Reusing ontology mappings for query routing in semantic peer-to-peer environment

To efficiently support automated interoperability between ontology-based information systems in distributed environments, the semantic heterogeneity problem has to be dealt with. To do so, traditional approaches have acquired and employed explicit mappings between the corresponding ontologies. Usually these mappings can be only obtained from human domain experts. However, it is too expensive and time-consuming to collect all possible mapping results on distributed information systems. More seriously, as the number of systems in a large-scale peer-to-peer (P2P) network increases, the efficiency of the ontology mapping is exponentially decreased. Thereby, in this paper, we propose a novel semantic P2P system, which is capable of (i) sharing and exchanging existing mappings among peers, and (ii) composing shared mappings to build a certain path between two systems. Given two arbitrary peers (i.e., source and destination), the proposed system can provide indirect ontology mappings to make them interoperable. In particular, we have focused on query-based communication for evaluating the proposed ontology mapping composition system. Once direct ontology mappings are collected from candidate peers, a given query can be (i) segmented into a set of sub-queries, and (ii) transformed to another query. With respect to the precision performance, our experimentation has shown an improvement of about 42.5% compared to the keyword-based query searching method.     

Dynamic quorums for DHT-based enterprise infrastructures

Peer-to-peer systems (P2P) have become a popular technique to design large-scale distributed applications in unmanaged inter-domain settings, such as file sharing or chat systems, thanks to their capabilities to self-organize and evenly split the load among peers. Recently, enterprises owning a large IT hardware and software infrastructure started looking at these P2P technologies as a means both to reduce costs and to help their technical divisions to manage huge number of devices characterized by a high level of cooperation and a relatively low churn. Gaining a quick exclusive access to the system for maintenance or auditing purposes in these enterprise infrastructures is a fundamental operation to be implemented. Conversely, this kind of operation is usually not an issue in the previously mentioned inter-domain setting, where peers are inherently independent and cannot be managed.     

A DHT-based fast handover mobile identifier/locator management scheme for separation networks

Several researches propose the identifier/locator separation architecture to tackle the scMing prob- lems of today＇s Internet routing and addressing system. And scalable and seamless mobility support is an important task in mobile identifier/locator separation networks. In this paper, by analyzing the features, such as direct separation, flexible mapping and identifier replacement, we show that the new architecture delivers data packets more efficiently and protects location privacy better than traditional mobile IP networks, and is able to implement soft handover conveniently. Then we present a distributed Hash table （DHT） based fast handover management （DFHM） scheme for the new architecture, which improves the reactive handover mode of FMIPv6 and eliminates the duplicate address detection （DAD） and return routability （RR） processes in MIPv6. And we propose a generic analysis framework for handover management. Further, we demonstrate the validity of our framework by simulation and quantificationMly study the effects of network scale and movement velocity. The results show that DFHM has good scalability and low handover latency, and has great advantages in the signaling cost and fast mobility support.     

L-overlay: A layered data management scheme for peer-to-peer computing

Efficient storage and handling of data stored in a peer-to-peer (P2P) network, proves vital for various applications such as query processing and data mining. This paper presents a distributed, scalable and robust layered overlay (L-overlay) to index and manage multidimensional data in a dynamic P2P network. The proposed method distinguishes between the data and peer layers, with efficient mapping between the two. The data is organized such that semantically similar data objects are accessed hastily. Grid and tree structures are proposed for the peer layer. As application examples of L-overlay in query processing and data mining, k-nearest neighbors query processing and distributed Naïve Bayes classification algorithms, are proposed. We show the effectiveness of our scheme in static and dynamic environments using simulation. L-overlay is shown to be more efficient than SSW, an available semantic overly, in terms of maintenance and query processing costs.     

A DHT-based fast handover management scheme for mobile identifier/locator separation networks

Several researches propose the identifer/locator separation architecture to tackle the scaling problems of today’s Internet routing and addressing system.And scalable and seamless mobility support is an important task in mobile identifer/locator separation networks.In this paper,by analyzing the features,such as direct separation,flexible mapping and identifer replacement,we show that the new architecture delivers data packets more efciently and protects location privacy better than traditional mobile IP networks,and is able to implement soft handover conveniently.Then we present a distributed Hash table(DHT)based fast handover management(DFHM)scheme for the new architecture,which improves the reactive handover mode of FMIPv6 and eliminates the duplicate address detection(DAD)and return routability(RR)processes in MIPv6.And we propose a generic analysis framework for handover management.Further,we demonstrate the validity of our framework by simulation and quantifcationally study the efects of network scale and movement velocity.The results show that DFHM has good scalability and low handover latency,and has great advantages in the signaling cost and fast mobility support.     

