A peer-to-peer （P2P） network is a distributed application architecture which provides many attractive features, such as availability, self-organization, load-balancing, and anonymity. However, P2P network has create...A peer-to-peer （P2P） network is a distributed application architecture which provides many attractive features, such as availability, self-organization, load-balancing, and anonymity. However, P2P network has created significant problems to network operators by generating large volumes of inter autonomous system （inter-AS） traffic. Focusing on the BitTorrent swarming protocol, this paper proposes an approach which aims to reduce P2P generated inter-AS traffic. In particular, the approach can reduce inter-AS traffic by 50% to 70%. Moreover, it can improve the downloading speed by 60% for the popular torrents. The evaluation shows that controlled regional-based contents replication can effectively achieve this goal. Furthermore, the approach is incrementally deployable. Network regions in which the system gets deployed can solve their P2P generated inter-AS traffic problems autonomously, i.e., without any Internet service providers-collaboration and any requirement, the system can be deployed in the entire Internet.展开更多
Correction to:Virologica Sinica https://doi.org/10.1007/s12250-021-00448-x Due to our oversight,the author list of reference“Promchan K.Natarajan V.Kanzaki M(2020)Leucine zipper transcription factor-like I binds adap...Correction to:Virologica Sinica https://doi.org/10.1007/s12250-021-00448-x Due to our oversight,the author list of reference“Promchan K.Natarajan V.Kanzaki M(2020)Leucine zipper transcription factor-like I binds adaptor protein complex-1 and 2 and participates in trafficking of transfcirin receptor 1.PLoS One 15:e0226298”was incorrectly displayed.展开更多
The impact of a Distributed Denial of Service(DDoS)attack on Soft-ware Defined Networks(SDN)is briefly analyzed.Many approaches to detecting DDoS attacks exist,varying on the feature being considered and the method us...The impact of a Distributed Denial of Service(DDoS)attack on Soft-ware Defined Networks(SDN)is briefly analyzed.Many approaches to detecting DDoS attacks exist,varying on the feature being considered and the method used.Still,the methods have a deficiency in the performance of detecting DDoS attacks and mitigating them.To improve the performance of SDN,an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model(RMCARTAM)is sketched in this article.The RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming packets.The model is designed with multiple controllers to handle net-work traffic but can turn the controllers according to requirements.The multi-con-straint adaptive replication model monitors different features of network traffic like rate of packet reception,class-based packet reception and target-specific reception.According to these features,the method estimates the Replication Turn-ing Weight(RTW)based on which triggering controllers are performed.Similarly,the method applies Traffic Approximation(TA)in the detection of DDoS attacks.The detection of a DDoS attack is performed by approximating the incoming traf-fic to any service and using various features like hop count,payload,service fre-quency,and malformed frequency to compute various support measures on bandwidth access,data support,frequency support,malformed support,route sup-port,and so on.Using all these support measures,the method computes the value of legitimate weight to conclude the behavior of any source in identifying the mal-icious node.Identified node details are used in the mitigation of DDoS attacks.The method stimulates the network performance by reducing the power factor by switching the controller according to different factors,which also reduces the cost.In the same way,the proposed model improves the accuracy of detecting DDoS attacks by estimating the features of incoming traffic in different corners.展开更多
As users increasingly befriend others and interact online via their social media accounts,online social networks (OSNs)are expanding rapidly.Confronted with the big data generated by users,it is imperative that data s...As users increasingly befriend others and interact online via their social media accounts,online social networks (OSNs)are expanding rapidly.Confronted with the big data generated by users,it is imperative that data storage be distributed,scalable,and cost-efficient.Yet one of the most significant challenges about this topic is determining how to minimize the cost without deteriorating system performance.Although many storage systems use the distributed key value store,it cannot be directly applied to OSN storage systems.And because users'data are highly correlated,hash storage leads to frequent inter-server communications,and the high inter-server traffic costs decrease the OSN storage system's scalability. Previous studies proposed conducting network partitioning and data replication based on social graphs.However,data replication increases storage costs and impacts traffic costs.Here,we consider how to minimize costs from the perspective of data storage,by combining partitioning and replication.Our cost-efficient data storage approach supports scalable OSN storage systems.The proposed approach co-locates frequently interactive users together by conducting partitioning and replication simultaneously while meeting load-balancing constraints.Extensive experiments are undertaken on two real- world traces,and the results show that our approach achieves lower cost compared with state-of-the-art approaches.Thus we conclude that our approach enables economic and scalable OSN data storage.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 61001084
文摘A peer-to-peer （P2P） network is a distributed application architecture which provides many attractive features, such as availability, self-organization, load-balancing, and anonymity. However, P2P network has created significant problems to network operators by generating large volumes of inter autonomous system （inter-AS） traffic. Focusing on the BitTorrent swarming protocol, this paper proposes an approach which aims to reduce P2P generated inter-AS traffic. In particular, the approach can reduce inter-AS traffic by 50% to 70%. Moreover, it can improve the downloading speed by 60% for the popular torrents. The evaluation shows that controlled regional-based contents replication can effectively achieve this goal. Furthermore, the approach is incrementally deployable. Network regions in which the system gets deployed can solve their P2P generated inter-AS traffic problems autonomously, i.e., without any Internet service providers-collaboration and any requirement, the system can be deployed in the entire Internet.
