5885917
Managing peer-to-peer networks with human tactics in social interactions
Abstract
Small-world phenomena have been observed in existing peer-to-peer (P2P) networks which has proved useful in the design of P2P file-sharing systems. Most studies of constructing small world behaviours on P2P are based on the concept of clustering peer nodes into groups, communities or clusters. However, managing additional multilayer topology increases maintenance overhead, especially in highly dynamic environments. In this paper, we present Social-like P2P systems (Social-P2Ps) for object discovery by self-managing P2P topology with human tactics in social networks. In Social-P2Ps, queries are routed intelligently even with limited cached knowledge and node connections. Unlike community-based P2P file-sharing systems, we do not intend to create and maintain peer groups or communities consciously. In contrast, each node connects to other peer nodes with the same interests spontaneously by the result of daily searches.

16471179
Small World Architecture for Peer-to-Peer Networks
Small-world phenomenon has been observed in existing peer-to-peer (P2P) networks, such as Gnutella and Freenet. Due to the similarity of P2P networks to social networks, the previous small-world model proposed by Duncan Watts can be adopted in the design of P2P networks: each node is connected to some neighbouring nodes, and a group of nodes keep a small number of long links to randomly chosen distant nodes. Unfortunately, current unstructured search algorithms have difficulty distinguishing these random long-range shortcuts. This paper presents small world architecture for P2P networks (SWAN) with a semi-structured P2P search algorithm that is used to create and find long-range shortcuts toward remote peer groups. In SWAN, not every peer node needs to be connected to remote groups, but every peer node can easily find which peer nodes have external connections to a specific peer group
17142920
Service-Oriented Integration of Systems for Military Capability
Service oriented architecture (SOA) is becoming established in computing as a means to integrate processing and data across organisations. This paper proposes that system-level integration can benefit from service oriented architectural descriptions and loose coupling between the problem domain requirements and different system solutions. The problem domain is exemplified as military capability, from the UK Ministry of Defence (MoD), in particular, network enabled capability (NEC). Representations of military capability in the problem domain can be described in terms of processes. The processes are sequences of functions that can be described as services. Then different types of system solutions can implement the described services. Firstly, the paper presents an overview of conceptual SOA and in the context of military capability compares three levels of service integration: business services, systems services and computing services. Secondly, the paper presents a framework for evaluating the performance and effectiveness of service integration to compare different solutions in delivering military capability.
16432148
Delivering Sustainable Capability on Evolutionary Service-oriented Architecture
Network Enabled Capability (NEC) is the U.K. Ministry of Defence’s response to the quickly changing conflict environment in which its forces must operate. In NEC, systems need to be integrated in context, to assist in human activity and provide dependable inter-operation. In order to provide reliable and sustainable military capability, fast paced changes must be conducted without halting the operation of a capability. In this paper we present the concept of evolutionary service-oriented architecture for delivering sustainable capability. The reliability of the architecture is evaluated by simulations using a computer-based model. The simulation results indicate that the evolutionary service-oriented architecture can provide higher reliability and sustainability in the provision of capability in a dynamic environment.
6983198
Investigation of Research towards Efficient Social Peer-to-Peer Networks
Peer-to-peer (P2P) networks attract attentions worldwide with their great success in file sharing networks (e.g. Napster, Gnutella, BitTorrent, and Kazaa). In the last decade, numerous studies have been devoted to the problem of resource discovery in P2P networks. However, efficient resource discovery remains a key challenge for large-scale P2P networks. An investigation of existing research on resource discovery towards efficient social P2P networks will be given in this paper.
8904843
Social Peer-to-Peer for Resource Discovery
For resource discovery in social networks, people can directly contact some acquaintances that have knowledge about the resources they are looking for. However, in current peer-to-peer networks, peer nodes lack capabilities similar to social networks, making it difficult to route queries efficiently. In this paper, we present a social-like system (Social-P2P) for resource discovery by mimicking human behaviours in social networks. Different from most informed search algorithms, peer nodes learn knowledge from the results of previous searches and no additional overhead is required to obtain extra information from neighbouring nodes. Unlike community-based P2P information sharing systems, we do not intend to create and maintain peer groups or communities consciously. Peer nodes with the same interests will be highly connected to each other spontaneously. Social-P2P has been simulated in a dynamic environment. From the simulation results and analysis, Social-P2P achieved better performance than current methods
14971936
Does Familiarity Breed Content? Taking Account of Familiarity with a Topic in Personalizing Information Retrieval
We report on an evaluation of the effectiveness of considering a user's familiarity with a topic in improving information retrieval performance. This approach to personalization is based on previous results indicating differences in user search behavior and judgments according to his/her familiarity to the topic explored, and to research on using implicit sources of evidence to determine the user's context and preferences. Our attempt was to relate a topic-dependent concept and measure, familiarity with the topic, with topic-independent measures of documents such as readability, concreteness/abstractness, and specificity/generality. Contrary to our expectations, a user’s familiarity with a topic has no effect on the utility of readability or concrete/abstract scoring. We are encouraged, however, to find that high readability had a positive effect on search results, regardless of a user’s familiarity with a topic.
11138089
Research on System Architecture and Interfaces in Heterogeneous Network Platform
The paper proposes an architecture for heterogeneous network platform based on adaptation layer according to service capability requirements and characteristics of modern service industry. In order to shield the diversity of heterogeneous networks to provide open interfaces in the adaptation layer, an abstract method of service capability is proposed to get a set of SCF components and sub-platforms. The basic service capabilities can be also integrated to generate new services by the service integration method. Some interfaces and service applications illustrate that the abstract method and interfaces are reasonably effective on the platform for the applications of modern service industry.
17430531
Interactive Separation of Segmented Bones in CT Volumes Using Graph Cut
We present a fast, interactive method for separating bones that have been collectively segmented from a CT volume. Given user-provided seed points, the method computes the separation as a multi-way cut on a weighted graph constructed from the binary, segmented volume. By properly designing and weighting the graph, we show that the resulting cut can accurately be placed at bone-interfaces using only a small number of seed points even when the data is noisy. The method has been implemented with an interactive graphical interface, and used to separate the 12 human foot bones in 10 CT volumes. The interactive tool produced compatible result with a ground-truth separation, generated by a completely manual labelling procedure, while reducing the human interaction time from a mean of 2.4 hours per volume in manual labelling down to approximately 18 minutes.
694781
A Decentralized Resource Discovery Based on Keywords Combinations and Node Clusters in Knowledge Grid
The organization and discovery of grid resources are foundational and key subjects in grid research. Many research works in this field have presented the solutions to the problem, but few of them are focused on knowledge resources. This paper aims to explore how to support user's knowledge requests submitted in form of multi-keywords. We present a decentralized resource discovery method based on keyword combinations and node clusters. In the method, hot keyword combinations are formed based on user's knowledge requests. Then, grid nodes can be clustered according to these keyword combinations and user's knowledge requests will be transmitted to those clusters that have high correlations with the requests.
36508955
Parameter convergence and minimal internal model with an adaptive output regulation problem
The parameter convergence of nonlinear adaptive control systems is an important yet not well addressed issue. In this paper, using the global robust output regulation problem of output feedback systems with unknown exosystems as a platform, we will show that the well known persistency of excitation (PE) condition still guarantees the convergence of the estimated parameter vector to the true parameter vector. Moreover, the PE condition will be satisfied if the internal model is minimal in certain sense.