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Internetworking and the Internet of Things

Meeting the business and science challenges posed by the IoT

Our research is addressing the challenges of integrating ‘wired’ and ‘wireless’ infrastructures to enable better connectivity and accessibility to services, and managing the large collections of distributed resources.

Our research

The internet is undergoing a great revolution ignited by a range of new technologies such as 5G networks and Internet of Things eco-systems that are impacting many areas in business and science. A number of international initiatives are attempting to explore the applicability of these new technologies. Also, with the wide availability of low-cost computers and pervasive network connectivity, many organisations are facing the need to manage large collections of distributed resources. These might include personal workstations, dedicated nodes in a distributed application such as a server farm, objects stored on these computers, or even external components such as drones and sensors.

There is also the need to integrate ‘wired’ and ‘wireless’ infrastructures to enable better connectivity and access to a wider range of services. Configurations of these systems change rapidly, failures and changes in connectivity are the norm, and significant adaptation may be required if the application is to maintain desired levels of service. To an increasing degree applications are expected to be self configuring, self managing and self healing. As the range of permissible configurations grows, this expectation becomes an enormously complex undertaking. Indeed, the management subsystem for a contemporary distributed system (that is, a web services system reporting data collected from a set of corporate databases, file systems and other resources) is often more complex than the application itself.

Key projects

Our expert: Professor Albert Zomaya

Our partner: Associate Professor Javid Taheri (University Karlstad, Sweden)

Industry partner: Ericsson AB, Sweden

This project aims to design the overall cross-layered network architecture for general purpose SDN networks. It includes defining and modelling all networking components for both horizontal and vertical communications between SDN nodes, and using optimisation techniques to solve the aforementioned model. For example, the proposed model will consider link characteristics among SDN links (bandwidth, latency and jitter) as well as QoS requirements of flows (maximum tolerable latency and minimum required bandwidth) and provide detailed solutions about how capacity of SDN links must be allocated to different flows.

Our experts: Professor Albert Zomaya, Dr Wei Bao, Dr Wei Li

Our partners: Professor Paulo Pires and Professor Flavia Delicato (Federal University of Rio de Janeiro)

Industry partner: Data61

This project aims to investigate the problem of resource management in IoT systems from a broad perspective. The core issue is how to allocate the resources available in the heterogeneous IoT system to accommodate the requirements imposed by multiple and heterogeneous applications. Algorithms and solutions for task scheduling and resource allocation tailored for the stringent requirements of IoT systems will be proposed and assessed. We will focus on IoT systems composed of three architectural tiers – the Things tier, the Cloud tier and an intermediary tier concretised by the Edge/Fog tier.

Our experts: Professor Albert Zomaya, Dr Wei Li

Our partners: Professor Paulo Pires and Professor Flavia Delicato (Federal University of Rio de Janeiro)

The goal of this project is to specify a light virtualisation model for edge computing that considers the heterogeneous and dynamic characteristics of current Internet applications. We are particularly interested in proposing a virtualisation model tailored to the requirements of time-critical applications for the Internet of Things.

Our experts: Dr Wei Bao

One challenge in fog computing systems is how to seamlessly hand over mobile IoT devices among different computation access points when computation offloading is in action, so that the offloading service is not interrupted – especially for those time-sensitive applications. In this project we establish Follow Me Fog, a framework supporting a new seamless handover timing scheme among different computation access points.

Our experts: Dr Dong Yuan

With the proliferation of Internet of Things (IoT) applications, many protocols have been proposed for the development of IoT applications, including constrained application protocol (CoAP), message queue telemetry transport (MQTT), data distribution service (DDS) and advanced message queuing protocol (AMQP). These protocols are powerful tools to manage the data communication over Internet Protocol and have different features to support the needs of IoT applications. However, software developers cannot fully understand the performance of these protocols by only reading their specifications.

In this project, we are developing a testbed where different protocols can be easily deployed and tested. Comparisons can be made in terms of latency, bandwidth consumption, ease of configuration etc., which will be helpful for developers to choose the most suitable protocol for their IoT applications. 

Our experts: Dr Wei Li, Professor Ting Yang, Professor Albert Zomaya

Industry partner: Global Energy Interconnection Development and Cooperation Organisation, State Grid Corporation of China

This project aims to investigate and implement an emerging vertical use case for Internet of Things (IoT) called Internet of Energy (IoE), which is a vast, smart and connected energy network that efficiently supplies electricity to anyone anywhere. Such systems are instances of the energy cloud that indicate a paradigm shift from the traditional and centralised energy generation and distribution architecture toward a networked and dynamic infrastructure.

IoE systems incorporate demand-based hybrid generation technologies and capabilities using green/renewable energy sources combined with other types of energy sources. Within IoE systems IoT applications drive the intelligence to the edge of the systems by collecting and processing the sensing information and coupling massive sensing and control to accomplish advanced levels of optimisation and energy efficiency.

By using distributed and scalable IoT systems, the IoE systems can be operated and managed at a local, national or even international level.