Sparse structures for searching and broadcasting algorithms over internet graphs and peer-to-peer computing systems

In a broadcasting problem, a message is sent from a source to all the other nodes in the network. Blind flooding is a classical mechanism for broadcasting, where each node retransmits received message to all its neighbors. Despite its important advantages, an increase in the number of requests or the network size or density produces communication overheads that limit the scalability of blind flooding, especially in networks with dynamic topologies. Theoretically optimal solution is based on minimal spanning trees (MST), but its construction is expensive. We discuss here protocols based on local knowledge and newly proposed sparse structures. In weighted RNG (Relative Neighborhood Graph), messages are forwarded only on links which are not the ‘longest’ in any triangle. In weighted RNGQ, messages are forwarded to links which are not the longest in any triangle or quadrangle. Each node constructs weighted MST based on its 2-hop knowledge. Weighted LMST (Localized LMST) preserves only edges that are selected by both endpoints, and messages are forwarded on these links. Any available metric, such as delay, reliability, reputation etc. can be used as weight. Analysis and simulation show that weighted RNG performs better than existing Flooding and Rumor Mongering (or Gossip) schemes. The parameterless weighted LMST, MST, RNG and RNGQ (RNG over Quadrangle) based broadcasting schemes are compared, showing overall advantage for LMST. We also hint that a number of existing protocols can be simplified by applying concept from this article.     

Emergent standard of knowledge management: Hybrid peer-to-peer knowledge management

Knowledge has been a critical resource for supporting business strategies. The major obstacle to classical knowledge management approach is that knowledge workers hesitate to release their own control and give up sharing autonomy. The peer-to-peer architecture facilitates achieving autonomy and self-organized management. However, there are still some problems, such as computational efficiency, organizational memory accumulation. This study proposes a hybrid peer-to-peer architecture to consider the tradeoff between centralized and decentralized knowledge management. The proposed architecture preserves the autonomy of knowledge workers as well as allows the accumulation of organizational memory. It also encourages workers to issue on-line discussions to add knowledge annotations. Under this architecture, a scenario of collaborative product design is described.     

A conceptual model for data management and distribution in peer-to-peer systems

While Peer-to-Peer (P2P) model gains significant attention in distributed computing, it is also expected to be a powerful model for information sharing. P2P systems are expected to provide exhaustive reliable computational resources and scalable accessibility. The data management and distribution in such systems requires storage, replication, data modeling, indexing, querying, retrieval, streaming, and topology management. While a lot of data management strategies have been proposed through the last years, these strategies have not been investigated with respect to a common model for P2P systems. However, since the services provided by the P2P systems are so diverse, it is very challenging to come up with a common layer-based model for all P2P systems. In this paper, we firstly propose a conceptual model for P2P systems, and then provide a classification and summary of data management and distribution strategies by referring to this model. The horizontal layers of the model correspond to modules of a P2P system whereas the columns are related to the services provided. The modules include base P2P service, storage, indexing, logical, service, and application modules. The services include security, querying, publish, join/leave, collaboration, and streaming. The paper concludes by providing a comprehensive list of data management and distribution strategies used in the existing P2P systems.     

基于DHT的分布式网络负载均衡研究

为了解决基于DHT(分布式哈希表)的分布式网络中单个节点负载过热的问题,提出了一种具有良好扩展性的负载均衡解决方案.在该方案中,单个节点自主完成负载平衡的操作,保证负载过重的情况不会发生.分析和实验结果表明,该方案在消除Chord DHT网络单个节点负载过热问题的同时,还拥有节点自我负载平衡和实现成本不受系统规模影响的特点和优势,因此具有良好的实用性和研究参考价值.     

Development of a distributed collaborative design framework within peer-to-peer environment

Distributed collaborative design and manufacture enables manufacturing organizations to maintain competitiveness in the fiercely competitive global industry. This requires that the distributed system not only maintains data consistency across globally-distributed locations seamlessly, but also allows team members to access the storage system and computing resources transparently and securely. Current grid applications mainly based on client-server architecture are inflexible and rigid for fast changing collaborations among manufacturers, especially for small and medium enterprises. In this paper, a distributed collaborative design framework is presented with a hybrid of grid and peer-to-peer technology. In order to access computational resources for design, analysis and process simulation, a meta-scheduler is designed and implemented. It helps in resource discovery and optimal utilization of resources. A test bed is established, based on the framework proposed to demonstrate a distributed collaborative design and manufacturing environment.     

