In Delay Tolerant Networks （DTNs）, the offiine users can, through the encountering nodes, use the specific peer-to-peer message routing approach to deliver messages to the destination. Thus, it solves the problem th...In Delay Tolerant Networks （DTNs）, the offiine users can, through the encountering nodes, use the specific peer-to-peer message routing approach to deliver messages to the destination. Thus, it solves the problem that users have the demands to deliver messages while they are temporarily not able to connect to the Internet. Therefore, by the characteristics of DTNs, people who are not online can still query some location based information, with the help of users using the same service in the nearby area. In this paper, we proposed a location-based content search approach. Based on the concept of three-tier area and hybrid node types, we presented four strategies to solve the query problem, namely, Data Replication, Query Replication, Data Reply, and Data Synchronization strategies. Especially we proposed a Message Queue Selection algorithm for message transferring. The priority concept is set associated with every message such that the most ＂important＂ one could be sent first. In this way, it can increase the query success ratio and reduce the query delay time. Finally, we evaluated our approach, and compared with other routing schemes. The simulation results showed that our proposed approach had better query efficiency and shorter delay.展开更多
Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviati...Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviation with actual rank for the existence of unknown web traffic, which cannot be identified accurately under current techniques. In this paper, we introduce a novel method to approximate the actual rank. This method associates unknown web traffic with websites according to statistical probabilities. Then, we construct a probabilistic top-k query model to rank websites. We conduct several experiments by using real HTTP traffic traces collected from a commercial ISP covering an entire city in northern China. Experimental results show that the proposed techniques can reduce the deviation existing between the ground truth and the ranking results vastly. In addition, we find that the websites providing video service have higher ratio of unknown IP as well as higher ratio of unknown traffic than the websites providing text web page service. Specifically, we find that the top-3 video websites have more than 90% of unknown web traffic. All these findings are helpful for ISPs understanding network status and deploying Content Distributed Network(CDN).展开更多
In this paper, we present a quantum-key-distribution(QKD)-based quantum private query(QPQ) protocol utilizing single-photon signal of multiple optical pulses. It maintains the advantages of the QKD-based QPQ, i.e., ea...In this paper, we present a quantum-key-distribution(QKD)-based quantum private query(QPQ) protocol utilizing single-photon signal of multiple optical pulses. It maintains the advantages of the QKD-based QPQ, i.e., easy to implement and loss tolerant. In addition, different from the situations in the previous QKD-based QPQ protocols, in our protocol, the number of the items an honest user will obtain is always one and the failure probability is always zero. This characteristic not only improves the stability(in the sense that, ignoring the noise and the attack, the protocol would always succeed), but also benefits the privacy of the database(since the database will no more reveal additional secrets to the honest users). Furthermore, for the user's privacy, the proposed protocol is cheat sensitive, and for security of the database, we obtain an upper bound for the leaked information of the database in theory.展开更多
With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the sing...With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the single concept image retrieval, which has limited practical usability. In practice, users always employ an Internet image retrieval system with multi-concept queries, but, the related existing approaches are often ineffective because the only combination of single-concept query techniques is adopted. At present semantic concept based multi-concept image retrieval is becoming an urgent issue to be solved. In this paper, a novel Multi-Concept image Retrieval Model(MCRM) based on the multi-concept detector is proposed, which takes a multi-concept as a whole and directly learns each multi-concept from the rearranged multi-concept training set. After the corresponding retrieval algorithm is presented, and the log-likelihood function of predictions is maximized by the gradient descent approach. Besides, semantic correlations among single-concepts and multiconcepts are employed to improve the retrieval performance, in which the semantic correlation probability is estimated with three correlation measures, and the visual evidence is expressed by Bayes theorem, estimated by Support Vector Machine(SVM). Experimental results on Corel and IAPR data sets show that the approach outperforms the state-of-the-arts. Furthermore, the model is beneficial for multi-concept retrieval and difficult retrieval with few relevant images.展开更多
文摘In Delay Tolerant Networks （DTNs）, the offiine users can, through the encountering nodes, use the specific peer-to-peer message routing approach to deliver messages to the destination. Thus, it solves the problem that users have the demands to deliver messages while they are temporarily not able to connect to the Internet. Therefore, by the characteristics of DTNs, people who are not online can still query some location based information, with the help of users using the same service in the nearby area. In this paper, we proposed a location-based content search approach. Based on the concept of three-tier area and hybrid node types, we presented four strategies to solve the query problem, namely, Data Replication, Query Replication, Data Reply, and Data Synchronization strategies. Especially we proposed a Message Queue Selection algorithm for message transferring. The priority concept is set associated with every message such that the most ＂important＂ one could be sent first. In this way, it can increase the query success ratio and reduce the query delay time. Finally, we evaluated our approach, and compared with other routing schemes. The simulation results showed that our proposed approach had better query efficiency and shorter delay.
