Yannong Huang's scientific contributions

The services composition technology provides flexible methods for building service composition applications (SCAs) in wireless sensor networks (WSNs). The high reliability and high performance of SCAs help services composition technology promote the practical application of WSNs. The optimization methods for reliability and performance used for traditional software systems are mostly based on the instantiations of software components, which are inapplicable and inefficient in the ever-changing SCAs in WSNs. In this paper, we consider the SCAs with fault tolerance in WSNs. Based on a Universal Generating Function (UGF) we propose a reliability and performance model of SCAs in WSNs, which generalizes a redundancy optimization problem to a multi-state system. Based on this model, an efficient optimization algorithm for reliability and performance of SCAs in WSNs is developed based on a Genetic Algorithm (GA) to find the optimal structure of SCAs with fault-tolerance in WSNs. In order to examine the feasibility of our algorithm, we have evaluated the performance. Furthermore, the interrelationships between the reliability, performance and cost are investigated. In addition, a distinct approach to determine the most suitable parameters in the suggested algorithm is proposed.

Services composition technology provides a flexible approach to building Cloud Service Applications (CSA) in Cloud Service system. The data security is a crucial issue in cloud service system, which affects the data reliability and service performance. Maintaining the data security, reliability and performance in CSA at the same time is a real challenge faced by researchers attempting to develop CSA. This issue involves the optimal service distribution in cloud service system subject to data security constraints. In this paper, we consider a cloud service system in which the Cloud Services Broker (CSB), as the resource management center, can map the service request into a set of atomservices and send them to different virtual machines (VMs) after receiving a service request from users. CSB can also dynamically control the startup, access to, and sharing of data resources located in VMs. By the optimal service partition into the atom-services and their distribution among VMs, the CSB can provide the greatest possible service reliability and/or expected performance subject to data security constraints. This paper proposes an algorithm of optimal service partition and distribution based on the universal generating function (UGF) technique and on the genetic algorithm (GA) approach. The experimental analysis is given to demonstrate the feasibility of the suggested algorithm.