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ABSTRACT Tag-based Social Interest Discovery
"... The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to co ..."
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The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to connect people with common interests and encourages people to contribute and share more contents. The main challenge to solving this problem comes from the difficulty of detecting and representing the interest of the users. The existing approaches are all based on the online connections of users and so unable to identify the common interest of users who have no online connections. In this paper, we propose a novel social interest discovery approach based on user-generated tags. Our approach is motivated by the key observation that in a social network, human users tend to use descriptive tags to annotate the contents that they are interested in. Our analysis on a large amount of real-world traces reveals that in general, user-generated tags are consistent with the web content they are attached to, while more concise and closer to the understanding and judgments of human users about the content. Thus, patterns of frequent co-occurrences of user tags can be used to characterize and capture topics of user interests. We have developed an Internet Social Interest Discovery system, ISID, to discover the common user interests and cluster users and their saved URLs by different interest topics. Our evaluation shows that ISID can effectively cluster similar documents by interest topics and discover user communities with common interests no matter if they have any online connections.
LightFlood: Minimizing Redundant Messages and Maximizing the Scope of Peer-to-Peer Search
"... Abstract—Flooding is a fundamental file search operation in unstructured peer-to-peer (P2P) file sharing systems, in which a peer starts the file search procedure by broadcasting a query to its neighbors, who continue to propagate it to their neighbors. This procedure repeats until a time-to-live (T ..."
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Abstract—Flooding is a fundamental file search operation in unstructured peer-to-peer (P2P) file sharing systems, in which a peer starts the file search procedure by broadcasting a query to its neighbors, who continue to propagate it to their neighbors. This procedure repeats until a time-to-live (TTL) counter is decremented to 0. Flooding can seriously limit system scalability, because the number of redundant query messages grows exponentially during the message propagation. Our study shows that more than 70 percent of the generated messages are redundant in a flooding with a TTL of 7 in a moderately connected Gnutella network. Existing efforts to address this issue have been focused on limiting the use of the flooding operation. We propose a new flooding scheme, called LightFlood, with the objective of minimizing the number of redundant messages and retaining a similar message-propagating scope as that of the standard flooding. In the scheme, each peer keeps track of the connectivities of every immediate and next indirect neighbor peers, which can be acquired locally. LightFlood identifies the neighbor with the highest connectivity and uses the link to that neighbor to form a suboverlay within the existing P2P overlay. In LightFlood, flooding is divided into two stages. The first stage is a standard flooding with a limited number of TTL hops, where a message can spread to a sufficiently large scope with a small number of redundant messages. In the second stage, message propagating is only conducted along the suboverlay, significantly reducing the number of redundant messages. Our analysis and simulation experiments show that the LightFlood scheme provides a low-overhead broadcast facility that can be effectively used in P2P search. For example, compared with standard flooding with seven TTL hops, we show that LightFlood with an additional two to three hops can reduce up to 69 percent
ASAP: an AS-Aware Peer-Relay Protocol for High Quality VoIP
"... Peer-to-peer (P2P) technology has been successfully applied in Internet telephony or Voice over Internet Protocol (VoIP), such as the Skype system, where P2P is used for both searching clients and relaying voice packets. Selecting one or multiple suitable peers to relay voice packets is a critical f ..."
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Peer-to-peer (P2P) technology has been successfully applied in Internet telephony or Voice over Internet Protocol (VoIP), such as the Skype system, where P2P is used for both searching clients and relaying voice packets. Selecting one or multiple suitable peers to relay voice packets is a critical factor for the quality, scalability and cost of a VoIP system. In this paper, we first present two sets of intensive Internet measurement results to confirm the benefits gained by peer relays in VoIP, and to investigate the performance of the Skype system. We obtain the following results: (1) many relay peer selections are suboptimal; (2) the waiting time to select a relay node can be quite long; and (3) there are a large number of unnecessary probes, resulting in heavy network traffic to limit scalability of the VoIP system. Our further analysis shows that two main reasons cause these problems. First, the peer selections do not take Autonomous System (AS) topology into consideration, and second, the complex communication relationships among peers are not well utilized. Motivated by our measurements and analysis, we propose an AS-aware peer-relay protocol called ASAP. Our objective is to significantly improve VoIP quality and system scalability with low overhead. Our intensive evaluation by trace-driven simulation shows ASAP is highly effective and easy to implement on the Internet for building large and scalable VoIP systems.
