The goal of this research is to overcome the challenges of cyber-physical systems in the Internet of Things. The challenges include: interoperability, autonomous machine-to-machine communication, automatic configuration, energy efficiency, trustworthiness etc.
Today, a common vision of Internet of Things (IoT) represents a global network interconnected with various electronic devices in a meaningful manner. The devices consist of Radio Frequency Identification (RFID)-attached objects, EPCGlobal Network-connected objects and a variety of internet-enabled objects such as mobile phones, smart watches, vehicles, sensors, home appliance and so on. As described by European Commission Information Society and Media (2009), the fundamental idea of IoT is to allow “people and things to be connected Anytime, Anyplace, with Anything and Anyone, ideally using Any path/network and Any service“. The US National Intelligence Council has predicted that “by 2025 Internet nodes may reside in everyday things–food packages, furniture, paper documents, and more“.
IoT technologies can be applied in various scenarios. E.g., combining the augmented reality technology with IoT, a system can help disabled people to perform many daily activities such as travel, shopping, operating appliances etc. In the enterprise domain, the EPCGlobal Network system provides a convenient way for product transporting and tracking processes. Other scenarios include the domains in transportation, healthcare, smart environment, social networking and so on.
Although various IoT projects are progressing, there are still many challenges remain unsolved.
- Interoperability. Most existing IoT solutions were built in isolation. Currently, the IoT environment still lack a feasible solution to enable the interaction among these heterogeneous fragments in a highly distributed environment. Assumption such as centralised mediation services are inapplicable and unrealistic.
- Autonomous Machine-to-Machine (M2M) communication. Autonomous M2M communication enables the cyber-physical systems to provide self-managed services to ease people’s daily life. However, such systems face service discovery challenges because existing Web-based service discovery mechanisms were not designed for resource constrained devices, which are major entities in IoT environments.
- Automatic Configuration. Most existing IoT solutions were proposed for domain specific applications. They cannot be directly applied to different scenarios. It is due to the lack of automatic configuration mechanism. Furthermore, the autonomous system also require self-management, self-healing and self-optimisation mechanisms.
- Energy Efficient Service Provisioning. Resource constrained devices such as sensors, actuators and mobile devices, which rely on battery power, are the major objects of IoT. In order to interact with these devices in the autonomous M2M manner, they need to provide some forms of networked services. However, the existing SOA-based service provisioning approaches such as HTTP-based REST or SOAP were fundamentally not designed for resource constrained IoT devices, and are considered as heavyweight in terms of energy consumption.
- Trustworthiness. Classic security strategies for Web services face the challenges in IoT because the limitations in terms of: (1) hard to control the identification of IoT participants; (2) centralised control is unrealistic; (3) heavy data transmission and overhead. One trend of improving IoT security is to apply the trust-based strategies. Trust strategies can be categorised into two types: (1) service requester aspect; (2) service provider aspect. Existing trust strategies for IoT were proposed only for the service requester aspect. There is still lack of a proper trust solution for preventing malicious service requesters from public accessible ‘Things’.
- Energy-efficient Things Framework
- Mobile-hosted Things Middleware (MHTM)
- Mobile-hosted Cloud Middleware (MHCM)
- Mobile Resource Composition Mediation Framework (MRCMF)
- Trustworthy Internet of Things
- Realtime Augmented Reality using Context-aware Cloud services with Mobile Hosts