12342025
Reputation management and signature delegation: A distributed approach
In this paper, we present a novel protocol, called Distributed Signcryption with Verifiable Partial Signature (DiSigncryption) protocol, to allow an agent owner to securely distribute his signing capability among a set of trusted third party hosts (TTP-hosts) via a mobile agent. The protocol incorporates three schemes: a novel Distributed Reputation Management scheme, a modified version of the Distributed Signcryption method proposed in [23], and an extended version of the Agent-based Threshold Proxy Signcryption (ATPS) protocol proposed in [2]. The security properties of the proposed protocol are analyzed, and the protocol is compared with the most related work.
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.
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.
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.
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
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.
5773205
Auction-Based Pricing Model for Web Service Providers
Applying auctions to Web services selection and invocation calls for examination due to the unique features of Web services, such as interoperable machine-to machine interactions and re-enterable bargaining services. In this paper, we propose a formal model for Web services-based auctions. Examining a one sided sealed auction type, we prove mathematically that service requestorsâ€™ risk preferences could lead to different pricing strategies for service providers towards higher profit. We argue that Service Level Agreement (SLA) documents can be used to analyze service requestorsâ€™ preferences. On top of WS Agreement, we propose a basic service requestor risk preference elicitation algorithm, as well as a historical data-based service requestor risk preference prediction model. Guidelines are provided to iteratively approach the learning rate of the proposed risk preference prediction model. The methods and techniques presented in this paper can be reused to investigate and examine more facades of services-oriented auctions towards establishing a new research realm on comprehensive services-oriented auctions.
62212730
Distributed supercomputing to achieve real-time representation and manipulation of complex scenes
Abstract Besides the ray tracing technique, the radiosity method is another major approach for global illumination modeling in the field of computer graphics. Since this method needs a huge amount of storage space (both memory and disk) and a long pre-computation cycle, it is not suitable to implement it on conventional workstations. Supercomputers seem to be necessary for such kind of graphics applications. However, some problems appear with the integration of supercomputers and workstations in a distributed computing environment, especially for graphics application. The major problems are: (i) unavailability of standard higher-level mechanisms for building distributed application; (ii) transparent access to supercomputers without remote login or file transfer sessions; (iii) computation balance to make the best use of the performance of supercomputers and workstations; (iv) data transfer/storage strategy between supercomputers and workstations; and (v) conflict between interaction and response time for graphics applications. In this paper we suggest solutions to the above mentioned problems based on the remote procedure call (RPC) and the client/server model, for the radiosity package implementation. After the introduction of the radiosity method, we concentrate on the integration between supercomputers and high-performance workstations. We also convey some general issues related to distributed computing and present the experience with our implementation, such as the application protocol definition, error recovery, code debugging etc. The radiosity package has been implemented at ZGDV in Darmstadt, F.R.G. in a network environment including a Multiflow TRACE 7/300 supercomputer connected to several VAX, SUN and HP workstations.
46032361
ERPDB: An Integrated Database of ERP Data for Neuroinformatics Research
Event-related potential (ERP) is the measurement of the brain's electrical activity in response to different types of events, such as attention, words, thinking, or sounds. By measuring the brain's response to such events, we can learn how different types of information are processed. As the mass of recorded ERP data explodes, an automatic and accurate tool to store, manage, and retrieve data readily is of increasing concern in neuroinformatics. In this paper, we describe a relational ERP database that has been constructed using the SQL server 2000 database management system and an IIS web server that has been setup for data retrieval through a custom web interface (http://202.113.232.103:8088/erpdb/index.asp). A novel database structure has been used to store ERP data of different activity channels, which provides a rapid and accurate way for data retrieval within any given range on the time zone with various searching options. The database is divided into: (1) subjects' information and record information and (2) ERP data, which has been structured and standardized in a database table supplemented with unrestricted text files. It can integrate or exchange data with other clinical databases or computer-based information systems through a program based on ADO techniques. Users are able to readily retrieve ERP data through the user-friendly web page interface. All online resources of the database are freely available to the scientific community. As the database develops further, we anticipate it will become a valuable tool that will make a great contribution to everyday clinical practice, teaching, and research work inneuroscience and psychology in the future.
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.