26994753
Efficient Scheduling for Reducing Load in the IMS Presence Service
6719824
Performance modeling of multicast groups for multiplayer games in peer-to-peer networks
A computer game is usually considered as a finite state machine. For a distributed multiplayer game, state information has to be exchanged among its players when they move and interact in a virtual space. If the number of players is very large, only a small subset of the game entities, controlled by their players, is interested and forms a multicast group so as to reduce the information dissemination over the network. In this paper, analytical models are proposed for evaluating the performance of multicast groups with multiplayer games in peer-to-peer networks. The system modeling is based on two stochastic processes and their possible solutions in terms of game type, player activity, and entity vision size, mode of user input processing, and grouping strategy. The cost of game operations on consumed resources is introduced to characterize the performance measure. Numerical examples are demonstrated, which provide useful insights of the behaviors of such systems.
9180158
Protocol Design of MPEG-4 Media Delivery with Active Networks
Traditionally, the Internet supports best effort service. The quality of service available to real time applications such as the delivery of video and audio is therefore difficult to predict and control. Two new technologies have emerged recently, namely the MPEG-4 standard and active network, for media data compression and data networking, respectively. MPEG-4 uses a content or object-based representation. It supports object-based scalability and, in particular, it allows the modification or editing of objects without having to first decode them. Active network allows program code to be loaded dynamically into network nodes. In this paper, we describe a system for real-time media delivery that exploits the strengths of MPEG-4 media encoding and active networks. It is based on a best-effort transport service. Our system performs congestion avoidance, error concealment, and media scalability.
17480069
Similarity-based Web service matchmaking
With the increasing growth in popularity of Web services, matchmaking of relevant Web services becomes a significant challenge. Commonly, Web service is described by WSDL and published on UDDI registers. UDDI provides limited search facilities allowing only a keyword-based search of businesses, services, and the so called tModels based on names and identifiers. This category-based keyword-browsing method is clearly insufficient. Semantic Web service uses DAML-S instead of WSDL to represent capabilities of Web services. This improvement enables software agents or search engines to automatically find appropriate Web services via ontologies and reasoning algorithm enriched methods. However, the high cost of formally defining to the heavy and complicated services makes this improvement widespread adoption unlikely. To cope with these limitations, we have developed a suite of methods which assesses the similarity of Web services to achieve matchmaking. In particular, we present a conceptual model which classifies properties of Web services into four categories. For each category, a similarity assessment method has been given. In Web service matchmaking process, these similarity assessment methods can be used together or individually. Experiments highlight complementary contributions that our work makes to facilitate Web service matchmaking.
15933707
Automatic extraction of web search interfaces for interface schema integration
This paper provides an overview of a technique for extracting information from the Web search interfaces of e-commerce search engines that is useful for supporting automatic search interface integration. In particular, we discuss how to group elements and labels on a search interface into attributes and how to derive certain meta-information for each attribute.
19018721
Estimating Size of Search Engines in an Uncooperative Environment
The number of documents that are indexed by a search engine is referred to as the size of the search engine. The information about the size of each underlying search engine is essential for any metasearch engine to conduct search engine selection, result merging and a few other processes. Thus, effectively estimating the size of search engines is important for a metasearch engine that incorporates multiple autonomous search engines. In this paper, we propose an algorithm that achieves better accuracy compared to the other existing methods for estimating the size of search engines, without losing efficiency. Compared to the Sample-Resample approach, which is the best-known approach in literature, our technique also shows much better tolerance to unfavorable environments.
16923777
Identifying redundant search engines in a very large scale metasearch engine context
For a given set of search engines, a search engine is redundant if its searchable contents can be found from other search engines in this set. In this paper, we propose a method to identify redundant search engines in a very large-scale metasearch engine context. The general problem is equivalent to an NP hard problem -- the set-covering problem. Due to the large number of search engines that need to be considered and the large sizes of these search engines, approximate solutions must be developed. In this paper, we propose a general methodology to tackle this problem and within the context of this methodology, we propose several new heuristic algorithms for solving the set-covering problem.
1209241
Spectral Energy Minimization for Semi-supervised Learning
Data mining problems often involve a large amount of unlabeled data and there is often very limited known information on the dataset. In such scenario, semi-supervised learning can often improve classification performance by utilizing unlabeled data for learning. In this paper, we proposed a novel approach to semi-supervised learning as as an optimization of both the classification energy and cluster compactness energy in the unlabeled dataset. The resulting integer programming problem is relaxed by a semi-definite relaxation where efficient solution can be obtained. Furthermore, the spectral graph methods provide improved energy minimization via the incorporation of additional criteria. Results on UCI datasets show promising results.