Fog Computing Initiative


The Internet of Things (IoT) paradigm promises to make "things" such as physical objects with sensing capabilities and/or attached with tags, mobile objects such as smart phones and vehicles, consumer electronic devices and home appliances such as fridge, television, healthcare devices, as part of the Internet environment. In cloud-centric IoT applications, the sensor data from these “things” is extracted, accumulated and processed at the public/private clouds, leading to significant latencies. Fog computing addresses this issue in developing real-time IoT applications, by mainly utilizing proximity based computational resources across the IoT layers such as gateways, cloudlets and network switches/routers. Similar approach of utilizing proximity resources in telecommunication domain is the Mobile Edge computing. Recently, there is also significant discussion in the similar lines with other approaches such as Mist computing and Dew computing.

To realize the full potential of Fog computing and similar paradigms, researchers and practitioners need to address several challenges and develop suitable conceptual and technological solutions for tackling them. These include development of scalable architectures, moving from closed systems to open systems, dealing with privacy and ethical issues involved in data sensing, storage, processing, and actions, designing interaction protocols, and autonomic management.

CLOUDS Lab at Melbourne is actively working on developing tools and technologies for Fog Computing. They include a Simulator (iFogSim), applications combining IoT, mobile, and clouds in areas such as healthcare, creating Fog environment using IoT devices, Fog devices (Raspberry pi) and enterprise/public clouds.

Related Projects


iFogSim enables modelling and simulation of Fog computing environments for evaluation of resource management and scheduling policies across edge and cloud resources under different scenarios. The simulator supports evaluation of resource management policies focusing on their impact on latency (timeliness), energy consumption, network congestion and operational costs. It simulates edge devices, cloud data centers, and network links to measure performance metrics. The major application model supported by iFogSim is the Sense-Process-Actuate model. In such models, sensors publish data to IoT networks, applications running on Fog devices subscribe to and process data coming from sensors, and finally insights obtained are translated to actions forwarded to actuators.

Download iFogSim here. More information can be found in our SPE paper.


: Fog and Edge Computing: Principles and Paradigms


: ICFEC 2018 in USA

Project Team Members

Active Members:

Former Members and Collaborators:


Some publications using iFogSim - External Users

Cloud Computing and Distributed Systems (CLOUDS) Laboratory
School of Computing and Information Systems
The University of Melbourne, Australia