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
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.
62553301
Efficient resource discovery in self-organized unstructured peer-to-peer networks
In unstructured peer-to-peer (P2P) networks, two autonomous peer nodes can be connected if users in those nodes are interested in each other's data. Owing to the similarity between P2P networks and social networks, where peer nodes can be regarded as people and connections can be regarded as relationships, social strategies are useful for improving the performance of resource discovery by self-organizing autonomous peers on unstructured P2P networks. In this paper, we present an efficient social-like peer-to-peer (ESLP) method for resource discovery by mimicking different human behaviours in social networks. ESLP has been simulated in a dynamic environment with a growing number of peer nodes. From the simulation results and analysis, ESLP achieved better performance than current methods. Copyright © 2008 John Wiley & Sons, Ltd.
13426917
Dependable Dynamic Service Integration on Service-Oriented Peer-to-Peer Networks
For provision of dependable search and rescue capability in dynamic and unpredictable disaster areas, the networked nodes should have the ability to autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly configure any services available on the disaster area to deliver a real-time capability. In this paper, we present an innovative architectural approach which is able to proactively self-diagnose and self-adapt evolution occurring in provision of search and rescue capabilities in service-oriented P2P (ServP2P) networks. This architecture provides flexibility and agility in handling dynamic changes and evolution encountered in the delivery of rescue capability. The experimental results indicate that the proposed approach provides a high-level of reliability and sustainability to achieve dependable service integration for capability provision.
2746167
Modelling and simulation of Network Enabled Capability on service-oriented architecture
Network Enabled Capability (NEC) is the UK 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 this paper, we present our research work in the NECTISE project with a focus on the modelling and simulation of service-oriented architecture (SOA) for delivering dependable and sustainable military capability. The simulation results indicate that the proposed architectural model can provide a high-level of reliability and sustainability in the provision of capability in a dynamic environment. Moreover, a NEC demonstration system for regional surveillance is introduced in this paper to illustrate the use of SOA to achieve NEC.
3090205
Challenges for End-to-End Quality of Service in Heterogeneous Networks
To guarantee the end-to-end QoS (E2E Quality of Service) in heterogeneous network is an important issue to provide pervasive and trusted service. Currently, the different networks are optimized for different services, but it becomes urgent to provide pervasive service across different networks. This paper gives an overview on how to design a dynamic and integrated QoS architecture under heterogeneous networks. This paper firstly analyzes the actuality of the E2E quality of service in heterogeneous networks, and then discusses the requirements of the E2E QoS of two types of heterogeneous networks, finally points out the five key issues to solve the practical problem in the current network.
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.
3041039
The Impacts of Enterprise Resource Planning Systems on Firm Performance: An Empirical Analysis of Chinese Chemical Firms
Chinese firms heavily invest in enterprise resource planning systems (ERP) in recent years and expect that ERP can help them gain superior financial performance. Given the high costs and high risk of ERP investments, to quantify the financial benefits of ERP implementation is an important research issue. This paper empirically examines the impacts of ERP implementation on firm performance using the financial data from 50 Chinese chemical firms that implemented ERP. The firms’ abnormal performance during the two-year implementation period and three-year post-implementation period was analyzed based on the guideline of Barber et al. on event studies. The results find no significant performance improvement during the implementation period and the three-year post-implementation period and a decline in performance in the first two years after implementation. However, a slight performance improvement in the third year after implementation may indicate that the financial benefits of ERP may show after a long-term ERP use. These results provide insight for Chinese firms that want to invest in ERP.
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.
34356811
Reduce Feature Based NN for Transient Stability Analysis of Large-Scale Power Systems
Aiming at the existence of relativity between repeat or similar samples and character parameters during diagnosis of character data, this paper presents an effective data analysis approach for character data compression from bi-direction, which can reduce the burden of learning machine without losing the connotative character knowledge of character data. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity measurement of principle component core for vertical reduction by using related mechanism of clone selection as well as immune network self-stabilization in organism natural immune system for reference. Finally, to analyze machine behavior quantitatively, a pattern discrimination model based on a cerebellar model articulation controller neural network ( NN ) was developed. Simulation experiments proved the effectiveness of this algorithm.