transmission probability, collision probability and the saturation throughput of each flow in IEEE 802.11 multi-hop wireless networks have been greatly affected by the cumulative interfering noise.
{"title":"Analyzing the cumulative interfering noise in multi-hop IEEE 802.11 networks","authors":"Chenfei Zhang, L. Lei, Ting Zhang","doi":"10.1109/ComComAp.2014.7017184","DOIUrl":"https://doi.org/10.1109/ComComAp.2014.7017184","url":null,"abstract":"Performance evaluation of IEEE 802.11 multi-hop wireless networks has been drawing significant attention in recent years whereas most studies ignore the interfering noise far away. However, since the packets may overlap in time in multi-hop wireless networks, the cumulative energy of the noise coming from far away can be high enough to affect the performance of the network. In this paper, we investigate the interfering noise in the IEEE 802.11 wireless multi-hop networks. Then, we perform simulations to evaluate the effect of cumulative interfering noise on the performance of IEEE 802.11 DCF protocol. The results show that the transmission probability, collision probability and the saturation throughput of each flow in IEEE 802.11 multi-hop wireless networks have been greatly affected by the cumulative interfering noise.","PeriodicalId":422906,"journal":{"name":"2014 IEEE Computers, Communications and IT Applications Conference","volume":"433 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132592785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/ComComAp.2014.7017172
Jinpeng Chen, Yu Liu, Ming Zou
In this paper, we focus on the problem of estimating users' home locations in the Twitter network. In order to solve the aforementioned problem, we propose a Social Tie Factor Graph Model (STFGM) for estimating a Twitter user's city-level location based on the following network, user-centric data and tie strength. In STFG, relationships between users and locations in social network are modeled as nodes, the attributes and correlations are modeled as factors. An efficient algorithm is proposed to learn model parameters and to predict unknown relationships. We evaluate our proposed method on large Twitter networks. Experimental results demonstrate that our proposed method significantly outperforms several state-of-the-art methods and achieves the best performance.
本文主要研究Twitter网络中用户家的位置估计问题。为了解决上述问题，我们提出了一种基于以下网络、以用户为中心的数据和联系强度的社交联系因素图模型(Social Tie Factor Graph Model, STFGM)来估计Twitter用户的城市级别位置。在STFG中，社交网络中用户和位置之间的关系被建模为节点，属性和相关性被建模为因素。提出了一种有效的模型参数学习和未知关系预测算法。我们在大型Twitter网络上评估了我们提出的方法。实验结果表明，我们提出的方法明显优于几种最先进的方法，并达到了最佳性能。
{"title":"From tie strength to function: Home location estimation in social network","authors":"Jinpeng Chen, Yu Liu, Ming Zou","doi":"10.1109/ComComAp.2014.7017172","DOIUrl":"https://doi.org/10.1109/ComComAp.2014.7017172","url":null,"abstract":"In this paper, we focus on the problem of estimating users' home locations in the Twitter network. In order to solve the aforementioned problem, we propose a Social Tie Factor Graph Model (STFGM) for estimating a Twitter user's city-level location based on the following network, user-centric data and tie strength. In STFG, relationships between users and locations in social network are modeled as nodes, the attributes and correlations are modeled as factors. An efficient algorithm is proposed to learn model parameters and to predict unknown relationships. We evaluate our proposed method on large Twitter networks. Experimental results demonstrate that our proposed method significantly outperforms several state-of-the-art methods and achieves the best performance.","PeriodicalId":422906,"journal":{"name":"2014 IEEE Computers, Communications and IT Applications Conference","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132024231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/ComComAp.2014.7017166
Shanshan Wan, Zhendong Niu
This article addresses how to fulfill ALOA (Adaptive Learning Objects Assembly) which provides users personalized learning resources and learning path based on evolutionary PBIL (Population Based Incremental Learning) algorithm. Both the users' preferences and learning resources' intrinsic characteristics are considered here. And the experience from proficient experts is used to give the LO (Learning Object) difficulty level and important grade which guides the LO's sequencing and selection. The constraints of knowledge such as basic ones, itinerary ones and compulsory ones are also vital factors for ALOA. All of above are modeled as a Constraint Satisfaction Problem (CSP). The PBIL algorithm is proposed and applied to ALOA firstly. The hybrid intelligent evolutionary algorithm is tested on true teaching data and the participants also give the learning feeling. We also obtained the experiment data from the tested data and questionnaire. ALOA's good validity, accuracy, and stability performance are verified.
