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Research in
Energy Efficiency
Edge IoT Computing
Cloud Computing
Large-scale Network Infrastructures
Investigating ways to reduce the ICT sector’s CO2 emissions by leveraging the environmental benefits of edge and cloud computing for IoT devices and individual PC users. We are looking into the development of a multi-criteria decision mechanism to guide the choice of execution location. According to criteria such as the processing intensity and the data collected by a device, the energy consumed and the conditions of the network, there can be three potential choices: executing everything locally on the device, or on the edge device or offloading the execution to a more powerful but remote cloud infrastructure which would incur additional networking overhead.
We have also investigated the effect that deep sleep based power savings have on the quality of service of the backbone network. We investigated the tradeoff between power consumption and network performance by introducing enhanced neighbour discovery, where special queues at each node store and delay forwarding packets to next hop nodes that are in sleep mode.
For more information, please see my publications.
We have also investigated the effect that deep sleep based power savings have on the quality of service of the backbone network. We investigated the tradeoff between power consumption and network performance by introducing enhanced neighbour discovery, where special queues at each node store and delay forwarding packets to next hop nodes that are in sleep mode.
For more information, please see my publications.