Cognitive Aware Smart Service Composition

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The Internet is becoming a global infrastructure to host heterogeneous services. Generally speaking, there are two types of services running on the Internet: (1) web services (e.g., on-line stores) are hosted by servers and provide users with software functionality by communicating with other web services; and (2) Internet of Things (IoT) services (e.g., thermostat apps) that directly communicate with hardware devices (e.g., thermostat) and make a direct impact to the environment (e.g., changing the room temperature). Despite the increasing use of the services on the Internet to support human activities, most on-line activities are performed manually. There is limited intelligent support to facilitate the interactions between human and machines. In this project, we collaborate with our industrial collaborators in IBM Canada to build a smart service composition framework that can perceive end-users' situational needs, automatically support end-users to conduct on-line tasks and reduce human cognitive burden. We aim to utilize machine learning algorithms to learn end-users' on-line activities and preferences over time to improve our service recommendation. The proposed project will focus on three aspects:1) Building a smart personal agent framework that can seamlessly integrate the traditional web services and IoT services, and enable an agent to act on behalf of an end-user in performing on-line tasks; 2) Creating analytics and predictive engines that track various information sources, analyze the information, and recommend services to end-users; and 3) Developing a multi-agents collaboration infrastructure that allows personal agents of various roles to communicate and interact on behalf of their end-users to achieve a common goal. The results of our proposed project can allow end-users to create smart environments to be responsive to their needs and help improve the quality of their lives in various domains, such as e-health, e-commerce, financial services, and assisted living. This project will train 10 HQP (2 PhD, 4MSc, and 4 BSc) in the important area of software engineering, specifically SOA and IoT software.