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Kademlia is one of the most popular routing algorithm based on DHT in P2P network research. It specifies the structure of the network and the exchange of information through node lookups. With the unique identifying pattern of nodes which kademlia adopts and XOR metric for distance, it contacts only O(log(n)) nodes during the search out of the total of n nodes in the system. The neighboring nodes in the network based on Kademlia are not always physical neighbours so that the delay between nodes is affected. In this paper, we put forward to a new model of Kademlia based on physical information. It re-construct the Kademlia model reasonably with the idea of making the nodes which are closed in physical network approach in the network in the logic topology. As a result, it will lower routing delay. We describes the structure and its query routing algorithm. Our query routing strategies are proved effective in our case studies mentioned in this paper.

The P2P data integration system aims to combine the advantages of P2P technologies and data integration to overcome centralized data integration systems' shortcomings. Kademlia, as a widely used and efficient network protocol for P2P files sharing system, has a very clear logical structure, and with its unique identifying pattern of nodes and XOR metric for distance, it can provide O(logn) lookup to locate the node closest to a given key. In this paper, we put forward a method of applying Kademlia to the P2P data integration system, and propose a new P2P data integration model, Dual-Kad, combing the Kademlia network over the Peer layer with that over the Super-Peer layer. Dual-Kad can process queries based on semantic logic which is a limitation of the original Kademlia, and shorten the query routing path, cache the query results, and as a result, speed the whole query routing. We describe the detailed structures of Dual-Kad and its query routing algorithms. Our query routing strategies are proved effective in our case studies mentioned in this paper.

With the flourish of the Web, online review is become a more and more useful and important information resource for people. As a result, automatic review mining has become a hot research topic recently. Traditional review mining based on feature extracts product feature and opinion word independently, and seldom considers their association information. In this paper, we only focus on Chinese product review. We propose a method based on Chinese dependency grammar to extract feature-opinion word pairs. Specifically, we use Chinese dependency grammar to set several rules, then we make use of these rules to extract candidate feature-opinion word pairs. Finally, we filter out mismatched feature-opinion words pairs by feature ranking and Named Entity Recognition (NER) system. Experiment shows that our method in Precision is rather high.

The labeling problem of dynamic XML documents has been a hot search topic. In this paper, we propose a new labeling scheme LSVP. Each node is assigned a unique vector label which supports the representation of the ancestor-descendant relationships and sibling relationships between nodes. One floating-point corresponds to a vector based on Polar coordinate system (while two in Cartesian coordinates). Meanwhile, the problem of floating-point is resolved in our scheme. Hence, LSVP can completely avoid re-labeling and its memory cost is low.

Along with the development of grid computing and cloud computing, finite computing resources supplied by stand-alone server usually become the bottleneck in the process of system implementation of online trading platform. Moreover, It is difficult to reuse algorithm module and the system also becomes more complicated to achieve. Traditional online trading framework can not preferably solve the problem listed above. Thus, we propose a framework of online trading platform based on cloud computing. It is feasible to establish a high-complexity online trading platform using infinite virtual computing capability provided by cloud computing. Simultaneously, this framework can realize the sharing of data sets after the integration of heterogeneous and distributed data based on layered thoughtway, and supply theoretical foundation and framework support for setting up a unified, open, distributed, and parallel online trading platform.

Considering the characteristic of heterogeneous wireless sensor networks, the clustering algorithm based on data content for heterogeneous sensor network is proposed. In cluster construction stage, according to the various sensor node types in CADC algorithm, the same types of nodes is divided into the same cluster and different types of nodes can not be divided into the same cluster. In the cluster heads selection scheme, nodes with the most residual energy will be elected cluster heads first. Cluster heads with the same type further integrat into the secondary cluster. Because this algorithm makes the data aggregation to be the most optimal and reduces the transmission distance of cluster heads, it can prolong the lifetime of the whole networks.

Grids provide a uniform interface to a collection of heterogeneous, geographically distributed resources. In recent years, the research on the Grid Monitoring System gets increasingly essential and significant. In this paper we put forward a novel Mobile Agent-based Grid Monitoring Architecture (MA-GMA), which is based on the GMA from GGF and introduces the mobile agents and cache mechanism of MDS. Based on the Open Grid Service Architecture (OGSA) standard, we merge the intelligence and mobility characteristic of mobile agent into the current OGSA to constructing a dynamic and extensible monitoring system. In the end, we do some experiments under different environments. As the results shown, this MA-GMA is proved to be effective and improve the monitoring performance greatly.

Grid based computational infrastructure is a promising next generation computing platform for solving large-scale resources- intensive problems. With the developing Grid technologies and applications, the research on the Grid monitoring system gets increasingly essential and significant. As far as the present research are concerned, there exist two mainly technologies in grid performance monitoring: MDS (monitoring and directory service) and GMA(Grid Monitoring Architecture). In this paper the author puts forward a novel Mobile Agent-based Grid Monitoring Architecture (MA-GMA), which introduces the mobile agents and cache mechanism of MDS. Based on the Open Grid Service Architecture (OGSA) standard, we merge the characteristics of intelligence and mobility of mobile agent into the current OGSA to construct a dynamic and extensible monitoring system. In the end, we do some experiments under different environments. From the results of experiments shown, this MA-GMA is proved to be effective and improves the monitoring performance greatly.