基金supported by 111 Project of China under Grant No.B08004
文摘Top-k ranking of websites according to traffic volume is important for Internet Service Providers(ISPs) to understand network status and optimize network resources. However, the ranking result always has a big deviation with actual rank for the existence of unknown web traffic, which cannot be identified accurately under current techniques. In this paper, we introduce a novel method to approximate the actual rank. This method associates unknown web traffic with websites according to statistical probabilities. Then, we construct a probabilistic top-k query model to rank websites. We conduct several experiments by using real HTTP traffic traces collected from a commercial ISP covering an entire city in northern China. Experimental results show that the proposed techniques can reduce the deviation existing between the ground truth and the ranking results vastly. In addition, we find that the websites providing video service have higher ratio of unknown IP as well as higher ratio of unknown traffic than the websites providing text web page service. Specifically, we find that the top-3 video websites have more than 90% of unknown web traffic. All these findings are helpful for ISPs understanding network status and deploying Content Distributed Network(CDN).
基金supported by the National Natural Science Foundation of China(Grant Nos.61272057 and 61170270)Beijing Higher Education Young Elite Teacher Project(Grant Nos.YETP0475 and YETP0477)Beijing University of Posts and Telecommunications Excellent Ph.D.Students Foundation(Grant No.CX201442)
文摘In this paper, we present a quantum-key-distribution(QKD)-based quantum private query(QPQ) protocol utilizing single-photon signal of multiple optical pulses. It maintains the advantages of the QKD-based QPQ, i.e., easy to implement and loss tolerant. In addition, different from the situations in the previous QKD-based QPQ protocols, in our protocol, the number of the items an honest user will obtain is always one and the failure probability is always zero. This characteristic not only improves the stability(in the sense that, ignoring the noise and the attack, the protocol would always succeed), but also benefits the privacy of the database(since the database will no more reveal additional secrets to the honest users). Furthermore, for the user's privacy, the proposed protocol is cheat sensitive, and for security of the database, we obtain an upper bound for the leaked information of the database in theory.
基金supported by National Natural Science Foundation of China(Grant Nos.6137022961370178+4 种基金61272067)National Key Technology R&D Program(Grant No.2013BAH72B01)MOE-China Mobile Research Fund(Grant No.MCM20130651)the Natural Science Foundation of GDP(Grant No.S2013010015178)Science-Technology Project of GDED(Grant No.2012KJCX0037)
文摘With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the single concept image retrieval, which has limited practical usability. In practice, users always employ an Internet image retrieval system with multi-concept queries, but, the related existing approaches are often ineffective because the only combination of single-concept query techniques is adopted. At present semantic concept based multi-concept image retrieval is becoming an urgent issue to be solved. In this paper, a novel Multi-Concept image Retrieval Model(MCRM) based on the multi-concept detector is proposed, which takes a multi-concept as a whole and directly learns each multi-concept from the rearranged multi-concept training set. After the corresponding retrieval algorithm is presented, and the log-likelihood function of predictions is maximized by the gradient descent approach. Besides, semantic correlations among single-concepts and multiconcepts are employed to improve the retrieval performance, in which the semantic correlation probability is estimated with three correlation measures, and the visual evidence is expressed by Bayes theorem, estimated by Support Vector Machine(SVM). Experimental results on Corel and IAPR data sets show that the approach outperforms the state-of-the-arts. Furthermore, the model is beneficial for multi-concept retrieval and difficult retrieval with few relevant images.
