23696811
A distributed reputation management scheme for mobile agent based e-commerce applications
This paper examines current approaches used in reputation management and defines five basic metrics for the evaluation of reputation of trusted third party (TTP) hosts employed in mobile agent-based e-commerce applications. By taking these metrics into account, a new distributed reputation management scheme is proposed for quantifying and managing the reputation of the TTP-hosts based on a transaction-based feedback system. The scheme exhibits several interesting features not seen in previous work: firstly, it offers better efficiency and robustness for an application that employs it, and secondly, it credits/penalizes a TTP-host according to its transactional behavior, the transaction value and the reputation of the source of feedback. In this way, TTP-hosts may be deterred from misbehaving.
1884872
A mobility monitoring based advance reservation protocol
Future wireless cellular networks will be Internet Protocol (IP) based. Users of wireless devices in these networks will expect to run real-time applications that require guarantees of Quality of Service (QoS). Such a user will expect the same seamless QoS that he would receive if he were running real-time applications on a wired network. Achieving seamless QoS in a mobile environment implies that a reservation should be re-established at the new Base Station (BS) before hand-over occurs. However, making these advance reservations is wasteful of valuable bandwidth in the wireless network. This paper proposes a protocol, called the Mobility Monitoring Based Advance Reservation Protocol (M²BARP), which aims to reduce the bandwidth overhead of making advance reservations. The protocol makes use of information about a Mobile Node's (MN) mobility to make a single advance reservation when the MN is about to hand-over. Unlike previous work, M²BARP takes advantage of overlapping cells to help to provide a more seamless QoS by reducing the number of calls dropped at hand-over
14935404
Levels of Authentication Assurance: an Investigation
The ES-LoA project, funded by the UK Joint Information Systems Committee (JISC) under its e- Infrastructure Security Programme, investigates current and future needs among UK research and education community for a more fine-grained authorisation scheme that would allow service providers to take into account of the levels of confidence in identifying a remote entity requesting for service access. Such a fine-grained authorisation scheme is attractive to service providers offering resources with varying levels of sensitivity and/or wishing to tailor their security protections based upon risk levels. Service providers may wish to restrict access to more sensitive resources only to those who have gone through a more stringent authentication process, or given the same remote entity, require the use of a stronger authentication token should the access request come from a more risky environment. In this way, the quality of an authentication instance, expressed as an authentication Level of Assurance (LoA), becomes one of the parameters used in access control decision making. This paper investigates the current worldwide efforts in defining LoA and identifies gaps in existing definitions when they are applied to a federated environment.
1660866
A General Fuzzified CMAC Controller with Eligibility
This paper presents an online neural network controller. Cerebellar Model Articulation Controller (CMAC) is suitable to online control due to its fast learning speed. By integrating the CMAC address scheme with fuzzy logic concept, a general fuzzified CMAC (GFAC) is proposed. Then by incorporating the concept of eligibility into the GFAC, a GFAC controller with eligibility is presented, named FACE. A learning algorithm for the FACE is derived to tune the model parameters. To achieve online control, an efficient implementation of the proposed FACE method is presented. As an example, the proposed FACE is applied to a ship steering control system. The simulation results show that the ship course can be properly controlled under the disturbances of wave, wind and current.
42027884
New Approximation for Minimum-Weight Routing Backbone in Wireless Sensor Network
Our problem formulation is as follows. Given a weighted disk graph Gwhere the weight of edge represents the transmission energy consumption, we wish to determine a dominating tree Tof Gsuch that the total weight of edges in Tis minimized. To the best of our knowledge, this problem have not been addressed in the literature. Solving the dominating tree problem can yield a routing backbone for broadcast protocols since: (1) each node does not have to construct their own broadcast tree, (2) utilize the virtual backbone to reduce the message overhead, and (3) the weight of backbone is minimized. 
 
Our contributions to this problem is multi-fold: First, the paper is the first to study this problem, prove the hardness of this problem and propose an approximation framework. Second, we present a heuristic to approximate the solution with low time complexity. Third, a distributed algorithm is provided for practical implementation. Finally, we verify the effectiveness of our proposal through simulation.