文摘Correction to:Virologica Sinica https://doi.org/10.1007/s12250-021-00448-x Due to our oversight,the author list of reference“Promchan K.Natarajan V.Kanzaki M(2020)Leucine zipper transcription factor-like I binds adaptor protein complex-1 and 2 and participates in trafficking of transfcirin receptor 1.PLoS One 15:e0226298”was incorrectly displayed.
文摘The impact of a Distributed Denial of Service(DDoS)attack on Soft-ware Defined Networks(SDN)is briefly analyzed.Many approaches to detecting DDoS attacks exist,varying on the feature being considered and the method used.Still,the methods have a deficiency in the performance of detecting DDoS attacks and mitigating them.To improve the performance of SDN,an efficient Real-time Multi-Constrained Adaptive Replication and Traffic Approximation Model(RMCARTAM)is sketched in this article.The RMCARTAM considers different parameters or constraints in running different controllers responsible for handling incoming packets.The model is designed with multiple controllers to handle net-work traffic but can turn the controllers according to requirements.The multi-con-straint adaptive replication model monitors different features of network traffic like rate of packet reception,class-based packet reception and target-specific reception.According to these features,the method estimates the Replication Turn-ing Weight(RTW)based on which triggering controllers are performed.Similarly,the method applies Traffic Approximation(TA)in the detection of DDoS attacks.The detection of a DDoS attack is performed by approximating the incoming traf-fic to any service and using various features like hop count,payload,service fre-quency,and malformed frequency to compute various support measures on bandwidth access,data support,frequency support,malformed support,route sup-port,and so on.Using all these support measures,the method computes the value of legitimate weight to conclude the behavior of any source in identifying the mal-icious node.Identified node details are used in the mitigation of DDoS attacks.The method stimulates the network performance by reducing the power factor by switching the controller according to different factors,which also reduces the cost.In the same way,the proposed model improves the accuracy of detecting DDoS attacks by estimating the features of incoming traffic in different corners.
基金the National Natural Science Foundation of China under Grant Nos.61502328,61672370,and 61572337the Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No.1701173B+1 种基金the Open Project Program of Jiangsu Provincial Key Laboratory for Computer Information Processing Technology under Graut No.KJS1740the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No.18KJA520009.
文摘As users increasingly befriend others and interact online via their social media accounts,online social networks (OSNs)are expanding rapidly.Confronted with the big data generated by users,it is imperative that data storage be distributed,scalable,and cost-efficient.Yet one of the most significant challenges about this topic is determining how to minimize the cost without deteriorating system performance.Although many storage systems use the distributed key value store,it cannot be directly applied to OSN storage systems.And because users'data are highly correlated,hash storage leads to frequent inter-server communications,and the high inter-server traffic costs decrease the OSN storage system's scalability. Previous studies proposed conducting network partitioning and data replication based on social graphs.However,data replication increases storage costs and impacts traffic costs.Here,we consider how to minimize costs from the perspective of data storage,by combining partitioning and replication.Our cost-efficient data storage approach supports scalable OSN storage systems.The proposed approach co-locates frequently interactive users together by conducting partitioning and replication simultaneously while meeting load-balancing constraints.Extensive experiments are undertaken on two real- world traces,and the results show that our approach achieves lower cost compared with state-of-the-art approaches.Thus we conclude that our approach enables economic and scalable OSN data storage.
