41392373
Small-World Peer-to-Peer for Resource Discovery
Small-world phenomenon is potentially useful to improve the performance of resource discovery in decentralized peer-to-peer (P2P) networks. The theory of small-world networks can be adopted in the design of P2P networks: each peer node is connected to some neighbouring nodes, and a group of peer nodes keep a small number of long links to randomly chosen distant peer nodes. However, current unstructured search algorithms have difficulty distinguishing among these random long-range shortcuts and efficiently finding a set of proper long-range links located in itself or its local group for a specific resource search. This paper presents a semi-structured P2P model to efficiently create and find long-range shortcuts toward remote peer groups.
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.
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
7638849
Efficient and scalable search on scale-free P2P networks
Unstructured peer-to-peer (P2P) systems (e.g. Gnutella) are characterized by uneven distributions of node connectivity and file sharing. The existence of “hub” nodes that have a large number of connections and “generous” nodes that share many files significantly influences performance of information search over P2P file-sharing networks. In this paper, we present a novel Scalable Peer-to-Peer Search (SP2PS) method with low maintenance overhead for resource discovery in scale-free P2P networks. Different from existing search methods which employ one heuristic to direct searches, SP2PS achieves better performance by considering both of the number of shared files and the connectivity of each neighbouring node. SP2PS enables peer nodes to forward queries to the neighbours that are more likely to have the requested files and also can help in finding the requested files in the future hops. The proposed method has been simulated in different power-law networks with different forwarding degrees and distances. From our analytic and simulation results, SP2PS achieves better performance when compared to other related methods.
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.
42190506
Three-objective fuzzy chance-constrained programming model for multiproject and multi-item investment combination
This paper presents a new fuzzy chance-constrained programming model to find the solution for multiproject and multi-item investment combination in investment combination problems. The proposed 0-1 integer programming model has three objectives with fuzzy constraints, and NSGA-II is applied to solve the optimization model with a small modification of the constraint-handling rule. A simulation experiment illustrating the application of the proposed model is presented and Pareto-optimal solutions are obtained through a modified NSGA-II algorithm. A comparison among NSGA-II, PSO, and DE shows that modified NSGA-II has some advantages over PSO and DE.
10474493
Calculation of intermodulation distortion in CMOS transconductance stage
The linearity of the transconductance stage is of major concern in the design of some analog circuits. In this paper, Volterra series expansion is used to compute the intermodulation distortion of high frequency CMOS transconductance stage with source degeneration resistor. The MOS model used in this paper includes short-channel effects and gate-source capacitance, gate-drain capacitance, and output resistance of the MOS transistor. Analytical results are compared with simulation results and the influences of circuit parameters on circuit linearity are discussed.
14622249
Knowledge Inventory Management Using Actuarial Method
Knowledge inventory management is nowadays central issue as knowledge management becomes vital for organizations. Knowledge inventory management involves acquiring, retaining, deploying, idling, and abandoning technologies. Managers must make investment decisions about which technologies should be involved into inventory for future usage. Options-pricing model (OPM) has been widely accepted to make investment decisions. An alternative technology is regarded as an option to switch technologies to deal with future contingencies. This paper studies another kind of knowledge inventory problem which OPM is sort of inefficient to deal with. An organization might be forced to invest in some technology in the future because of some specific incident occurs, thus option is replaced by obligation. The characteristics of this kind of problem are portrayed and we show why OPM is not applicable. We treat the specific incident as an insurance accident to organizations and initial investment in some technology as insurance fee which can cover the loss when accident occurs. We use actuarial model to analyze the problem and give the evaluation methods in different conditions.
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.
6333240
Web video topic discovery and tracking via bipartite graph reinforcement model
Automatic topic discovery and tracking on web-shared videos can greatly benefit both web service providers and end users. Most of current solutions of topic detection and tracking were done on news and cannot be directly applied on web videos, because the semantic information of web videos is much less than that of news videos. In this paper, we propose a bipartite graph model to address this issue. The bipartite graph represents the correlation between web videos and their keywords, and automatic topic discovery is achieved through two steps - coarse topic filtering and fine topic re-ranking. First, a weight-updating co-clustering algorithm is employed to filter out topic candidates at a coarse level. Then the videos on each topic are re-ranked by analyzing the link structures of the corresponding bipartite graph. After the topics are discovered, the interesting ones can also be tracked over a period of time using the same bipartite graph model. The key is to propagate the relevant scores and keywords from the videos of interests to other relevant ones through the bipartite graph links. Experimental results on real web videos from YouKu, a YouTube counterpart in China, demonstrate the effectiveness of the proposed methods. We report very promising results.