13044783
A New Time-domain Detection Approach with Blind Separation Based on Neural Network
In this paper a new technique is proposed for time-domain detection in energy detection. The proposed scheme is based on a independent-component analysis (ICA): blind separation of unknown source signals. This method not only improves the nicety of time-domain detection for narrow band signal and the sinusoidal signal but also reduces the power of the whole detection system.
10586032
A tag recommendation system for folksonomy
Social bookmarking tools become more and more popular nowadays and tagging is used to organize information and allow users to recall or search the resources. Users need to type the tags whenever they post a resource, so that a good tag recommendation system can ease the process of finding some useful and relevant keywords for users. Researchers have made lots of relevant work for tag recommendation systems, but those traditional collaborative systems may not perform well in the case of a new user and a new resource.
 To address this problem, we propose a tag recommendation system for two different cases. The first case is that the active user or active resource is a new one which has not appeared in the past while the second case is that the active user and resource has already been posted. In this paper, we present two different methods for these two cases: a content-based method and a graph-based method. We implement our tag recommendation system in a realworld academic Folksonomy system. In order to gain better results,we apply improvements and combinations of previous work in each of these two methods.and combinations of previous work in each of these two methods. We participated into the Discovery Challenge 2009 with the proposed methods. The results of our teams are within the top teams.
11505780
InterJoin: Exploiting Indexes and Materialized Views in XPath Evaluation
XML has become the standard for data exchange for a wide variety of applications, particularly in the scientific community. In order to efficiently process queries on XML representations of scientific data, we require specialized techniques for evaluating XPath expressions. Exploiting materialized views in query processing significantly enhances query processing performance. We propose a novel view definition that allows for intermediate (structural) join results to be stored and reused in XML query evaluation. Unlike current XML view proposals, our views do not require navigation in the original document or path-based pattern matching. Hence, they are evaluated significantly faster and are easily costed as part of a query plan. In general, current structural joins cannot exploit views efficiently when the view definition is not a prefix (or a suffix) of the XPath query. To increase the applicability of our proposed view definition, we propose a novel physical structural join operator called InterJoin. The InterJoin operator allows for joining interleaving XPath expressions, e.g., joining //A//C with //B to evaluate //A//B//C. InterJoin allows for more join alternatives in XML query plans. We propose several physical implementations for InterJoin, including a technique to exploit spatial indexes on the inputs. We give analytic cost models for the implementations so they can be costed in an existing XML query optimizer. Experiments on real and synthetic XML data show significant speed-ups of up to 200% using InterJoin, and speed-ups of up to 400% using our materialized views
8279850
Analysis and Simulation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network
In this paper a novel multipriority reservation protocols for plastic optical fiber network is proposed. In conventional OCDMA system only allows finite units to transmit and access simultaneously according to the number of channels which be restricted by BER. To resolve this problem, a novel protocol based on slotted ALOHA is proposed in this paper. By using the reservation scheme and a distributed arbitration algorithm, channel collision and destination conflict can be avoided. The protocol can efficiently support the transmission of multimedia messages that require the different time-delay. The network throughput and average delay has been investigated by numerical analysis and simulation experiments. It is showed that the multipriority reservation protocol in this POF network is valid and efficient.
2697231
Lossless compression of color mosaic images
We present a low complexity algorithm for lossless compression of color mosaic images generated by a Bayer CCD color filter array. This algorithm is based on an interesting use of the integer wavelet transform followed by a fast adaptive context-based Golomb-Rice coding. The lossless compression performance of the proposed algorithm is apparently the best reported in the literature so far for color mosaic images.
10680010
Automatic sports genre categorization and view-type classification over large-scale dataset
This paper presents a framework with two automatic tasks targeting large-scale and low quality sports video archives collected from online video streams. The framework is based on the bag of visual-words model using speeded-up robust features (SURF). The first task is sports genre categorization based on hierarchical structure. Following on the second task which is based on automatically obtained genre, views are classified using support vector machines (SVMs). As a consequence, the views classification result can be used in video parsing and highlight extraction. As compared with state-of-the-art methods, our approach is fully automatic as well as domain knowledge free and thus provides a better extensibility. Furthermore, our dataset consists of 14 sport genres with 6850 minutes in total. Both sport genre categorization and view type classification have more than 80% accuracy rates, which validate this framework's robustness and potential in web-based applications.