An Efficient Service Discovery Method and its Application

2013 ◽  
pp. 382-404
Author(s):  
Shuiguang Deng ◽  
Zhaohui Wu ◽  
Jian Wu
Keyword(s):  
Bipartite Graph ◽  
Service Discovery ◽  
Graph Matching ◽  
Information Model ◽  
Recall Rate ◽  
Two Phase ◽  
Service Oriented Computing ◽  
Service Oriented ◽  
Series Of Experiments ◽  
Discovery Method

To discover services efficiently has been regarded as one of important issues in the area of Service Oriented Computing (SOC). This article carries out a survey on the issue and points out the problems for the current semantic-based service discovery approaches. After that, an information model for registered services is proposed. Based on the model, it brings forward a two-phase semantic-based service discovery method which supports both the operation matchmaking and operation-composition matchmaking. Th authors import the bipartite graph matching to improve the efficiency of matchmaking. An implementation of the proposed method is presented. A series of experiments show that the method gains better performance on both discovery recall rate and precision than a traditional matchmaker and it also scales well with the number of services being accessed.

An Efficient Service Discovery Method and its Application

2009 ◽  
Vol 6 (4) ◽  
pp. 94-117 ◽  
Author(s):  
Shuiguang Deng ◽  
Zhaohui Wu ◽  
Jian Wu ◽  
Ying Li ◽  
Jianwei Yin
Keyword(s):  
Bipartite Graph ◽  
Service Discovery ◽  
Graph Matching ◽  
Information Model ◽  
Recall Rate ◽  
Two Phase ◽  
Service Oriented ◽  
Series Of Experiments ◽  
Bipartite Graph Matching ◽  
Discovery Method

To discover services efficiently has been regarded as one of important issues in the area of Service Oriented Computing (SOC). This article carries out a survey on the issue and points out the problems for the current semantic-based service discovery approaches. After that, an information model for registered services is proposed. Based on the model, it brings forward a two-phase semantic-based service discovery method which supports both the operation matchmaking and operation-composition matchmaking. The authors import the bipartite graph matching to improve the efficiency of matchmaking. An implementation of the proposed method is presented. A series of experiments show that the method gains better performance on both discovery recall rate and precision than a traditional matchmaker and it also scales well with the number of services being accessed.

The Extended Algorithm of the Bipartite Graph Matching Semantic Web Service Discovery

2014 ◽  
Vol 886 ◽  
pp. 677-680
Author(s):  
Bing Yue Liu
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Bipartite Graph ◽  
Service Discovery ◽  
Graph Matching ◽  
Recall Rate ◽  
Semantic Web Service ◽  
Web Service Discovery ◽  
Bipartite Graph Matching ◽  
Semantic Web Service Discovery

In previous work, the ontology-based algorithm of bipartite graph matching semantic web service discovery was presented. But in these algorithms, the problem of finding augment path was not resolved very well. It will affect the recall rate and precision rate of web service discovery. In order to resolve these problems, this paper proposes an ontology-based bipartite graph matching semantic web service discovery algorithm, which extends the optimal bipartite graph matching algorithm. It uses the slack function to find the augment path in the equivalent sub graph. The algorithm also contributes to the improvement of the recall rate and precision rate of the service discovery.

Distributed and Adaptive Service Discovery Using Preference

2010 ◽  
pp. 396-424
Author(s):  
Ryota Egashira ◽  
Akihiro Enomoto ◽  
Tatsuya Suda
Keyword(s):  
Service Discovery ◽  
Service Providers ◽  
End Users ◽  
Research Community ◽  
End User ◽  
Network Service ◽  
Preference Information ◽  
Extensive Simulation ◽  
Service Oriented Computing ◽  
Service Oriented

In Service-Oriented Computing, service providers publish their services by deploying service components which implement those services into a network. Since such services are distributed around the network, Service-Oriented Computing requires the functionality to discover the services that meet certain criteria specified by an end user. In order to overcome the scalability issue that the current centralized discovery mechanism inherently has, distributed discovery mechanisms that the P2P research community has developed may be promising alternatives. This chapter outlines existing distributed mechanisms and proposes a novel discovery mechanism that utilizes end users’ preferences. The proposed mechanism allows end users to return their feedback that describes the degree of the preference for discovered services. The returned preference information is stored at nodes and utilized to decide where to forward subsequent queries. The extensive simulation demonstrates that the proposed mechanism meets key requirements such as selectivity, efficiency and adaptability.