Concurrent algorithms for real-time memory management

The conflict between the performance demands of real-time systems and the shared-resource needs of high-level languages (Ada in particular) is examined. Shared memory requires carefully designed concurrency control, but the traditional approach, which is to embed the entire allocate-release implementation code in critical sections, is unsuitable for real-time applications because it results in excessively high response time. The design and performance of three memory-management systems for real-time applications are evaluated, and it is shown that one system, an optimized optimistic version, does deliver performance that is acceptable for real-time applications     

Data management issues in mobile and peer-to-peer environments

Mobile computing is a revolutionary technology, born as a result of remarkable advance in the development of computer hardware and wireless communication. It enables us to access information anytime and anywhere even in the absence of physical network connection. More recently, there has been increasing interest in introducing ad hoc network into mobile computing, resulting in a new distributed computing style known as peer-to-peer (P2P) computing. In this paper, we discuss the data management issues in mobile and P2P environments. The use of wireless communication makes the data availability the most important problem here, so we focus on the problem of data availability and provide detailed discussion about replicating mobile databases. Not only that, we extend our discussion to mobile–P2P environment. At the end, we discuss the general data management issues in P2P environment.     

Software environment for simulating algorithms for image analysis and processing

We consider the purpose, functionality, configuration, and structure of a software environment designed for simulation and investigation of methods, algorithms, and information technology for digital images analysis and processing. Mikhail V. Gashnikov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the chair of earth information of the SSAU. Scientific interests: image processing, compression, statistical coding. Author of more than 30 publications, including 12 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Evgenii V. Myasnikov. Born 1981. Graduated from the Samara State Airspace University in 2004. He is now a post-graduate student at the Chair of Earth Information of the Samara State Airspace University. Scientific interests: development of software systems, image processing, image retrieval in databases. Author of 6 publications, including one paper. Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the Chair of Earth Information of the SSAU and a research fellow at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, geoinformation systems. Author of more than 50 publications, including 11 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai I. Glumov. Born 1962. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1985. Received candidate’s degree in Technology in 1994. He is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition, compression of images, simulation of systems of digital image formation. Author of more than 50 publications, including 21 papers and one monographs (in coauthorsip). Member of the Russian Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1974. Received doctoral degree in Technology in 1993. Head of the Laboratory of Mathematical Methods for Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, earth information. Author of more than 150 publications, including approximately 40 papers and two monographs (in coauthorship). President of the Povolzh’e Branch of the Russian Association for Pattern Recognition and Image Analysis. Corresponding member of the Russian Ecological Academy and of the Russian Academy of Engineering Sciences. Member of the International Society for Optical Engineering. A laureate of the Samara Provincial Government prize in science and engineering. Marina A. Chicheva. Born 1964. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1987. Received candidate’s degree in Technology in 1998. She is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image recognition, compression, fast algorithms for discrete transformations. Author of more than 40 publications, including 15 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis.     

VectorTrust: trust vector aggregation scheme for trust management in peer-to-peer networks

With emerging Internet-scale open content and resource sharing, social networks, and complex cyber-physical systems, trust issues become prominent. Conventional trust mechanisms are inadequate at addressing trust issues in decentralized open environments. In this paper, we propose a trust vector based trust management scheme called VectorTrust for aggregation of distributed trust scores. Leveraging a Bellman–Ford based algorithm for fast and lightweight trust score aggregation, VectorTrust features localized and distributed concurrent communication. Built on a trust overlay network in a peer-to-peer network, a VectorTrust-enabled system is decentralized by nature and does not rely on any centralized server or centralized trust aggregation. We design, implement, and analyze trust rating, trust aggregation, and trust management strategies. To evaluate the performance, we design and implement a VectorTrust simulator (VTSim) in an unstructured P2P network. The analysis and simulation results demonstrate the efficiency, accuracy, scalability, and robustness of VectorTrust scheme. On average, VectorTrust converges faster and involves less complexity than most existing trust schemes. VectorTrust remains robust and tolerant to malicious peers and malicious behaviors. With dynamic growth of P2P network scales and topology complexities, VectorTrust scales well with reasonable overheads (about O(lg?N) communication overheads) and fast convergence speed (about O(log? _D N) iterations).     

GCF-RT——一种P2P环境下的实时协同框架的原型实现

实时协同应用是指程序同程序以分布式的方式同步合作完成某项工作。分析了引入P2P技术后实时协同应用的特点,提出了一个泛型的实时应用框架的解决方案GCF-RT,利用框架技术为用户提供一个半成品化的开发原型,阐述了该原型中应用依赖接口、核心引擎和通信组件等部分的具体设计与实现,解决了实时协同应用中的一致性、实时性、动态性以及容错等问题。介绍了GCF-RT的应用实例,印证了GCF-RT的功能完备性和有效性。     

Participant selection algorithms for large-scale mobile crowd sensing environment

Microsystem Technologies - Mobile crowd sensing (MCS) is an emerging sensing platform that concedes mobile users to efficiently collect data and share information with the MCS service providers....     

无线传感器网络信誉管理机制

无线传感器网络信誉管理作为保护网络安全、提高网络可用性的一种手段,被广泛应用在生产生活中。介绍了传统的无线传感器网络信誉管理机制,在其基础上加以改进,提出加入能量因素和环境误差因素,以提高无线传感器信誉值测量的准确性。