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Ranking Services by Service Network Structure and Service Attributes
"... Abstract — Web service ranking is an essential functionality in web service discovery, search, mining and recommendation. Many popular web service networks are content-rich in terms of heterogeneous types of entities, attributes and links. A main challenge for ranking services is how to incorporate ..."
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Abstract — Web service ranking is an essential functionality in web service discovery, search, mining and recommendation. Many popular web service networks are content-rich in terms of heterogeneous types of entities, attributes and links. A main challenge for ranking services is how to incorporate multiple complex and heterogeneous factors, such as service attributes, relationships among services, relationships between services and service providers or service consumers, into the design of service ranking functions. In this paper, we model services, attributes, and the associated entities, such as providers, consumers, by a heterogeneous service network. We propose a unified neighborhood random walk distance measure, which integrates various types of links and vertex attributes by a local optimal weight assignment. Based on this unified distance measure, a reinforcement algorithm, ServiceRank, is provided to tightly integrate ranking and clustering by mutually and simultaneously enhancing each other such that the performance of both can be improved. An additional clustering matching strategy is proposed to efficiently align clusters from different types of objects. Our extensive evaluation on both synthetic and real service networks demonstrates the effectiveness of ServiceRank in terms of the quality of both clustering and ranking among multiple types of entity, link and attribute similarities in a service network. I.
Trust-based Service Management for Social Internet of Things Systems
- IEEE Trans. on Dependable and Secure Computing
"... Abstract — A social Internet of Things (IoT) system can be viewed as a mix of traditional peer-to-peer networks and social networks, where “things ” autonomously establish social relationships according to the owners ’ social networks, and seek trusted “things ” that can provide services needed when ..."
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Abstract — A social Internet of Things (IoT) system can be viewed as a mix of traditional peer-to-peer networks and social networks, where “things ” autonomously establish social relationships according to the owners ’ social networks, and seek trusted “things ” that can provide services needed when they come into contact with each other opportunistically. We propose and analyze the design notion of adaptive trust management for social IoT systems in which social relationships evolve dynamically among the owners of IoT devices. We reveal the design tradeoff between trust convergence vs. trust fluctuation in our adaptive trust management protocol design. With our adaptive trust management protocol, a social IoT application can adaptively choose the best trust parameter settings in response to changing IoT social conditions such that not only trust assessment is accurate but also the application performance is maximized. We propose a table-lookup method to apply the analysis results dynamically and demonstrate the feasibility of our proposed adaptive trust management scheme with two real-world social IoT service composition applications.
Clustering Service Networks with Entity, Attribute and Link Heterogeneity
"... Abstract—Many popular web service networks are content-rich in terms of heterogeneous types of entities and links, associated with incomplete attributes. Clustering such hetero-geneous service networks demands new clustering techniques that can handle two heterogeneity challenges: (1) multiple types ..."
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Abstract—Many popular web service networks are content-rich in terms of heterogeneous types of entities and links, associated with incomplete attributes. Clustering such hetero-geneous service networks demands new clustering techniques that can handle two heterogeneity challenges: (1) multiple types of entities co-exist in the same service network with multiple attributes, and (2) links between entities have diverse types and carry different semantics. Existing heterogeneous graph clustering techniques tend to pick initial centroids uniformly at random, specify the number k of clusters in advance, and fix k during the clustering process. In this paper, we propose SERVICECLUSTER, a novel heterogeneous SERVICE network CLUSTERing algorithm with four unique features. First, we incorporate various types of entity, attribute and link information into a unified distance measure. Second, we design a Discrete Steepest Descent method to naturally produce initial k and initial centroids simultaneously. Third, we propose a dynamic learning method to automatically adjust the link weights towards clustering convergence. Fourth, we develop an effective optimization strategy to identify new suitable k and k well-chosen centroids at each clustering iteration. I.
Chapter 1 Trust-Oriented Service Provider Selection in Complex Online Social Networks
"... Abstract In recent years, Online Social Networks (OSNs) with numerous partici-pants have been used as the means for rich activities. For example, employers could use OSNs to investigate potential employees, and participants could use OSNs to look for movie recommendations. In these activities, trust ..."
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Abstract In recent years, Online Social Networks (OSNs) with numerous partici-pants have been used as the means for rich activities. For example, employers could use OSNs to investigate potential employees, and participants could use OSNs to look for movie recommendations. In these activities, trust is one of the most impor-tant indication of participants decision making, greatly demanding the evaluation of the trustworthiness of a service provider along certain social trust paths from a service consumer. In this chapter, we first analyze the characteristics of the current generation of functional websites and the current generation of online social net-works based on their functionality and sociality, and present the properties of the new generation of social network based web applications. Then we present a new selection model considering both adjacent and end-to-end constraints, based on a novel concept Quality of Trust and a novel complex social network structure. More-over, in order to select the optimal one from massive social trust paths yielding the most trustworthy trust evaluation result, this chapter presents an effective and ef-ficient heuristic algorithm for optimal social trust path selection with constraints, which is actually an NP-Complete problem. Experimental results illustrate that the proposed method outperforms existing models in both efficiency and the quality of delivered solutions. This work provides key techniques to potentially lots of service-oriented applications with social networks as the backbone.