scholarly journals POOR TEXTURAL IMAGE MATCHING BASED ON GRAPH THEORY

2016 ◽  
Vol XLI-B3 ◽  
pp. 741-747 ◽  
Author(s):  
Shiyu Chen ◽  
Xiuxiao Yuan ◽  
Wei Yuan ◽  
Yang Cai
Keyword(s):  
Computer Vision ◽  
Image Matching ◽  
Urban Areas ◽  
Graph Matching ◽  
Recall Rate ◽  
Edge Weight ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Low Contrast ◽  
Series Of Experiments

Image matching lies at the heart of photogrammetry and computer vision. For poor textural images, the matching result is affected by low contrast, repetitive patterns, discontinuity or occlusion, few or homogeneous textures. Recently, graph matching became popular for its integration of geometric and radiometric information. Focused on poor textural image matching problem, it is proposed an edge-weight strategy to improve graph matching algorithm. A series of experiments have been conducted including 4 typical landscapes: Forest, desert, farmland, and urban areas. And it is experimentally found that our new algorithm achieves better performance. Compared to SIFT, doubled corresponding points were acquired, and the overall recall rate reached up to 68%, which verifies the feasibility and effectiveness of the algorithm.

scholarly journals POOR TEXTURAL IMAGE MATCHING BASED ON GRAPH THEORY

2016 ◽  
Vol XLI-B3 ◽  
pp. 741-747
Author(s):  
Shiyu Chen ◽  
Xiuxiao Yuan ◽  
Wei Yuan ◽  
Yang Cai
Keyword(s):  
Computer Vision ◽  
Image Matching ◽  
Urban Areas ◽  
Graph Matching ◽  
Recall Rate ◽  
Edge Weight ◽  
Matching Problem ◽  
Matching Algorithm ◽  
Low Contrast ◽  
Series Of Experiments

Image matching lies at the heart of photogrammetry and computer vision. For poor textural images, the matching result is affected by low contrast, repetitive patterns, discontinuity or occlusion, few or homogeneous textures. Recently, graph matching became popular for its integration of geometric and radiometric information. Focused on poor textural image matching problem, it is proposed an edge-weight strategy to improve graph matching algorithm. A series of experiments have been conducted including 4 typical landscapes: Forest, desert, farmland, and urban areas. And it is experimentally found that our new algorithm achieves better performance. Compared to SIFT, doubled corresponding points were acquired, and the overall recall rate reached up to 68%, which verifies the feasibility and effectiveness of the algorithm.

scholarly journals An IOTA-Based Service Discovery Framework for Fog Computing

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 844
Author(s):  
Tsung-Yi Tang ◽  
Li-Yuan Hou ◽  
Tyng-Yeu Liang
Keyword(s):  
Service Discovery ◽  
Fog Computing ◽  
Cost Effective ◽  
Public Access ◽  
Hash Tables ◽  
Network Attacks ◽  
Comprehensive Information ◽  
Data Flows ◽  
Multiple Levels ◽  
Discovery Method

With the rise in fog computing, users are no longer restricted to only accessing resources located in central and distant clouds and can request services from neighboring fog nodes distributed over networks. This can effectively reduce the network latency of service responses and the load of data centers. Furthermore, it can prevent the Internet’s bandwidth from being used up due to massive data flows from end users to clouds. However, fog-computing resources are distributed over multiple levels of networks and are managed by different owners. Consequently, the problem of service discovery becomes quite complicated. For resolving this problem, a decentralized service discovery method is required. Accordingly, this research proposes a service discovery framework based on the distributed ledger technology of IOTA. The proposed framework enables clients to directly search for service nodes through any node in the IOTA Mainnet to achieve the goals of public access and high availability and avoid network attacks to distributed hash tables that are popularly used for service discovery. Moreover, clients can obtain more comprehensive information by visiting known nodes and select a fog node able to provide services with the shortest latency. Our experimental results have shown that the proposed framework is cost-effective for distributed service discovery due to the advantages of IOTA. On the other hand, it can indeed enable clients to obtain higher service quality by automatic node selection.

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