Towards the Advanced Data Processing for Medical Applications Using Task Offloading Strategy

Alekseeva, Daria; Ometov, Aleksandr; Lohan, Elena Simona

doi:10.1109/wimob55322.2022.9941708

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…XR scenario corresponding to remote Augmented Reality (AR) Assisted Telesurgery, is a used example of extremely high data rate with intensive workload and static modality, detailed in Table III, based on the standartisation summary [35].…”

Section: A Test Scenariosmentioning

confidence: 99%

Demystifying Usability of Open-Source Computational Offloading Simulators: Performance Evaluation Campaign

Alekseeva,

Ometov,

Lohan

2023

IEEE Sensors J.

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Along with analysis and practical implementation, simulations play a key role in wireless networks and computational offloading research for several reasons. First, the simulations provide the ability to easily obtain the data for a complex system's model evaluation. Secondly, simulated data provides a controlled environment for experimentation, allowing models and algorithms to be tested for robustness and identifying potential limitations before deploying them in real-world applications. Choosing the most appropriate tool for simulation might be challenging and depends on several factors, such as the main purpose, complexity of data, researcher skills, community support, and available budget. As of the time of the present analysis, several system-level open-source tools for modeling computational offloading also cover the systems' communications side, such as CloudSim, CloudSim Plus, IoTSim-Edge, EdgeCloudSim, iFogSim2, PureEdgeSim, and YAFS. This work presents an evaluation of those based on the unique features and performance results of intensive workload-and delay-tolerant scenarios: XR with an extremely high data rate and workload; remote monitoring with a low data rate with moderate delays and workload requirements; and data streaming as a general human traffic with a relatively high bit rate but moderate workload. The work concludes that CloudSim provides a reliable environment for virtualization on the host resources, while YAFS shows minimal hardware usage, while IoTSim-Edge, PureEdgeSim, and EdgeCloudSim have fewer implemented features.

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Section: A Test Scenariosmentioning

confidence: 99%

Demystifying Usability of Open-Source Computational Offloading Simulators: Performance Evaluation Campaign

Alekseeva,

Ometov,

Lohan

2023

IEEE Sensors J.

Self Cite

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Hybrid Edge-Cloud Computational Offloading for XR Medical Applications

Alekseeva,

Ometov

2024

2024 9th International Conference on Fog and Mobile Edge Computing (FMEC)

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Artificial Intelligence to Reshape the Healthcare Ecosystem

Reali,

Femminella

2024

Future Internet

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This paper intends to provide the reader with an overview of the main processes that are introducing artificial intelligence (AI) into healthcare services. The first part is organized according to an evolutionary perspective. We first describe the role that digital technologies have had in shaping the current healthcare methodologies and the relevant foundations for new evolutionary scenarios. Subsequently, the various evolutionary paths are illustrated with reference to AI techniques and their research activities, specifying their degree of readiness for actual clinical use. The organization of this paper is based on the interplay three pillars, namely, algorithms, enabling technologies and regulations, and healthcare methodologies. Through this organization we introduce the reader to the main evolutionary aspects of the healthcare ecosystem, to associate clinical needs with appropriate methodologies. We also explore the different aspects related to the Internet of the future that are not typically presented in papers that focus on AI, but that are equally crucial to determine the success of current research and development activities in healthcare.

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Towards the Advanced Data Processing for Medical Applications Using Task Offloading Strategy

Cited by 3 publications

References 22 publications

Demystifying Usability of Open-Source Computational Offloading Simulators: Performance Evaluation Campaign

Demystifying Usability of Open-Source Computational Offloading Simulators: Performance Evaluation Campaign

Hybrid Edge-Cloud Computational Offloading for XR Medical Applications

Artificial Intelligence to Reshape the Healthcare Ecosystem

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