PACE: Privacy-Aware Cloud Ecosystems
Lead Research Organisation:
Newcastle University
Department Name: Sch of Computing
Abstract
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Organisations
Publications
Marikyan D
(2022)
"Alexa, let's talk about my productivity": The impact of digital assistants on work productivity
in Journal of Business Research
Al-Khafajiy M
(2020)
COMITMENT: A Fog Computing Trust Management Approach
in Journal of Parallel and Distributed Computing
Alwasel K
(2021)
IoTSim-Osmosis: A framework for modeling and simulating IoT applications over an edge-cloud continuum
in Journal of Systems Architecture
Singh M
(2020)
Blockchain-enabled secure communication for drone delivery
Marikyan D
(2021)
Privacy & Cloud Services: Are We There Yet?
Marikyan D
(2021)
General data protection regulation
Description | Our experiments reveal that existing consensus algorithms (e.g., proof-of-X, practical Byzantine fault tolerance) for DLT platforms, such as Ethereum, have high computation and communication overhead. Hence, we need to investigate a new lightweight consensus approach, which will adopt cryptography mechanisms (such as digital signature, and device trust) to authenticate blocks within the network of trusted IoT/Edge devices, instead of evaluating them using expensive cryptographic puzzles. We will also need to investigate new algorithms for computing dynamic trust value for IoT/Edge devices and Cloud servers, which will take into account various run-time parameters including statistics related to false block authentication. |
Exploitation Route | The growing decentralisation, digitalisation, and complexity of energy systems (e.g., microgrids) is making central management and operation challenging. Distributed control and management techniques are required to handle these trends. Blockchains or Distributed Ledger Technologies (DLT), primarily designed to manage distributed transactions by removing central control, could help address the challenges surrounding decentralised energy systems (i.e, microgrids). |
Sectors | Energy Healthcare Manufacturing including Industrial Biotechology |
Title | IoTSim-OSmosis |
Description | Osmotic computing paradigm sets out the principles and algorithms for simplifying the deployment of Internet of Things (IoT) applications in integrated edge-cloud environments. Osmotic Computing focuses on strategies and mechanisms to extend the IoT capabilities by defining, designing, and implementing a modern computing model (IoT, edge, cloud, and SD-WAN). IoTSim-Osmosis is a simulation framework that supports the testing and validation of osmotic computing applications. In particular, it enables a unified modelling and simulation of complex IoT applications over heterogeneous edge-cloud SDN-aware environments. IoTSim-Osmosis is capable of capturing the key functions, characteristics, and behaviors of osmotic paradigm. A wide range of osmosis applications can be simulated and evaluated in IoTSim-Osmosis. To handle the complexity and diversity of osmotic applications, IoTSim-Osmosis provides an abstract mechanism called Microelements (MELs), which encapsulates services, resources and data. In particular, any IoT applications can be represented using a graph of MELs as shown in the figure below. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | The tool is being used by academic and industrial research communities. It has also motivated further research in this area. https://scholar.google.com/scholar?oi=bibs&hl=en&cites=17488445812004146680 |
URL | https://rajivranjan.net/iotsim/iotsim-release/ |