本文讨论了如何实现ALOA (Adaptive Learning Objects Assembly)， ALOA是一种基于进化PBIL (Population based Incremental Learning)算法为用户提供个性化学习资源和学习路径的方法。这里既考虑了用户的偏好，也考虑了学习资源的内在特征。并利用专家的经验给出学习对象的难度等级和重要等级，指导学习对象的排序和选择。基础知识约束、行程知识约束、义务知识约束等也是影响ALOA的重要因素。所有这些都被建模为约束满足问题(CSP)。首先提出了PBIL算法，并将其应用于ALOA。混合智能进化算法在真实的教学数据上进行了测试，参与者也给出了学习的感觉。我们还从测试数据和问卷中获得了实验数据。验证了ALOA具有良好的效度、准确性和稳定性。
{"title":"Adaptive Learning Objects Assembly with compound constraints","authors":"Shanshan Wan, Zhendong Niu","doi":"10.1109/ComComAp.2014.7017166","DOIUrl":"https://doi.org/10.1109/ComComAp.2014.7017166","url":null,"abstract":"This article addresses how to fulfill ALOA (Adaptive Learning Objects Assembly) which provides users personalized learning resources and learning path based on evolutionary PBIL (Population Based Incremental Learning) algorithm. Both the users' preferences and learning resources' intrinsic characteristics are considered here. And the experience from proficient experts is used to give the LO (Learning Object) difficulty level and important grade which guides the LO's sequencing and selection. The constraints of knowledge such as basic ones, itinerary ones and compulsory ones are also vital factors for ALOA. All of above are modeled as a Constraint Satisfaction Problem (CSP). The PBIL algorithm is proposed and applied to ALOA firstly. The hybrid intelligent evolutionary algorithm is tested on true teaching data and the participants also give the learning feeling. We also obtained the experiment data from the tested data and questionnaire. ALOA's good validity, accuracy, and stability performance are verified.","PeriodicalId":422906,"journal":{"name":"2014 IEEE Computers, Communications and IT Applications Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125660541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/ComComAp.2014.7017180
Xuebin Ma, Zhenchao Ouyang, Lin Bai, Xin Zhan, Xiangyu Bai
A more detailed community structure can contribute to a better understanding of the network, which can also benefit efficient routing protocols and QoS schemes designing. For an Opportunistic Network which consists of different kinds of mobile nodes, its topology changes over time. Therefore the community detection becomes more difficult than static situations. Moreover the overlapping community detection is a more complex problem. This paper analyzes the time varying topology of Opportunistic Networks and the overlapping community structures of human. Then, we propose a new detection algorithm to solve the overlapping community detection problems in Opportunistic Networks. Only with the local network topology information and a short period, nodes can get their overlapping community structures by our detection algorithm. Numerical simulations with both scenarios of movement models and real trace data are presented to illustrate the accuracy and efficiency of our algorithm.
{"title":"An overlapping community detection algorithm for opportunistic networks","authors":"Xuebin Ma, Zhenchao Ouyang, Lin Bai, Xin Zhan, Xiangyu Bai","doi":"10.1109/ComComAp.2014.7017180","DOIUrl":"https://doi.org/10.1109/ComComAp.2014.7017180","url":null,"abstract":"A more detailed community structure can contribute to a better understanding of the network, which can also benefit efficient routing protocols and QoS schemes designing. For an Opportunistic Network which consists of different kinds of mobile nodes, its topology changes over time. Therefore the community detection becomes more difficult than static situations. Moreover the overlapping community detection is a more complex problem. This paper analyzes the time varying topology of Opportunistic Networks and the overlapping community structures of human. Then, we propose a new detection algorithm to solve the overlapping community detection problems in Opportunistic Networks. Only with the local network topology information and a short period, nodes can get their overlapping community structures by our detection algorithm. Numerical simulations with both scenarios of movement models and real trace data are presented to illustrate the accuracy and efficiency of our algorithm.","PeriodicalId":422906,"journal":{"name":"2014 IEEE Computers, Communications and IT Applications Conference","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126208075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-10-01DOI: 10.1109/ComComAp.2014.7017194
Li Xu, Guozhen Tan, Xia Zhang
Network Virtualization paves the way for sharing the physical infrastructure with many service providers and enables resources in physical substrate network being applied and provisioned as a form of Virtual Network(VN). However, there exist many obstacles in applications of this technology. The problem of VN embedding is commonly considered the most difficult one of them. Most existing research only considers the case of how to embed VN request. Provided user demands on Virtual Network are dynamically changing, how to efficiently reconfigure VN to adapt to changing demand is challenging also. In this paper, our objective is to find way for optimally reorganize VN that already embedded on VN in a cost sensitive way to meet the changed demand. We address this problem by proposing a cost sensitive VN reconfiguration approach. A heuristic VN reconfiguration algorithm with virtual node and virtual link migration and swapping strategy is designed. We validate and evaluate the given algorithms by conducting experiments in high fidelity emulation environment. Our evaluation results show that the proposed approach can effectively reconfigure VN while minimizing cost and fragmentation of resource. By comparing our algorithms with others, the given reconfiguration algorithm outperforms existing solutions.
{"title":"A cost sensitive approach for Virtual Network reconfiguration","authors":"Li Xu, Guozhen Tan, Xia Zhang","doi":"10.1109/ComComAp.2014.7017194","DOIUrl":"https://doi.org/10.1109/ComComAp.2014.7017194","url":null,"abstract":"Network Virtualization paves the way for sharing the physical infrastructure with many service providers and enables resources in physical substrate network being applied and provisioned as a form of Virtual Network(VN). However, there exist many obstacles in applications of this technology. The problem of VN embedding is commonly considered the most difficult one of them. Most existing research only considers the case of how to embed VN request. Provided user demands on Virtual Network are dynamically changing, how to efficiently reconfigure VN to adapt to changing demand is challenging also. In this paper, our objective is to find way for optimally reorganize VN that already embedded on VN in a cost sensitive way to meet the changed demand. We address this problem by proposing a cost sensitive VN reconfiguration approach. A heuristic VN reconfiguration algorithm with virtual node and virtual link migration and swapping strategy is designed. We validate and evaluate the given algorithms by conducting experiments in high fidelity emulation environment. Our evaluation results show that the proposed approach can effectively reconfigure VN while minimizing cost and fragmentation of resource. By comparing our algorithms with others, the given reconfiguration algorithm outperforms existing solutions.","PeriodicalId":422906,"journal":{"name":"2014 IEEE Computers, Communications and IT Applications Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115147572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：