Robust Super-Peer-Based P2P File-Sharing Systems
, 2009
"... This paper presents an efficient approach for improving file availability in super-peer-based peer-to-peer (P2P) file-sharing systems. In the super-peer-based P2P file-sharing system, peers are organized into multiple groups. In each group, there is a special peer called super-peer to serve the regu ..."
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This paper presents an efficient approach for improving file availability in super-peer-based peer-to-peer (P2P) file-sharing systems. In the super-peer-based P2P file-sharing system, peers are organized into multiple groups. In each group, there is a special peer called super-peer to serve the regular peers within the same group.With this property, the proposed approach utilizes the super-peer to tolerate the departure (failure) of a regular peer in order to protect shared files. Unlike traditional replication-based approaches, the proposed approach keeps track of the file queries in the super-peer to support fault tolerance. The cost of tracking the file queries is much smaller than the cost of replicating the file contents in advance. Furthermore, the proposed approach uses a logical connection technique to consider the departure (failure) of the super-peer. Finally, simulation experiments are performed to quantify the performance and overhead of the proposed approach.
The design and implementation of free . . .
, 2008
"... With the dramatic increase of media traffic on the Internet, existing media systems have shown their inefficiencies in resource utilization and performance bottlenecks on high qual-ity media services. Although the inconsistency between the media access patterns and the Zipf-like distributions of Web ..."
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With the dramatic increase of media traffic on the Internet, existing media systems have shown their inefficiencies in resource utilization and performance bottlenecks on high qual-ity media services. Although the inconsistency between the media access patterns and the Zipf-like distributions of Web workloads has been observed by a number of measurement studies, existing media system designs and evaluations still assume that media workload has the same access pattern as that of conventional Web workload. An insightful understand-ing of media access patterns is essential to guide Internet system design and management, including resource provisioning and performance optimizations. In this Ph.D. dissertation, we analyze the access patterns of Internet media systems and study effective system designs for large scale media content delivery. With exten-sive measurements on the Internet, we find current media systems tend to over-supply or over-utilize server hardware and network bandwidth to provide high quality media service, which is not a scalable and effective approach for serving the explosively increasing media traffic on the Internet. We then systematically study the access patterns of different kinds
Adaptively Routing P2P Queries Using Association Analysis
"... Unstructured peer-to-peer networks have become a very popular method for content distribution in the past few years. By not enforcing strict rules on the network’s topology or content location, such networks can be created quickly and easily. Unfortunately, because of the unstructured nature of thes ..."
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Unstructured peer-to-peer networks have become a very popular method for content distribution in the past few years. By not enforcing strict rules on the network’s topology or content location, such networks can be created quickly and easily. Unfortunately, because of the unstructured nature of these networks, in order to find content, query messages are flooded to nodes in the network, which results in a large amount of traffic. This work borrows the technique of association analysis from the data mining community and extends it to intelligently forward queries through the network. Because only a small subset of a node’s neighbors are forwarded queries, the number of times those queries are propagated is also reduced, which results in considerably less network traffic. These savings
Contents lists available at ScienceDirect Journal of Network and Computer Applications
"... journal homepage: www.elsevier.com/locate/jnca Reducing query overhead through route learning in unstructured ..."
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journal homepage: www.elsevier.com/locate/jnca Reducing query overhead through route learning in unstructured
WWW 2008 / Refereed Track: Social Networks & Web 2.0- Discovery and Evolution of Communities Tag-based Social Interest Discovery
"... The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to co ..."
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The success and popularity of social network systems, such as del.icio.us, Facebook, MySpace, and YouTube, have generated many interesting and challenging problems to the research community. Among others, discovering social interests shared by groups of users is very important because it helps to connect people with common interests and encourages people to contribute and share more contents. The main challenge to solving this problem comes from the difficulty of detecting and representing the interest of the users. The existing approaches are all based on the online connections of users and so unable to identify the common interest of users who have no online connections. In this paper, we propose a novel social interest discovery approach based on user-generated tags. Our approach
Commentary-based Video Categorization and Concept Discovery
"... Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are ex-amples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search video ..."
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Social network contents are not limited to text but also multimedia. Dailymotion, YouTube, and MySpace are ex-amples of successful sites which allow users to share videos among themselves. Due to the huge amount of videos, grouping videos with similar contents together can help users to search videos more efficiently. Unlike the tradi-tional approach to group videos into some predefined cat-egories, we propose a novel comment-based matrix factor-ization technique to categorize videos and generate concept words to facilitate searching and indexing. Since the cate-gorization is learnt from users feedback, it can accurately represent the user sentiment on the videos. Experiments conducted by using empirical data collected from YouTube shows the effectiveness of our proposed methodologies. 1
