Service Composition In Internet Of Things Research Articles

Trust-Based Service Management for Social Internet of Things Systems

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 versus 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.

An Experimental Study for Intelligent Logistics: A Middleware Approach

Recent years have witnessed a rapid growth in using Internet of things (IoT), which facilitates and simultaneously raises challenges for the intelligent logistics. The real-world devices can provide their functionality as Web services. Because of the dynamicity and heterogeneity of the target networking environment, the services offered by IoT resources cannot be composed by simply extending existing Service oriented architecture (SOA) approaches. Logistics, which consists of a complex network of organizations and business processes, must be monitored in real time. Based on the proper understanding of the possible exceptions, we propose a middleware approach to solve the logistics service composition in IoT, where a decentralized coordination mechanism is used to monitor the component services with few resources efficiently. Through a set of experiments, the effectiveness and robustness of our approach are evaluated.

Optimal algorithm for Internet-of-Things service composition based on response time

In the near future, the Internet-of-Things (IoT) technology will improve dramatically our daily life as a new pervasive computing paradigm. For the IoT computing, various devices and wireless networks are the hardware infrastructure, and Service-Oriented Architecture (SOA) is a valuable software system that allows heterogeneous devices to interoperate each other. Even though IoT researchers have tackled a number of challenges for service composition, the orchestration techniques on IoT are rarely studied yet. Moreover, it is hard to automatically compose IoT services with an optimal aggregate response time since we have to compare all the combinations of parallel/serial structures in a composite IoT service. In the SOA literature, many researches on QoS-aware composition consider parallel work-flows, but they employ service selection models that require users to manually or semi-automatically predefine a top-level work process. Accordingly, they cannot guarantee the optimal solution. In this paper, we hence propose a novel IoT service composition algorithm which automatically produces a composite IoT service with a minimal response time.

Network Aware Composition for Internet of Thing Services

To enhance the adoption of Internet of Things (IoT) philosophy for the internet, research into IoT service composition has gathered momentum. In a distributed IoT environment, identifying IoT service among a set of similar service offerings that meets both functional and performance requirements of an IoT application has become important. However, the performance of a service cannot be guaranteed. Therefore service’s QoS and network characteristics are required to aggregate IoT services. Most existing composition approaches only consider non-network related QoS properties at the application tier. However they do not consider the network parameters such as network latency at the application level in selection and composition of services. Therefore we propose two evolutionary algorithms for IoT service composition that consider not only QoS but also network latency at the IoT application layer. The algorithms are discussed and results of evaluation are presented. The results indicate that our algorithms are efficient in finding QoS optimal and low latency solutions.